While these models enable customers to flexibly customize their products, they are operationally taxing. Companies using the ETO model must manage complex products and coordinate with multiple stakeholders. They also face other challenges, including manual processes that result in longer lead times, inefficient change management causing costly reworks, and a high number of product tests due to the heavy customization. Fortunately, modern technologies and solutions exist to solve these challenges, including CAD-CPQ integration and PLM-ERP integration.

This article delves into how CAD-CPQ integration can support manufacturing companies as they embrace modern operational models to meet customers’ emerging needs. We will discuss the mechanics of this integration – including the solutions that provide this integration, the benefits of CAD-CPQ integration, real-world applications and success stories, its implementation, and much more. Let’s get started.

The Mechanics of CAD-CPQ Integration

As with other software, the CAD-CPQ integration is aided by application programming interfaces (APIs) and integration connectors. But before detailing the mechanics of this integration, how about we first discuss what CPQ is?

What is CPQ?

Short for Configure Price Quote, CPQ software enables users – mostly companies – to configure products, calculate the prices of the configured products, and generate quotations of the fabricated products in a way that aligns with the requirements of their customers. It is intended to automate processes, preventing, at a very early stage, errors in the configuration, prices, and quotes. In fact, the software automatically applies pricing changes whenever you modify the configured product. 

This ensures consistency and accuracy throughout the process, ultimately making prices and quotes more competitive. CPQ software is especially instrumental for ETO companies that receive a multitude of orders, some of which might include very complex products. This is because the solution enables them to deliver complex and distinctly designed parts and products in a standardized way.

CPQ software is primarily used by marketing and sales teams responsible for receiving customer orders and managing upselling. And given that the order must then reach the engineering and design team as well as other teams throughout the company for the design and manufacturing process to begin, there is a need to ensure the seamless flow of data. 

This, therefore, means that CPQ, CAD (computer-aided design), PDM (product data management), ERP (engineering or enterprise resource planning), and CRM (customer relationship management) systems, which different departments within the organization use, must be connected. This connection between data systems and departments is known as the digital thread.

To create the digital thread, systems must be connected. At the foundational level, where customer orders must reach the design team, a CAD-CPQ integration must exist to ensure data flow and connectedness.

Need for CAD-CPQ Integration

In an ideal setup, the CAD-CPQ integration should enable ordering customers to work from a point of knowledge. This means that customers should be able to view the products they wish to customize. In this case, the CPQ software, linked to a CAD database, takes data from the available 2D drawings and 3D models and displays the product or products on a dedicated section of the CPQ interface. 

Besides this capability, the interface should include tools that enable the customer to change various variables in a process known as configuration. Then, the solution should automatically calculate the cost based on the configuration and subsequently create a quote that considers all other manufacturing elements. 

What you may find with pure CPQ software, however, is the lack of a section on the user interface that displays CAD data for better visualization. In other cases, you may be using software incapable of generating technical CAD drawings. Unfortunately, this means that customers create orders without a visual reference, which can lead to errors. It also means the company must have designers and engineers on standby to draw the products in CAD. The CAD-CPQ integration, therefore, solves these problems. 

How CAD and CPQ Software Integrate

There are three ways of integrating CAD and CPQ software, namely:

1. Application programming interface (API)
2. Integration connector
3. Plugins

Application Programming Interface

As we mentioned earlier, APIs power the CAD-CPQ integration. APIs provide a set of rules and definitions that enable information to flow between two applications. They offer access to the platform and its capabilities by creating a bridge to support communication. 

To better understand how APIs enable CAD-CPQ integration, let’s take the example of Autodesk Platform Services(APS). APS comprises a growing set of APIs and services that power integrations, pre- and custom-built apps, and other innovative technologies. 

Within the context of CAD-CPQ integration, these APIs enable developers of web-based CPQ software to embed the APS Viewer in a web page that then displays 2D and 3D views of designs on their website. However, the process is much more elaborate than this, as it follows several steps. 

First, CAD designers upload product designs into the APS Design Automation API, which processes design files, generates drawings, and extracts data. Next, APS’s Model Derivative API takes over; it translates or converts designs into file formats that can be rendered in Viewer SDK, an Autodesk product. 

The next step is the responsibility of the APS Viewer API, which renders the 3D models within the browser, enabling the end-user to view the various products. To improve the viewing experience, developers can use another API, the Data Management API, to create an app that enables the users to view all the products.

By harnessing the power of APS’s APIs to link CAD to their solutions, developers can build web-based CDQ software that can display 2D drawings and 3D models. As a result of this CAD-CDQ integration, ETO manufacturers can display their entire catalog on the web, showing their customers what to expect. The catalog offers templates (2D drawings or 3D models) for customers to customize their products with. Then, the CPQ software automatically calculates the price and generates the quote.

Integration Connectors

The integration connectors are the more popular method of integrating CAD and CPQ software and other software required to implement the digital thread. Unlike an API, which is a set of rules that act as a bridge through which information flows, connectors are pieces of software that allow two applications to connect and transfer data. Connectors are existing pieces of software, meaning they are pre-built and ship with pre-configured settings that enable the exchange of information right off the bat.

To facilitate the CAD-CPQ integration, CPQ software developers provide integration connectors to external CAD systems. These connectors link both software, facilitating certain requests such as the generation of CAD documents. CPQ software like Epicor CPQ, Cincom CPQ, Elfsquad, and more use integration connectors.

Elsquad CPQ Software Interface (source)

Plugins

Some standalone CPQ software includes plugins that add CAD features after installation. For instance, DriveWorks Ltd. develops a collection of downloadable plugins called PowerPacks for its software, DriveWorks Pro. These plugins can perform numerous tasks. However, we will focus on the SolidWorks PowerPack.

SolidWorks PowerPack adds tasks like exporting a drawing table, inserting a block in a drawing, opening and saving SolidWorks files, exporting files, and more. This means that the installation of this plugin integrates the DriveWorks CPQ with SolidWorks CAD software. This CPQ-CAD integration enables you to manipulate SolidWorks within the DriveWorks CPQ interface. 

Impact of CAD-CPQ Integration by Industry

Implementing the digital thread through CAD-CPQ integration and other similar integrations has greatly benefited companies that employ the ETO strategy. This strategy is common in the construction of ships, machines, machine parts, buildings, and plants. Here, such companies design, engineer, fabricate, and assemble parts or products only after receiving the customer’s order. 

However, while the ETO model is meant to produce unique parts or products with a low probability of reappearance, thus saving costs, it gives rise to several new challenges, as mentioned earlier. For instance, ordering customers may submit requirements that, by and large, complicate the designs. And if a flurry of customers makes such orders, the issue compounds even further. 

Additionally, companies must coordinate with different suppliers and stakeholders to source parts that may not be in stock. What’s more, organizations that store technical, operational, and product information in siloed systems may also face delays and issues in accessing this vital data. And with having to conduct numerous tests to assess the performance and quality of the customized products, it is easy to see how this creates another issue. 

The solution to these challenges lies in integrations that connect various software such as CAD, CPQ, PLM, ERP, PDM, and CRM. And as has been observed in practice, such integrations do offer various benefits, as detailed below.

Impact of CAD-CPQ Integration in Manufacturing Industry

The benefits of CAD-CPQ integration as it relates to the manufacturing industry include:

1. Increased Productivity and Collaboration

CPQ software integrates with CAD, PLM, CRM, and other enterprise solutions, seamlessly linking design, engineering, manufacturing, and sales teams. In this regard, the integration eliminates the fragmentation of teams, promoting data flow and collaboration. The result is high productivity, with DriveWorks Ltd., the developer of the DriveWorks, noting that manufacturers using the product have achieved a 75% increase in productivity.

2. Improved Quoting

CPQ software automatically generates quotes. In addition, by connecting to CAD and ERP software, CPQ solutions can easily generate technical drawing files and bill of materials (BOM), all with the click of a button. The BOM lists all parts, assemblies, subassemblies, and materials required to create the part. It shows, in a tabular format, what was used to generate the quote, lending even more credence to the total price. 

This automated process takes only a fraction of the time it would take you to create the quote manually. In fact, DriveWorks notes that its CPQ achieves 95% faster quoting. Tacton, another CPQ provider, noted that companies that used its solution saw an 11% increase in the number of quotes per year. These companies also witnessed a +8% average win rate per quote.

Tacton’s Web-Based CPQ Software (source)

3. Time Savings

Codeo, a Turkey-based engineering firm that works with manufacturers that design and cell ETO products, notes that CAD-CPQ integration reduces the time it would take senior engineers to redesign customized versions of the same product. Codeo reports that tasks which previously took engineers 70 hours to complete manually now take only a few minutes. The time savings have also been experienced elsewhere, with Cadaq, a company that facilitates CPQ integrations, noting that its client now takes 2 hours to produce parts that would previously take 40 hours.

In addition to reducing the time it takes engineers to redesign parts, the CAD-CPQ integration also benefits the sales and marketing team. For its part, DriveWorks reports that its CPQ enables manufacturers to achieve 50% faster sales onboarding. Additionally, Tacton observed that the use of its CPQ software reduced by 34% the time sales personnel spent per quote. Similarly, Tacton CPQ reduced by 33% the time sales staff spent to revise quotes. 

4. Improved Operations/Business Growth

The time savings translate to savings elsewhere, including on labor costs. It is little wonder, then, that DriveWorks reports that manufacturers achieved 64% business growth with its CPQ solution.

5. Enhanced Customer Experience

As detailed earlier, the CAD-CPQ integration enables customers to visualize whatever they are configuring. Additionally, the integrated interface guides the customers throughout the ordering process. These features improve the customer experience and reduce or eliminate errors. 

Impact of CAD-CPQ Integration in Architecture and Construction Industry

Each construction project is unique. Whether it be a skyscraper, bridge, dam, or underground tunnel, the project will require the contractor and engineers to order custom structural components, glass facades, windows, steel frames, formworks, scaffoldings, and more. The impact of CAD-CPQ integration in the architecture and construction industry is similar to that experienced in manufacturing.

Behind the Scenes: The Tech Driving Integration

The success of a CAD-CPQ integration relies on a number of technologies, including cloud computing, artificial intelligence, and machine learning, just to mention a few.

Cloud Computing

Most CPQ software applications are cloud-based. These tools store data such as pricing, inventory, and sales in the cloud to improve consistency and speed of calculating prices and quoting. Cloud-based CPQ solutions make integrating with cloud-based CAD tools through APIs easy. Another advantage of cloud computing and cloud-based tools is that it ensures accessibility to customers.

Artificial Intelligence and Machine Learning

Just as AI is revolutionizing CAD, so is it changing CPQ as we know it. As it stands, the role of artificial intelligence and machine learning in the CPQ space is still nascent but is expected to play a more significant role in the future. For instance, CPQ developers hold that AI and ML will be able to recommend the best product configurations based on a large trove of data on past purchases, market trends, and customer purchases. 

Additionally, AI models, trained on customer behavior, competitor pricing, and factors like supply and demand, will enable CPQ software to dynamically change pricing in real time. In this regard, AI will ensure that the adjusted prices reflect prevailing market conditions and the customer’s background. Simply put, this application of AI will help manufacturers maximize profitability without sacrificing their competitiveness.

Another avenue that is ripe for disruption within the CPQ space is in quoting. AI is poised to birth intelligent quoting by generating personalized quotes that align with each customer’s preferences and previous practices. Moreover, AI and ML are expected to boost the predictive analysis of sales, allowing manufacturers to identify future opportunities or orders. Based on this analysis, manufacturers can stock certain materials, buy specific CNC machines and manufacturing tools, or customize tools.

Evolving Customer and Market Demands

Admittedly, there has been a noticeable shift in the manufacturing industry. As a result, manufacturing companies are transitioning from certain traditional practices to new ones to accommodate their customers’ changing needs and demands. So, how is the current manufacturing landscape set up? And what is prompting companies to embrace CAD-CPQ integrations, among other essential enterprise solutions?

Growing Demand for Customization and Personalization

Now more than ever, manufacturers are moving away from mass production and embracing customization. This is a response to the changing preferences among customers looking for tailored products. To accommodate this shift, manufacturers have adopted ETO models and integrated solutions that support customization, including CAD-CPQ products. But the changing consumer demands extend beyond merely placing customized orders. Users have other requirements as well.

Sustainability Requirements

There is no question that customers are becoming more environmentally conscious. Their increased environmental awareness stems from the increasingly apparent effects of climate change. As such, consumers are avoiding practices that may increase pollution and instead embracing sustainability. Supporting or, in some cases, driving the shift to sustainability are regulations and legislation that compel companies and end-users to prioritize environmental and social responsibilities.

To align with the sustainability requirements as well as regulatory standards, manufacturers are adopting tools that help them calculate the impact of their products on the environment. Some of these tools are available in configurators. These configurators, which are part of some CPQ software like Tacton’s, enable manufacturers to integrate sustainability into both the sales process and manufacturing. This way, these companies can appeal to the environmentally conscious consumer.

Digitally Savvy Customers

The modern-day consumer has access to digital tools and is vastly adept at using them. And in an age where developers emphasize and market their solutions as the yardsticks of great user experiences, consumers have grown accustomed to such seamless experiences. Against this backdrop, manufacturers have to provide digital tools for configuring ETO products. They must also ensure these tools are responsive, intuitive, and equally available online. 

In addition, manufacturers who embrace CAD-CPQ integration should always ensure their tools are available for customers to use 24/7. This requires selecting service providers who promise and deliver robust infrastructure for their online tools. The continued availability/uptime of such solutions guarantees that the customers continuously enjoy the perks of 3D visualization and the ability to generate CAD drawings within the CPQ interface, just as the CAD-CPQ integration envisions. It also accommodates the needs of the digitally savvy customer.

Conclusion

The future of manufacturing, at least based on customers’ changing preferences, lies in customization and engineer-to-order models. To meet the demands of customers and, as a result, maintain or boost profitability and competitiveness, manufacturers are integrating several technologies, one of which is the CAD-CPQ integration. This integration links CAD software to CPQ software. It enables customers to generate CAD drawings, visualize 2D and 3D models, and manipulate CAD software within the interface of the CPQ software as they configure their products. The CPQ software automatically calculates the price of the configured product and generates a quote. 

This CAD-CPQ integration, which can be completed using APIs, integration connectors, and plugins, has benefited manufacturers and players in the architecture and construction industry. For instance, it has increased productivity, reduced lead time, improved operations, and enhanced the customer experience. As technology advances, developers expect to package additional capabilities into their software, increasing the benefits even further and meeting the ever-changing needs of the customers.

Indeed, this mental image, which is perhaps influenced by the ubiquity of printing, accurately represents the mechanism behind 3DP. In fact, it corresponds with what the standards body ISO says about the technology: 3D printing is typically associated with machines used for personal use and other non-industrial purposes. So, it goes without saying that 3DP is restricted to the non-industrial creation of objects with a small form factor. This highlights a limitation of 3DP: it does not encompass manufacturing processes used in industrial scenarios for creating objects and parts of both large and small volumes. Instead, we use the term additive manufacturing, which can be referred to by its contracted form AM, to refer to this scenario. 

Additive manufacturing addresses the shortcomings of 3DP by more accurately capturing the scale and nature of the fabrication process. In fact, standards bodies and experts use additive manufacturing as the technical and more comprehensive name for both 3DP and rapid prototyping. Put simply, 3D printing and rapid prototyping are subsets of AM. Against this backdrop, what is additive manufacturing? What does it entail? This article answers these and more questions.

Understanding Additive Manufacturing

What is Additive Manufacturing?

The term additive manufacturing describes a process of using a digital 3D model, generated using 3D CAD software, to fabricate a 3D object directly by joining bulk materials layer upon layer. Historically, the term was referred to by other names, including freeform fabrication, solid freeform fabrication, layer manufacturing, additive layer manufacturing, additive techniques, additive processes, and additive manufacturing. However, today, additive manufacturing is the only accepted term for the process described above.

Additive manufacturing processes utilize machines and systems that manipulate materials, combining them layer upon layer to form a physical object from 3D CAD data. Naturally, this means the process creates a product that did not exist previously or one that is much larger than what was initially present.

Manufacturers use AM to manufacture both production parts and prototypes. When manufacturers use additive manufacturing for the fabrication of end-use components, this process is called Direct Digital Manufacturing (DDM). Improvements in AM technology have led to rapid manufacturing, a category of AM that is fast, accurate and should not be confused with rapid prototyping. Rapid prototyping describes the process through which manufacturers rapidly fabricate representations of the part way before final production and commercialization.

It is worth pointing out that the AM fabrication method makes it possible to fabricate parts and prototypes that have different characteristics. This is because a manufacturer has the liberty to choose among various AM processing methods, each with its own requirements and fabrication technique. Moreover, manufacturers can tweak the process parameters – the operating parameters and system settings used during a single build cycle – to achieve a particular result.

For the best results, additive manufacturing requires manufacturers to have a manufacturing plan. The plan typically comprises process parameters, preparation operations, post-processing tasks, and applicable verification/inspection methods. 

General Additive Manufacturing Process

The additive manufacturing process involves eight steps:

1.     3D modeling and support 2D design
2.     Conversion of CAD data to the STL format or AMF format
3.     Transmission/transfer of converted file to AM machine
4.     AM machine setup
5.     Part fabrication
6.     Part removal from the AM machine and cleaning
7.     Post-processing, which improves geometrical, surface, and tribological properties (including friction and wear), as well as mechanical characteristics
8.     Application/use of fabricated product

History of Additive Manufacturing

It is hard to expressly point out the exact year when additive manufacturing was invented. For instance, researchers and builders had, as early as the 1950s and 1960s, already started experimenting with ways to join materials to form objects. Additionally, technologies – like computers, computer-aided design (CAD), computer-aided manufacturing (CAM), computer-numerical computing (CNC), lasers, and programmable logic controllers – that ultimately enabled the realization of additive manufacturing had already been developed or were in development. (At Scan2CAD, we have documented the evolution of CAD and the history of CAM.)

The annals of additive manufacturing nonetheless became more well documented beginning in the 1980s. In 1984, for example, innovators filed parallel patents in Japan, France, and the United States. These patents described a similar concept of creating a 3D object by selectively adding material layer upon layer. One of the patents filed in the United States by Charles Hull is generally regarded as the most consequential because it gave rise to the founding of 3D Systems Corporation. This company still manufactures and sells 3D printers and 3D printing materials.

In 1986, plenty more patents came along, filed by three different companies. These patents described processes such as laminated object manufacturing (LOM), solid ground curing (SGC), and selective laser sintering (SLS). In 1989, fused deposition modeling (FDM) and 3D printing were patented by Scott Crump and a group at MIT, respectively. The former led to the formation of Stratasys Company, while the latter was out-licensed to various companies. What the group at MIT invented is now called binder jetting (BJT). Later, in 1994, inkjet technology, which was used to deposit droplets of material directly onto a base platform (substrate), was developed.

Materials Science: The Heart of Additive Manufacturing

Early additive manufacturing machines and systems made use of materials like paper laminates, photocurable resins, waxes, powders, plastics, and composites. Generally, these were materials that were already available then and had been developed with other processes in mind. However, additive manufacturing had – and still has – pretty unique characteristics and requirements. This meant that these materials were far from ideal for AM. 

For instance, when materials such as photocurable resins were used to create products, the products would be brittle and warped easily. Powders that were used in Laser-Based Powder Bed Fusion (LB-PBF) would quickly degrade within the material. This resulted in products that were weaker than expected. Fortunately, these shortcomings have not persisted. 

As professionals understood what additive manufacturing entails, they developed materials that suit the various AM processes. Today, there are numerous materials that perfectly match the operating requirements of different processes. These materials include metals, glass, paper, ceramics, composites, bio-inks, graphene-embedded plastics, food, concrete, yarn, etc. The development of these materials has enabled professionals to produce stronger, longer-lasting, more accurate, and well-built parts and prototypes.

Categories of Additive Manufacturing Feedstock

Materials added to additive manufacturing machines before part fabrication commences are known as feedstock. The feedstock can be grouped into three categories:

1.     Liquid-Based Materials

Liquid-based materials that are used in additive manufacturing include liquid polymers like Photopolymers and waxes; liquid metals like mercury and melted tin, aluminum, copper, bismuth, etc.; polymeric liquids; and liquid ceramic composite material.

2.     Solid-Based Materials

The following solid-based materials can be used in AM machines: 

• Solid metal: Wire metal (stainless steels, nickel and copper-nickel alloys, titanium and titanium alloys, cobalt alloys, alloy steels, aluminum alloys, niobium, molybdenum, tungsten, tantalum, zircalloy, and 4340 steel), sheet metal, and strip metal (nickel-based strip metal, mild steel, and stainless steel, copper, titanium, and aluminum)
• Solid ceramic: ceramic tape (sheets or laminates of ceramic powders joined together by polymer binders)
• Solid polymers: thermoplastic polyurethane (TPU) filaments, biopolymers, acrylonitrile butadiene styrene (ABS), polycarbonate (PC), PC-ABS, polylactic acid (PLA), Nylon 6 and 12, polyphenylsulfone (PPSF), polyetherimide (PEI), and polyetherketoneketone (PEKK)
• Solid composites: including metal-metal, metal-ceramic, ceramic-polymer, and ceramic-ceramic material, which are used to create such feedstock as composite laminate, composite polymer filament, particle-reinforced polymer filament, nanomaterial-reinforced polymer filament, fiber-reinforced polymer filament, and solid-based composite wires

3.     Powder-Based Materials

Powder-based materials comprise polymer, metal, ceramic, and composite powders. Polymer powders include polyamide, polystyrene, polypropylene, polyaryletherketone (PAEK), thermoplastic polyurethane (TPU), and thermoplastic elastomer (TPE). These powder-based materials can be used as feedstock for powder-based AM processes like BJT, MJT, PBF, and DED.

Additive Manufacturing Processes

There are seven additive manufacturing processes whose selection depends on such factors as cost, accuracy, material properties, and speed:

1. Material Extrusion (MEX)

Illustration of the Material Extrusion Process (source)

Typically, in the material extrusion (MEX) process, the feedstock is heated and melted just before or as the machine forces it through a nozzle. The nozzle follows a specific pattern and can control the flow of material. Once it completes a layer, the machine either moves upwards or moves the platform holding the part downwards. This enables it to produce the next layers. MEX machines come in inexpensive packages for hobbyists and personal use, as well as expensive setups for industrial use. 

While temperature is the most common method for controlling the state of the feedstock, alternative approaches are also used. This approach entails using a chemical reaction to trigger solidification. This means the material starts out as a paste. A curing agent, residual solvent, drying, or reaction with air causes the paste to cure or dry out.

Common MEX materials include solid polymers like ABS (acrylonitrile butadiene styrene), ULTEM 9085, polyphenylsulfone (PPSF), and polycarbonate (PC), as well as fiber-reinforced filaments like carbon fiber, fiberglass, and Kevlar filaments.

2. Vat Photopolymerization (VPP)

Illustration of the Vat Photopolymerization Process (source)

Vat photopolymerization (VPP), which includes the prominent stereolithography process, is a type of photopolymerization. Photopolymerization uses liquid polymers, or photopolymers, that solidify in response to radiation sources such as UV, gamma rays, electron beams, and sometimes visible light. 

In VPP, the photopolymer is placed inside a container called a vat. The material is then exposed to repeated patterns of radiation that correspond to the cross-sections of the product being fabricated. By emitting radiation in repeated patterns of known shape, VPP facilitates the layered solidification of the photopolymer. In addition to photopolymers, resins called epoxides are also used as materials in both stereolithography and VPP. Another class of feedstock, liquid ceramic materials that are a mixture of toughening agents, liquid resin, and powder, can also be used.

3. Powder Bed Fusion (PBF)

Illustration of the Selective Laser Sintering Process (source)

Powder Bed Fusion, or PBF, is one of the most versatile additive manufacturing processes. Not only is it well suited for metals (metal powders) and polymers, but it can also use composites and ceramics as feedstock. 

Generally, PBF uses one or more heat sources, such as lasers (the most common) or electron beams, to fuse powder particles. The entire process occurs in an enclosed chamber filled with nitrogen gas, which helps minimize degradation and oxidation of the powdered material. The chamber is fitted with various sources of heat that elevate the temperature around the part, increase the temperature of the build platform, and preheat the powder to just below its melting point. The elevated temperatures prevent the part from warping and minimize the laser power requirements. 

Once the preheated powder is laid on the heated build platform, it forms an appropriate powder layer. Next, a laser beam is directed onto the platform. The beam is moved such that it follows a pattern that forms a slice of the part’s desired cross-section. The surrounding unfused powder remains loose. 

The loose powder subsequently supports the layers that are laid above it. Once this layer is complete, the build platform is lowered by one layer, and a new powder platform is laid. This time, the fused and unfused powder become the primary supports for the new layer. The laser beam is again focused. This process is repeated until the part is fabricated. Then, the part is removed from the platform, and the loose powder is cleaned off. Finally, post-processing activities follow.

Under PBF, we have processes like: 

• Selective Laser Sintering (SLS), the first commercialized PBF process
• Polymer laser sintering (pLS)
• Metal laser sintering (mLS)
• Laser-Based Powder Bed Fusion (LB-PBF)

4. Material Jetting (MJT)

In Material Jetting (MJT), a printing head dispenses part material following a predefined path that defines the cross-section of the part. Motion controllers, which are part of the MJT machine, control the movement of the head along the path. This ensures the accurate deposition of materials such as polymers, ceramics, metals (tin, bismuth, copper, aluminum, mercury, etc.), and waxes.

The process uses deposition methods like inkjet deposition, multi-jet modeling, cold spray additive manufacturing (CSAM), and metal droplet printing, just to mention a few. Nonetheless, companies are continuously innovating, meaning they may develop additional methods in the future.

5. Binder Jetting (BJT)

Illustration of Binder Jetting Process (source)

Binder Jetting (BJT) was initially called 3D printing and was developed by a group at MIT. In BJT, a machine uses a print head containing many injection nozzles to print binder droplets onto a platform filled with powder to form a part. Once a layer is formed, the platform lowers, and a new layer of powder is spread across its surface area. This machine then dispenses the binder onto the platform. This process is repeated until the product is built.

Unlike other additive manufacturing processes, Binder Jetting is only concerned with printing a small fraction of the part’s material. The rest of the material is spread on the powder bed using non-BJT methods.

The binder materials used in BJT include calcium sulfate hemihydrate, poly-methyl methacrylate, and colloidal silica binders. The binder jetting process can be used to print binders into metal and ceramic powder beds.

6. Sheet Lamination (SHL)

In Sheet Lamination (SHL), sheet material is cut, stacked to form layers, and bonded to form a part. It is worth pointing out that the sheet material, which can include metal, paper, polymer, and ceramic sheets, can be stacked and then cut or cut and then stacked. In addition, the process can employ a variety of bonding methods that bind the various layers of sheets. These include:

• Adhesive bonding or gluing (the most popular SHL bonding technique)
• Ultrasonic welding
• Clamping
• Thermal bonding

While SHL was one of the earliest commercialized additive manufacturing techniques, its limited success is attributed to material waste, as unused material cannot be reused. This is perhaps because the material not used in the part cannot be reused, leading to wastage.

7. Direct Energy Deposition (DED)

Illustration of the Directed Energy Deposition Process (source)

In Direct Energy Deposition (DED), the material delivered in the form of a wire or powder is melted as it is being deposited, layer upon layer. Unlike other additive manufacturing techniques, which use a number of material types, DED is only applied to metals. The most common type of DED machine uses lasers as the source of heat to melt the metals. They use a deposition head to deposit material onto the substrate, which can be either a flat platform for building new parts or an existing part for adding additional layers. 

The deposition head typically combines powder nozzles, sensors, inert gas tubing, and laser optics. The machine’s controller actuates the movement of the deposition head, substrate, or the combined motion of the head and substrate. This relative differential motion controls the deposition of material. 

Industrial Applications Redefining Production

The early evolution of AM and the development of AM techniques rest on the shoulders of the medical, aerospace, and automotive industries, which were the early adopters of the technology. These industries’ respective needs led to improvements in additive manufacturing techniques, culminating in what we know and use today. As a result of these efforts, additive manufacturing is applicable in many major industries. We have discussed some of them below.

From a general industry-agnostic perspective, additive manufacturing has redefined production, enabling manufacturing companies in multiple industries to:

• Develop tooling solutions (rapid tooling): AM is ideal for low-volume production of tools
• Produce prototypes (rapid prototyping)
• Create scale models for functional testing applications like flow testing

Additive Manufacturing in the Medical Industry

AM enables the creation of customized solutions such as prosthetics and implants, given clinicians can use patient-specific data stored in scans to create 3D CAD data. Models of complex body parts act as surgical aids, helping surgeons to better visualize the organs and parts and subsequently perform complex surgical procedures. Other applications include organic printing and tissue engineering

Additive Manufacturing in the Construction Industry

For more than a decade now, professionals in the construction industry have used AM techniques to make architectural models. Besides this common application, research on 3D printing methods that can be applied in the construction industry has been on high gear, especially in recent years. As a result of these efforts, gantry systems and large robotic arm systems have been created to fabricate parts using polymers, metals, and aggregate-based materials.

Additive Manufacturing in the Food Industry

The food industry has not shied away from using additive manufacturing. Here, Material Extrusion is the most common additive manufacturing technique. It is used to dispense puree, dough, and chocolate onto a heated platform, where the material solidifies. Other techniques like Binder Jetting and Selective Laser Sintering are also used in the additive manufacture of food.

Additive Manufacturing in the Aerospace Industry

In an industry like aerospace that requires parts that have complex engineered geometries yet have the least possible weight, additive manufacturing has proven to be the go-to fabrication method. AM enabled aerospace companies to build complex parts using the least number of processing steps. Moreover, it supports topology optimization, a mathematical technique that enables manufacturers to place material only where it is needed to support loads. Put simply, additive manufacturing in the aerospace industry produces highly optimized components that are incredibly lighter.

At Boeing, AM has enabled the company to use less materials, produce less waste, and promote the fuel efficiency of its aircraft. AM also helped the company reduce lead time, which has led to a 25%-50% reduction in manufacturing costs. The company has used AM in production for over 30 years. By 2022, it had created 70,000 products using additive manufacturing techniques.

Additive Manufacturing in the Automotive Industry

Automotive companies were the first to deploy many of the additive manufacturing applications that are used today. However, the industry, known for the mass production of cars and parts, does not use AM to produce large volumes of parts. Doing this would obviously take an unnecessarily long time. So, automotive companies have largely restricted additive manufacturing to the fabrication of prototypes as well as the development of tooling, fixtures, and jigs. 

Niche automotive companies like Formula 1 racing teams also use additive manufacturing to fabricate parts for their cars. These teams also conduct wind tunnel testing using scale models fabricated through additive manufacturing.

The Unique Identity of Additive Manufacturing

Additive manufacturing is just but one type of fabrication technique. In all, there are four manufacturing/fabrication processes:

1. Additive manufacturing: As detailed in this article, additive manufacturing processes join material, layer-by-layer, to form a product whose size is much larger than the feedstock.
2. Subtractive manufacturing: In subtractive processes, the final part is smaller in size than the workpiece from which it is fabricated.
3. Formative manufacturing: Formative processes use restricting formworks or mechanical forces to form the material into a part with a desired shape.
4. Hybrid manufacturing: Hybrid manufacturing processes combine additive and subtractive fabrication methods.

Each of these fabrication processes has distinct properties defining its unique identity. Yet, the distinction between additive manufacturing and 3D printing may not be obvious.

Additive Manufacturing vs. 3D Printing

Additive manufacturing is a broad term covering all processes that build products layer upon layer from 3D CAD data. On the other hand, within the manufacturing industry, 3D printing generally describes the process of fabricating objects by using a print head, nozzle, or any other printer technology to deposit material. Thus, 3DP mostly relates to processes like Binder Jetting and Material Jetting. Usually, this term is associated with machines used for personal or non-industrial purposes. The table below summarizes the differences between additive manufacturing and 3D printing.

Based on these differences, it is easy to understand why discussing additive manufacturing goes beyond the limited scope of 3D printing.

Additive Manufacturing and the Digital Workflow

The Industrial Revolution 4.0 or Industry 4.0 has introduced smart manufacturing, bringing digitalization technologies into the manufacturing space and shop floors. The result has been an increase in productivity, better energy optimization, and parts and products that satisfy customer needs. The digitalization technologies include the digital thread, digital twins, generative design and artificial intelligence, the industrial Internet of Things (IIoT), and more. 

Today, it is not uncommon for manufacturers and organizations to integrate additive manufacturing with these digitalization technologies. For instance, the United States Department of Defense once had a spare parts problem for some of its old vehicles and aircraft. Whenever they needed a new replacement part, they would discover that the original equipment manufacturer, part supplier, or tooling they required was no longer in business. They also found that to fabricate the parts, they needed the parts’ drawings, which they could not access. To solve the problem, General Electric made digital twins of the aircraft and vehicles. They then used this digital twin to print perfectly fitting parts using additive manufacturing.

What’s more, manufacturers have built digital and IIoT infrastructures that connect various factions of production floors and assembly lines. This infrastructure includes sensors that collect data, facilitating analytics. This data then flows across connections facilitated by a communication framework called the digital thread. In the additive manufacturing domain, the digital thread can help manufacturers harness the full potential of AM technology. For instance, by facilitating data transfer and analytics, the digital thread enables companies to anticipate machine failures and perform predictive maintenance. 

Moreover, they can couple the digital twin of the AM machines with the digital thread. This approach would allow them to fabricate replacement parts from the digital replica that fit into the AM machines.

Benefits of Additive Manufacturing

Additive manufacturing offers numerous benefits, including:

1. It enables manufacturers to rapidly create physical models of any complexity and subsequently conduct functional tests and experiments
2. Additive manufacturing offers the ability to increase part complexity without impacting lead time and cost
3. It minimizes the design, manufacturing, and verification of tooling, lowering fixed costs 
4. Additive manufacturing technologies eliminate costs associated with labor since AM machines do not require part-specific setting up or programming, casting, or machining labor; also, a single person can operate the machines
5. The technology reduces material waste and waste disposal costs
6. It eliminates material transportation and inventory cost
7. AM supports customization because of fewer constraints.
8. Additive manufacturing enables companies to change in real time the production capacity to meet market demand 
9. The fabrication technique simplifies the supply chain
10. The Binder Jetting AM technique enables the economical fabrication of standard engineering materials as it does not require high energy, is fast, and relatively inexpensive

Overcoming Challenges and Navigating Barriers

There are certain challenges you are likely to encounter when you use additive manufacturing techniques, the benefits discussed above notwithstanding. These challenges include:

1. Limited Production Volume

Additive manufacturing techniques and machines are not suited for high-volume production. For this reason, automotive companies do not use AM machines to manufacture parts that need to be mass-produced. Instead, they only use the techniques to fabricate prototypes.  

2. Complex AM Techniques

AM techniques like MJT for 3D fabrication can be extremely complex. This is because the heads and nozzles in MJT systems dispense the feedstock in the form of liquid material droplets. This deposition must be controlled. What’s more, once deposited, the solidification of the droplets must be controlled. The need for controls at the different stages of fabrication adds layers of complications to the process. While this is just one example, each AM technique has its own level of complication. To overcome this challenge, it is important to undergo training.

3. Material deficiencies

There are three classes of AM machines: liquid-based systems, powder-based systems, and solid-based systems. These categories point to the specificity of the machines in that they can only use certain materials as feedstock. You cannot feed liquid feedstock into a powder-based or solid-based system. The same applies to powder and solid materials. Thus, if you are working with different classes of material, you will have to purchase different AM machines, adding production costs.

4. Industry-Specific Deficiencies

Professionals in the medical field have reported deficiencies in existing AM technologies. These deficiencies relate to how the technologies and techniques are used to build medical models. They arise from the fact that AM machines were not originally developed with the medical field in mind, even though players in the industry were among the early adopters. Rather, they were intended for widespread adoption. Thus, device manufacturers have mostly worked to develop improvements that solve problems for manufacturers rather than the industry-specific problems that medical professionals raise.

5. High Technical Requirements

AM machines – especially larger, more complex machines – require a high degree of technical expertise to fabricate quality parts and objects. But this is not an insurmountable challenge. Companies can continuously train their technicians to handle complex machines.

Conclusion

Additive manufacturing is broader and has a larger scope than 3D printing. While 3DP describes processes that use printer technology, AM covers all techniques that create products from 3D CAD data through layer-by-layer material deposition. For this reason, additive manufacturing includes techniques like vat photopolymerization, powder bed fusion, material extrusion, material jetting, binder jetting, directed energy deposition, and sheet lamination. 

These techniques are applied in the medical, aerospace, automotive, construction, and food industries. And thanks to the technological developments brought by Industry 4.0, they can be used with other technologies like digital twins, the industrial Internet of Things, the digital thread, artificial intelligence, and more. As we have touched on above, AM processes offer numerous advantages when used in isolation or with other technologies. Nonetheless, you are likely to encounter some challenges when you deploy additive manufacturing in your organization, but they are easily surmountable

Note: For more information about additive manufacturing, we recommend the book Additive Manufacturing Technologies by Ian Gibson and colleagues, which we have referenced in the writing of this article.

MBE represents one of the technologies that manufacturing companies adopt and implement to digitize their operations. In fact, many manufacturers view MBE as an integral part of their digital transformation strategy, with a great many of them taking a keen interest in the concept when they come to the realization that traditional systems are holding them back. The MBE strategy prepares companies to use innovative technologies like additive manufacturing, artificial intelligence, machine learning, digital twins, digital threads, 5G, the Internet of Things (IoT), cloud computing and cloud-based CAD, robotics, automation, and edge computing, just to mention a few. Additionally, they develop and manufacture products with greater speed and responsiveness. 

To understand where MBE falls in the CAD landscape, how it is transforming the design and manufacturing spaces, and the benefits it presents to companies that adopt it, it is crucial to take a deep dive. The purpose of this article is to explore the concept of model-based enterprise (MBE) in depth, along with two related concepts: model-based definition (MBD) and model-based systems engineering (MBSE). 

Essence of Model-Based Enterprise

What is a Model-Based Enterprise?

A model-based enterprise (MBE) is a manufacturing organization that manages and organizes its business processes through the creation and use of digital 3D CAD models throughout the product lifecycle, from development and manufacturing to quality control, maintenance, repair, overhaul, and more. The 3D CAD models define, represent, and manage various business aspects of the enterprise, including products, processes, and systems. Evidently, the 3D models form the foundation on which an MBE is built. 

The 3D models must contain all the data needed to clearly define and effectively communicate the characteristics of a product, process, or system. It is worth mentioning early on that we refer to the approach to creating such a 3D model as the model-based definition (MBD). Thus, a model-based definition is a crucial component of the MBE approach. 

Typically, an MBE employs MBD to define product specifications and requirements for all engineering activities across the product lifecycle, supplanting the prior era of reliance on paper-based or digital documents as data sources. CAD professionals create this product data, captured in the MBD/3D model, only once, with other professionals then reusing it for all downstream activities, including manufacturing and inspection. This points to the need for a mechanism of transferring data across the lifecycle, which is where the digital thread comes in. 

A digital thread is a communication framework that enables data flows between design, engineering, manufacturing, supply chains, and business processes. Thus, major players view the creation of a digital thread as the best approach to realizing the vision of a model-based enterprise. In fact, it is the digital thread that enables mature MBEs to work with external and internal stakeholders, like suppliers. And as you will see later, forming competencies that support the collaboration with external stakeholders is the last step in realizing a model-based enterprise. 

What Necessitated the Model-Based Enterprise?

Both the MBD and MBE address limitations that were prevalent in traditional practices. In the past, engineers and designers derived 2D drawings from the 3D models they were designing. They then used the 2D drawings to deliver product manufacturing information needed in the downstream stages. At these subsequent stages, they would again use the 2D drawings to recreate 3D models for other stage-specific product lifecycle work.

Even from the sound of it, this approach was very inefficient, costly, slow, and presented risks associated with the likelihood of making errors. Moreover, it condemned manufacturing companies to a largely document-centric operation. There was a clear need to change these traditional practices, especially in the face of competition. 

Companies needed to be fast, faster than their competitors. They also needed to use efficient processes that were cost-effective and anchored in accuracy and precision. And as the wave of digital transformation swept through the manufacturing industry, companies began implementing MBE and MBD strategies to digitize their operations. 

Adoption of MBE Strategy

According to a Deloitte study, today, over 85% of enterprises across various industries are initiating efforts to enhance and support their MBE capabilities. However, a separate study that surveyed 250 different manufacturing organizations observed that company size is a huge determinant of whether such organizations adopt an MBE strategy. 

The study noted that 39% of companies whose annual sales were greater than $1 billion already had a strategy to become an MBE, while 23% were considering an MBE strategy. By contrast, only 9% of companies with less than $100 million in annual sales had a strategy to become an MBE, with 55% having no strategy at all. The reasons for manufacturers’ intentions to become model-based enterprises lie in the value the concept brings. Which brings us to the benefits of MBEs: why should companies adopt the MBE strategy?

Benefits of MBE

Companies gain a wide array of benefits by adopting the MBE strategy. For instance, they realize transformations in design and manufacturing with MBE. The strategy also improves other operations within the organization. Here are the benefits of MBE vis-à-vis organizations’ operations:

1. Improved Communication and Collaboration

MBD enables an integrated and collaborative environment based on the 3D product definition. This, in turn, facilitates the rapid, seamless, and cost-effective deployment of a product.

2. Improved Efficiency

3D models enable faster design iterations, as designers can get feedback and input from their colleagues in other departments more easily and quickly. By working together, professionals can identify and resolve errors quite early on. As a result, they avoid situations where the errors propagate downstream, disrupting manufacturing and causing wastage.

3. Lower Cost

Scholars estimate that by implementing the MBE strategy, companies reduce the cost of product innovation, development, production, and support by 50%. For instance, it emphasizes the use of 3D CAD models that support simulations and analysis, eliminating or lessening the reliance on physical prototypes. This lowers the cost companies would have otherwise spent on materials and labor if they were to create multiple physical prototypes.

4. Reduced Time to Market

Studies have shown that adopting an MBE strategy reduces the time to market by 45%. In addition, another study found that using MBD can shorten by 75% the process of designing, manufacturing, and inspecting products. For instance, the use of MBDs, which support virtual prototyping, saves time, as companies do not have to create multiple physical prototypes.

5. Better Understanding and Interpretation of Products

In an MBE, engineers, team members, and other stakeholders gain early access to critical model-based data, enabling them to understand the products better. Better comprehension is also pegged on using data rendered in three dimensions rather than two-dimensional drawings and data. Moreover, the annotated 3D models provide stakeholders with contextual insights and measurements that boost understanding and interpretation.

6. Increased Quality

Traditional methods that required the use of 2D drawings were not infallible. They were prone to misinterpretation, which could affect the quality of production, force reworks, and cause delays. MBDs, however, solve these shortcomings. By using the validated and authenticated MBD as a central, authoritative source of information, MBEs eliminate conflicting, misrepresented, inaccurate, and missing information. This reduces errors and enhances clarity, resulting in increased quality.

7. Better Traceability

One of the hallmarks of a trusted MBD is its traceability. It makes it easy for the stakeholders within the organization to find the authoritative originator of data and the 3D model. Also, since MBEs embrace digital twins, digital threads, and other technologies, tracking products, processes, plants, and even people is easier. In this regard, the MBE and MBD strategies facilitate better traceability throughout the product lifecycle.

Full traceability allows manufacturers to implement changes far more easily than before. This way, they become evermore agile.

MBE’s Operational Framework in CAD

Transitioning from a traditional manufacturing enterprise to a model-based enterprise is a complex process for companies, regardless of their size. This complexity arises because developing and adopting an MBE strategy involves more than merely creating a 3D model with preferred CAD software. If this were the case, most companies in the manufacturing industry would already be MBEs. After all, they have been using 3D models for years. But it is definitely more than that. Complicating matters further, not all 3D CAD modeling software is suitable, as some lack the model-based definition capabilities crucial for establishing model-based enterprises.

Developing an MBE, therefore, necessitates the integration of product, process, system, service, and logistic models throughout the enterprise. To achieve this, a phased approach involving seven stages, as outlined in the MBE Maturity Index, developed by the US National Security Enterprise (NSE), is recommended. A manufacturing company uses this index to assess itself as a model-based enterprise. Put more broadly, the index is used as a rubric to evaluate the extent to which organizations have implemented the model-based enterprise strategy. While it is mainly an assessment rubric, it provides the steps companies can use to realize a model-based enterprise. It is a guiding compass.

Model-Based Enterprise Maturity Index Levels

Upon examining the seven stages, one will notice their foundation in both 2D drawings and 3D models. This emphasizes the importance of CAD tools. The table below summarizes the seven stages/phases of the NSE MBE maturity index:

In each of these levels, manufacturing companies have to undertake various activities, including design, product data management, manufacturing, quality control, and enterprise-enabling activities. The figure below provides a more comprehensive summary of these points:

Comprehensive Model-Based Enterprise Index (source)

The MBE maturity index does provide a step-by-step template that manufacturing companies can use to transition to model-based enterprises. However, for optimal outcomes, the index emphasizes the importance of companies placing significant trust in their models and associated data. It is this trust that will enable them to achieve various concepts, namely digital engineering, digital enterprise, automation, and, more crucially, the model-based enterprise.

Trust Framework for Model-Based Enterprises

Against this backdrop, the NSE developed the trust framework, which applies to models, datasets, artifacts, and associated components.

NSE-Developed MBE Trust Framework (source)

You will notice that the trust framework uses the terms defined below:

• Signed: The originator of a model, e.g., a designer or engineer, guarantees the authenticity of the model, using agreed-upon criteria that also confirm the authenticity of the originator, which cannot be repudiated
• Traceable: A traceable model is one whose authoritative source can be found
• Authenticated: the model is proven genuine as created or issued by the originator; an authenticated model is traceable and signed by the originator.
• Authorized: An authorized model is approved by a party in authority for use in a section or entire lifecycle
• Certified: A certified model or dataset is confirmed to conform to protocols
• Validated: A validated model or dataset is guaranteed to satisfy the intent
• Verified: A verified model or dataset is guaranteed to satisfy requirements
• Versioned: All successive revisions have been appropriately identified in their correct sequence and stored
• Trusted: when a model has been certified, authorized, and authenticated, it is regarded with confidence and is now said to be trusted

Other terms that increase parties’ confidence in a model include:

• Required: Mandated by an authority
• Specified: Defined to minimally acceptable detail
• Record: Permanently and irrevocably documented for future reference

The greatest level of trust is accorded to an artifact or 3D CAD model that is signed, traceable, authenticated, authorized, versioned, validated, verified, required, and specified.

Distinctions Among MBD, MBE, and MBSE

Manufacturing companies may adopt three model-based approaches and practices on their path to digital transformation. These model-based approaches are somewhat related. To understand the relationships, let’s look at what each entails.

The model-based definition, or MBD, is restricted to product manufacturing. It relates to the use of 3D CAD models to describe parts and products. The 3D CAD models capture necessary product information, including design intent, manufacturing notes, and component specifications such as Product Manufacturing Information (PMI). The PMI includes annotations, geometric dimensioning and tolerancing (GD&T) data and symbols, materials and bills of materials, surface finishes, revisions and version history, parts list, and quality requirements. 

These 3D CAD models, therefore, serve as authoritative and comprehensive sources of information for the product and the entire product lifecycle. As a result, MBD reduces errors, facilitates collaboration, and streamlines the design-to-manufacturing pipeline.

Model-based Systems Engineering, or MBSE, is an approach that uses CAD tools to design, document, and simulate complex systems as well as define their behavior, requirements, interactions, and functions. Under this practice, a digital model represents the entire system. This enables better analysis, communication, and understanding of the system.

Finally, model-based enterprise or MBE is a concept that brings together both MBD and MBSE. It is concerned with the entire product lifecycle. MBE utilizes the 3D models not only for design and manufacturing, as is the case with MBD, but also for maintenance, service and support, quality control, sales, procurement, and beyond. Moreover, an MBE integrates product, process, system, service, and logistic models across the entire enterprise. 

MBE and Modern CAD Profession

CAD Professionals in Traditional Dispensation

The MBD and MBE concepts have transformed the workflows of CAD professionals. Previously, they created 2D engineering drawings to communicate the quality requirements, engineering configurations, design intent, engineering and manufacturing notes, materials, and more. The professionals often used multiple separate documents to capture this information. This largely inefficient practice had a few disadvantages. 

First, it was prone to misinterpretation, given some vital information was in discrete documents and could be overlooked. This resulted in miscommunication that could easily lead to errors, production delays, plenty of wasted material, and rework. Second, it took up a lot of time, which naturally increased the cost of operations.

CAD Professionals in MBE

For its part, MBE has changed the narrative, with MBD conveniently taking the place of 2D drawings. Moreover, embedded within the 3D CAD models is information such as technical information, component specifications such as Product Manufacturing Information (PMI), annotations, geometric dimensioning and tolerancing (GD&T) data and symbols, materials and bill of materials, dimensions, various technical properties and quality requirements, the design intent, and any manufacturing notes. 

What this means is that rather than the information being in separate documents, it exists within the same file and is embedded within the 3D CAD model. The benefits of this approach on both companies and the CAD profession are clear. For instance, the MBD approach saves MBEs time, improves quality, and offers other benefits discussed earlier. What’s more, it enables professionals to work on more complex parts, assemblies, and products than before.

Modern CAD professionals have also had to learn how to use MBD software, whose unique capabilities are unavailable in non-MBD software. Also, they have to learn and know about the information they need to embed in the 3D models and how to embed it. 

Today, the modern CAD professional has to do more upfront work than traditionally. This is because their input is impactful from the very beginning and is useful throughout the product’s lifecycle. Simply put, CAD professionals set the tone for the smoothness of downstream activities.

Overcoming the Implementation Challenges of MBE

The transition towards an MBE is not easy. It is punctuated by hurdles and challenges that companies must overcome to take advantage of the MBE and MBD strategies. We have discussed these challenges and ways to overcome them below.

1. High Capital Outlay

The implementation of the MBE strategy is not cheap. It requires companies to invest large sums of money in software, training, and human resources. Moreover, an MBE also relies on technologies like 5G sensors, IoT solutions, cloud computing, robotics, automation, edge computing, and more to support multiple activities. Companies need to have a budget to adopt some or all these technologies, which can run into the thousands of dollars. 

Fortunately, companies need not dive all the way into the deep end; instead, they can progressively implement the MBE strategy, which can be a cheaper approach. In fact, they can follow the steps outlined in the NSE maturity index.  

2. Gaps in MBD Datasets

It is not always easy for professionals to establish beforehand the datasets and elements they should include in the product definition. This is partly because existing MBD standards and tools do not capture all the details. It is equally difficult for them to decide which information contained in a 2D drawing they should move to the 3D model. This issue is compounded by the fact that there are multiple workflows in a product lifecycle, each with its own set of information and elements.

To overcome this challenge, standards bodies have to develop comprehensive MBD and CAD standards. However, this solution may take some time to become a reality. In the meantime, companies must develop in-house practices that address this shortcoming.

3. Interoperability Issues

There are plenty of applications that offer different capabilities that are integral across various domains of the product lifecycle. In some cases, these applications are not always interoperable. The interoperability issues stem from differences in data types, languages, processes, systems, and more. 

Similarly, data is not always interpretable by all applications in an organization. This is particularly the case if different teams and departments involved in the product lifecycle use different types of applications. The lack of interoperability can lead to data loss when transferring data across different formats. It can also prevent long-term archival and retrieval. 

To overcome this challenge, companies can adopt software created by one company and incorporate modules and add-ons created specifically for that software.

4. Technical Limitations

As mentioned earlier, some 3D CAD software applications lack MBD capabilities. As such, these tools are incapable of fully defining product data. Thus, companies should be careful when choosing CAD software. 

An ideal tool should have the right tools and capabilities to incorporate data and elements from all the stages of the product lifecycle. They should also allow teams to include the semantics of this data and embed PMI. Moreover, the software should have capabilities for manufacturing and inspection, including computer numerical control (CNC), coordinate-measuring machining (CMM), and intelligent tooling.

5. Authenticity and Trustworthiness

Errors can arise at different stages in the manufacturing company’s operations. For instance, translation errors can lead to data loss or inaccurate data. Additionally, the model development technique or CAD software can be a source of errors. Unfortunately, these errors negatively impact the quality of the model, which puts into question its authenticity and trustworthiness. 

Yet, it is paramount that product data and 3D models have the highest degree of trust attached to them, which, in turn, guarantees their reliability. After all, they aim to support downstream activities throughout the entire enterprise. 

To boost trustworthiness, companies must ensure their model data is up to date, correct, and of high quality. They must also ensure the model and associated data are signed, traceable, authenticated, authorized, versioned, validated, verified, required, and specified. Only after a model has achieved the desired level of trust can it be certified as a master and used to support enterprise-wide activities.

6. Disruption

Adopting the MBE strategy requires companies to change their traditions and working patterns. For instance, they must change from using conventional drawings to MBD. They must also change their procedures and other practices their employees have grown used to. Such an enterprise-wide change is not easy. In fact, it can very easily be impacted by resistance from factions within the company and even external stakeholders. To overcome this challenge, companies can invest in training and consultations. Plus, they can implement the MBE strategy in stages, as the MBE Maturity Index prescribes.

Conclusion

The CAD landscape has transformed immensely, with companies and professionals in the manufacturing space adopting more efficient approaches to replace traditional practices. One of the approaches they have embraced is model-based enterprise (MBE). MBE brings together approaches like model-based definition (MBD) and model-based systems engineering (MBSE), as well as other technologies. Under the MBE, manufacturing companies use 3D models within which product information such as Product Manufacturing Information (PMI), design intent, and manufacturing notes are embedded. Such information-enriched 3D models are now known as MBD. They act as single sources of truth and are used throughout the product lifecycle. 

The MBE concept offers numerous advantages, including improved quality and efficiency, better collaboration and traceability, less time to market, and enhanced understanding of products. However, certain challenges can impact its implementation. Fortunately, there are ways to overcome these challenges. This article has captured everything to a tee, comprehensively decoding model-based enterprise in the CAD and manufacturing landscapes.

Each of these approaches has its own advantages, disadvantages, and roles. And in this article, we will explore the digital thread, an alternative that connects multiple aspects of an organization’s operations. We will discuss what a digital thread is, its benefits, and its role in different industries/spaces. Additionally, we will map out the digital thread’s journey in a digital enterprise and how it ties together the various processes in an asset’s life cycle. Lastly, we will detail the challenges associated with implementing the digital thread. Let’s get started.

Understanding Digital Thread

Every process has a beginning and an end, naturally encompassing numerous steps and strategies along the way. Each step may generate data and require data generated in the preceding step or steps. In the context of a complex enterprise operation, ensuring that data reaches its intended recipient at the right time can be challenging. Fortunately, the digital thread has been advanced as a formidable solution to this problem. As a result, it plays a foundational role in enabling enterprises to adopt and implement digital transformation.

What is Digital Thread?

A digital thread is a communication framework that creates continuity across people, processes, and products by facilitating data flows both upstream and downstream, and also enables enterprises to maintain an integrated view or record of the entire lifecycle. The data flow occurs across interconnected informational nodes and data storage units. To paint a clearer picture, you can think of a digital thread as a chart that shows the data flows and the links connecting the nodes and repositories (data storage units). This chart not only captures these interconnections but also all the decisions made throughout the asset’s life cycle. 

Functioning as a clear map, the digital thread enables enterprises to integrate various chosen data sources across multiple operations. This way, it eases access to data that was previously siloed and challenging to access. As a result of this integration and bi-directional data flow, the digital threat propagates changes made to data in one CAD model, design, or simulation to all the other stages of the life cycle. 

Implementations of the Digital Thread

The most common implementation of the digital thread is a thread of a product or system that weaves through its lifecycle from conceptualization, design, engineering, and product lifecycle management (PLM) through manufacturing, customer use, and decommissioning. This thread records the sequence of discrete, traceable, and linked activities in a product’s or system’s life cycle. In this regard, this implementation of the digital thread enables enterprises to track the progression of the product and relay that information both upstream and downstream of where the product is in its lifecycle. 

By propagating the latest information across the lifecycle, the digital thread ensures all participants are up to date with the most current data. For example, it alerts stakeholders of key decisions or activities that may be behind schedule. In this regard, the digital thread helps them prepare for any eventuality, anticipate the next steps, or react to changes as they emerge. 

It is vital to mention that the other less common implementations of digital threads cover operational environments and processes.

History of Digital Thread

The term digital thread was coined during the development of the F-35 Lightning project. The project was a joint effort by Lockheed Martin and the United States Air Force. (For context, the project started in 1995, with the full-rate production phase beginning in 2010.) Some sources nonetheless state that the concept was originally developed in the mid-2000s.

Within the context of the project, the term generally referred to the continuous data link between the original 3D CAD model and the finished product. There was nonetheless a more comprehensive definition. The phrase described the way to use 3D CAD data directly in manufacturing, for computer numerical control (CNC) machining programming, composite programming systems (CPS), inspections, and tooling, as well as training and maintenance. This allowed for the finished product to be traced back to the original CAD model.

Since then, the meaning of ‘digital thread’ has evolved to its current definition. 

Digital Thread vs. Digital Twin

The concept of the digital thread is far newer than that of the digital twin. A digital twin is a computer-generated replica of a product, process, environment, or task. On the other hand, as we have introduced earlier, a digital thread is a record or chart that connects data, activities, and processes that are integral to creating a product or system. It’s important to highlight that prior to the adoption of digital threads, these activities, processes, and data existed in isolation.

While their definitions are expectedly different, digital twins and digital threads are tied. How so? A digital thread aids in creating, maintaining, and utilizing a digital twin. It achieves this feat by linking data and information collected from physical entities, via sensors and Internet of Things (IoT) technologies, as well as virtual systems such as CAD software. It subsequently uses it to update and enhance an asset’s digital twin. Moreover, the digital thread stores this data within the digital twin. This connectedness allows for seamless data flow across different stages of the product life cycle, from inception to disposal.

It is worth noting that individual digital threads or multiple linked digital threads can build a comprehensive digital twin over time. At the same time, digital threads influence the continuous real-time evolution of the digital twin model. It ensures the model reflects and stores the latest data.

Digital Thread vs. Digital Web

Industry experts, including professionals at Dassault Systèmes, suggest that a relatively newer concept known as the digital web is replacing the digital thread. They argue that in a digital thread, the data and processes are interconnected via a single link. Yet this is not an accurate representation of the reality today. Instead, the digital web accurately represents the interconnections in digital enterprises. 

As the name suggests, a digital web is a collection of multiple digital threads. A digital thread’s nodes are each connected by a single link. By contrast, the digital web’s nodes are connected by multiple links. 

Mapping the Digital Thread’s Journey in Digital Enterprises and CAD Projects

What is a Digital Enterprise?

A digital enterprise is an organization that has adopted and implemented digital transformation. Such an organization has fully integrated digital technologies and tools across all facets of its operations. It, therefore, goes without saying that a digital enterprise is one that has incorporated digital CAD models, visualization, simulation, and analysis tools, as well as the digital twin and digital thread concepts and approaches. 

It bears emphasizing that a digital thread provides a record of the activities, data, decisions, and processes that form part of the asset’s life cycle. And given that digital enterprises have to integrate multiple areas and processes, from design and customer relations to logistics, supply chain, and manufacturing, just to mention a few, it is easy to establish how such organizations use the digital thread concept. 

Against this backdrop, it is equally easy to map the digital thread’s journey as taken by digital enterprises. Similarly, given that most human creations start their lifecycle as CAD designs, it is also worth looking at where CAD, CAE, and CAM fall within this journey. 

Digital Thread in Digital Enterprises

Typically, the operations of industrial enterprises cover multiple areas that must be integrated for the smooth running of the companies. These areas include engineering, commercial, sourcing, supply chain, and services. Engineering covers design, modeling, simulation, and analysis. The commercial aspect covers all the activities a company performs, from inquiry to order of materials, while sourcing includes the activities conducted around ordering raw materials. The supply chain is concerned with activities around manufacturing, while the last area covers all services, from logistics to customer relationship management.

To gain an informed view of each of these areas, companies use enterprise platforms such as: PLM, Electronic Design Automation (EDA), Product Data Management (PDM), Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Manufacturing Operations Management (MOM), Manufacturing Execution Systems (MES), Totally Integrated Automation (TIA), Total Quality Management (TQM), Asset Performance Management (APM), Asset Lifecycle Management (ALM), Customer Relationship Management (CRM), Supplier Relationship Management (SRM), and more.

In an ideal situation, a digital thread has to connect all these platforms and, by extension, the activities they support. So, the digital thread begins its journey at the PLM stage and weaves through the other stages. 

Benefits of the Digital Thread

A digital thread offers numerous benefits, which, combined, increase business value. The benefits of implementing the digital thread include:

Digital Thread and CAD Collaboration

Today, many manufacturing companies have multiple manufacturing facilities and service centers detached from the head office. Despite their location in different regions of the world, these entities must work in congruence, with multidisciplinary teams collaborating on projects. The optimal situation calls for designers and engineers to receive prompt feedback on their designs. Additionally, the CAD designs and materials have to reach the factory floor on time. And the manufacturing teams must be capable of monitoring the machining and manufacturing operations. 

However, traditional approaches that were anchored in siloed operations have long struggled with orchestrating the various operations. The separated nature of processes that should ideally be interconnected has traditionally made collaboration difficult, dramatically impacting productivity. But this is no longer the case with the digital thread. 

The adoption of the digital thread in CAD design, as well as other processes in an asset’s life cycle, has dramatically boosted collaboration. It enables real-time synchronicity of data from different repositories or nodes/sources. This means when one person performs a process integral to the asset’s life cycle, the thread updates all downstream and upstream parties. The result is improved worker productivity and cooperation.  

Increased Market Agility

Companies that embrace the digital thread concept can more quickly design and build customized products. This benefit is linked to the fact that the thread, which links CRM systems with the CAD design and engineering systems, enables the free flow of data. As a result, designers and engineers receive customer feedback or requests much faster. Therefore, they can tweak their designs per their customers’ demands. 

Better Decision Making

A digital thread is an authoritative source of truth throughout the asset’s life cycle. Moreover, it facilitates continuous feedback between and among teams, enabling them to choose the best CAD designs, materials, and manufacturing processes that meet the program’s goals and constraints. This way, it helps the teams make better and more informed decisions in what improves performance and reduces cost.

Enhancing Quality in Design and Manufacturing

The digital thread enables organizations to identify and correct errors early in development. This capability stems from the seamless data flow and connection. Little wonder, then, that companies have implemented digital threads to streamline quality control and quality assurance processes. It is quite common for enterprises to use augmented reality (AR) technology to compare data collected from physical assets, such as prototypes or the initial manufacturing batches, with the digital twin’s parameters. If the properties of the physical asset and virtual model do not align, then that indicates issues that need correcting. 

For example, while manufacturing the F-35 Lightning II fighter, Lockheed Martin uses lasers alongside the digital twin to identify interference issues early on in the asset’s lifecycle.

The F35 Lightning II Fighter Jet

Boosting Manufacturing Efficiency

The digital thread has also made it possible for companies to perform cost-effective manufacturing and machining processes that may not have been possible before. It has also facilitated automation and reduced downtime. Still on the F-35 Lightning II project, the digital thread technology enabled Lockheed Martin to implement automated drilling, which improved quality, saved time, and, more broadly, enhanced the quality of the manufacturing process. 

Role of the Digital Thread

Digital Thread in Manufacturing and Packaging Industry

Manufacturing companies use digital threads to:

• Coordinate the activities of global teams
• Democratize and streamline processes and data
• Improve quality control and quality assurance
• Enrich their digital twins, which provide better end-to-end visibility of operations and enhance transparency 
• Realise the vision of a model-based enterprise (MBE)
• Some enterprises implement digital threads with technologies like AR to onboard new employees. This is because the digital threads digitalize traditional procedures.

Digital Thread in Aerospace and Defense 

The United Air Force developed the digital thread analytical framework to offer engineering analysis capabilities and support the military organization’s decision-making over the lifecycle of airplanes. This digital thread merges data, 3D modeling, and simulation to generate an authoritative digital twin for each of the processes of the vehicle. The use of the digital thread aims to ensure the timely and cost-effective acquisition of military systems.

Similarly, the design and development of the F-35 Lightning II took advantage of the digital thread technology to connect engineering and manufacturing nodes. As a result, the program expanded automation of the fighter jet’s manufacturing and assembly process. Other notable advantages of deploying the digital twin included drops in tool rework, better first-time part fit, and substantially fewer reconfigurations on the part of suppliers.

Digital Thread in Compliance and Standards

The certifications, compliance regulations, and standards are all about safety assurance and protection of the public. These spaces are, however, not immune to the influence of digital threads and could, in fact, greatly benefit from the concept. The reason for this is simple. Usually, regulatory bodies enforce a lot of requirements, which include mandatory processes and steps. This, therefore, means companies must fulfill the requirements before receiving a certification, standard, or regulatory approval for their products. 

These processes ordinarily involve multidisciplinary teams. However, these teams can sometimes be drawn from different companies, such as the contracting organizations and their preferred suppliers. These teams must collaborate internally amongst themselves as well as externally with the regulatory bodies and vice versa. The pathway to regulatory approval requires the documentation of all steps taken. Therefore, having a convenient tool that facilitates the flow of data through each step makes the process relatively seamless. And that is where the digital thread comes in. It provides a record of all the procedures a company performs.

Regulatory bodies can use the digital thread for aircraft certification and the approval of medical diagnostics tools, therapies, and vaccines.

The Backbone of Integrated Systems

As introduced earlier, a digital enterprise connects various enterprise platforms and applications, including PLM, EDA, PDM, ERP, MOM, MES, TIA, TQM, APM, ALM, CRM, ALM, SCM, SRM, and more. While the acronyms can be confusing, they all serve a vital enterprise function. And as digital transformation continues to have a firmer grip on operations across the entire enterprise, new models integrating two or more platforms across the entire digital thread (i.e., both downstream and upstream) are becoming more widely accepted and common. 

While technical issues often make it challenging to integrate these platforms, software publishers and vendors have developed and offered a number of working alternatives. For example, PLM, ERP, MES, and enterprise software vendors provide APIs and connectors that facilitate the integration of their solutions with third-party applications. 

Moreover, some software publishers have joined forces to create tailor-made solutions, i.e., integrated systems, that seamlessly bring together two otherwise separate platforms. At their core, these solutions are essentially end-to-end integration of systems and data. They are intended to provide insights into operations and promote traceability. It is worth pointing out that the process of building such solutions is known as building digital threads. And several companies have taken this second route. 

Examples of Integrated Systems

Siemens and SAP entered a strategic alliance to build an interface that connected their PLM and ERP platforms. This move enhanced data continuity, an integral piece when building a digital thread. Similarly, Siemens and IBM collaborated to build a holistic digital thread that covered product development, production, operations, and asset maintenance. 

The Siemens-IBM partnership combined IBM’s Engineering Lifecycle Management, Engineering Systems Design Rhapsody, and Maximo with Siemens’ Teamcenter, Capital, and other solutions under the Xcelerator Portfolio. Teamcenter is a platform that integrates product design, innovation, and CAD and feeds that data into downstream systems.

It is clear these companies’ strategic alliances aim at using integrated systems to build digital threads across discrete enterprise platforms. These integrated systems help accelerate the adoption of the digital thread concept by collating information from multiple connected business platforms. This way, they break siloed operations that impede effective product innovation. 

In the same vein, the digital thread provides a basis for creating a functional integrated system. It defines which platforms should be connected to create efficient upstream and downstream data flows. Thus, we can accurately say the digital threads, which weave across the various enterprise platforms and operations, is the backbone of integrated systems. This is particularly so within the context of digital enterprises. 

Challenges of Implementing Integrated Systems and Digital Threads

There are a few challenges that can impede the implementation of digital threads and integrated systems. These include:

• Technical issues: Integrated systems are not easy to implement. They require professional teams to make plenty of considerations and adopt technical solutions. What’s more, for the best results, a team of professionals with the requisite expertise should implement the digital thread.
• Differing goals and scope of projects: A one-size-fits-all solution does not exist. Instead, companies must customize the digital thread per their unique needs. This calls for enterprises to identify what works for them and build their solutions around this discovery. They should also pursue achievable goals and scale appropriately.

Conclusion

The digital thread is a proven approach to helping companies implement digital transformation. It achieves this by connecting the nodes that generate data, facilitating the two-way flow of data. As a result, it makes it possible for the design and engineering team to receive feedback from different stakeholders instantaneously in what allows them to make the changes. It also allows the engineers and designers to send their CAD data to the factory floor. Simply put, the digital thread enables all stakeholders to read from the same script. The benefits that abound are quite a number. They include better quality, improved manufacturing efficiency, increased market agility, and better decision-making, to mention just a few. And while implementation of the digital thread is not without a few challenges, they can be dealt with strategically.

Exploring the Concept of Digital Twins

PTC’s Illustration of the Digital Twin of an Airplane Engine (source)

A digital twin is an up-to-date virtual (computer-generated) representation or replica of an operational process or task, real-world physical product, place, or person. To boost the accuracy of the representation, digital twins heavily rely on data. This data tells the story of the product, process, person, or environment. The data is directly sourced from the physical object or environment it represents and is used to build and subsequently improve the digital twin. Thus, the digital twin is uniquely tailored to only what it represents; after all, no two products, tasks, individuals, or processes are alike.

Usually, this data covers all project stages, from planning and design to manufacturing/construction and use. It is provided by Internet of Things (IoT) sensors and cameras as well as the professionals working on the project. This means the data is not only up-to-date and delivered in real time, but it is also accurate. It therefore provides the digital twins with reliable information that professionals can trust to mirror the exact state of the physical world. It is worth pointing out that this data is the crucial difference between a digital twin and a regular CAD model or physical-based simulation.

Broadly speaking, a digital twin acts as a singular source of information about a project, helping improve collaboration. Moreover, it provides all stakeholders with more profound insights into products, processes, environments, and personnel involved in the project. It is also worth pointing out that multiple digital twins can be integrated, providing a more enriched understanding of the interdependencies and the ecosystem within which they exist.

Building Blocks of Digital Twins

We have established that for a digital twin to be termed as such, it must have real-time or near-real-time data associated with it. But data is only one element that contributes to the wholeness of a digital twin. What we mean by this is that there are several building blocks that provide/gather, visualize, process, transfer, analyze, or use this data. The building blocks of a digital twin include: 

• Modeling
• Sensors
• IoT connectivity
• Compute

Modeling

The modeling building block includes both visualization and scientific modeling techniques. Visualization-based modeling involves the creation of 2D drawings and 3D models using CAD and Building Information Modeling (BIM) software. More on this below. On the other hand, scientific modeling techniques aid in predictions and what-if scenario planning. They predict the behavior of the digital twin and, by extension, the physical object. They are concerned with phenomena like structural deformation, fluid flow, biochemical processes, and more. The predictions are based on artificial intelligence (AI) and machine learning technologies. 

Sensors

Sensors are mounted on the physical object. They collect in real time the data relating to the behavior and characteristics of the object. The digital twin uses this data to update itself. Sensors enable professionals and building owners to identify areas where the structures are aging or nearing failure.

IoT Connectivity

IoT connectivity ensures a two-way flow of data to and from the digital twin. This building block ensures the virtual replica is a ‘living’ and ‘breathing’ representation of the physical object. Nonetheless, it is worth noting that the frequency with which the data should flow from the physical object to the virtual model varies based on the use cases. Some use cases require real-time data transfers, while others thrive on periodic data transfers.

Compute

The last building block of digital twins is computing power or compute. It is concerned with analyzing large volumes of data, helping make sense of whatever the sensors gather. The compute processes the data, converting it into usable insights. It is worth noting that the computing power should be tailored to the scale of the project and the number of sensors to reduce bottlenecks that may restrict the efficiency of a digital twin. At-scale compute is usually the reserve of cloud computing, which also efficiently stores the data. 

Linking these building blocks is a communication framework called the digital thread. The digital thread facilitates the flow of data between the real-world asset and its digital replica, with this data flow occurring across multiple interconnected informational nodes (data sources) and data storage units. It is not only integral to the creation, maintenance, update, and utilization of the digital twin but also ensures and supports the real-time, accurate evolution of the digital replica.

History of Digital Twins

The idea of using replicas to represent actual products is not new. The National Aeronautics and Space Administration (NASA) pioneered the concept in the 1960s. While it was not called the digital twin and was, in fact, not digitized, it had all the hallmarks of the technology as we know it today. At that time, NASA created, at ground level, physical duplicates of spacecraft, notably used during the Apollo 13 mission. The employees who worked as flight crew used these replicas for training and simulation. 

Technologies evolved between the 1960s and the end of the 20th century, with advances in CAD and evolutions in CAM being prominent. So evolved were the technologies that it was possible to depict digitally a physical object. Scholars like David Gelernter, who in 1991 published a book titled “Mirror World,” began imagining a future where people could start seeing the representations of realities through a computer screen. Later that decade, in 1998, the term’ digital twin’ was used for the first time to refer to the digital version of a physical object. 

However, it was not until 2002 that Dr. Michael Grieves, a professor at the University of Michigan, introduced the “Conceptual Ideal of PLM,” which had all the characteristics of the digital twin model. For the avoidance of doubt, it was not called the digital twin, at least not yet. The credit for coining the name for the digital twin model Grieves had introduced goes to NASA’s John Vickers. The term’ digital twin’ – and the modern meaning attached to it – was officially coined in 2010.

Types of Digital Twins

There are four types of digital twins:

1. Product: This type represents the product lifecycle from conception and design to manufacturing, customer use, and decommissioning.
2. Process: This digital twin represents production operations, manufacturing activities, and all tasks used to create products and services.
3. People: A digital twin of people captures data about individuals such as workers or patients. Organizations also use this type of digital twin to provide workers with information about the tasks they are required to complete. By capturing and delivering this data, this type of digital twin helps improve the efficiency of various processes in the product lifecycle.
4. Spatial: This digital twin represents places and physical environments such as workstations or factories. It helps professionals to visualize environments. As a result, they gain more information and insights into the complexities of these environments and how to better engage with them.

How Digital Twins Add Value to Physical Assets

Digital twins are not just intended to represent processes, people, products, or places. Instead, they are designed to add value to each of these assets. It is worth pointing out that the value companies draw from digital twins depends on how they intend to apply the technology. So, how do digital twins create value?

1. Digital twin CAD helps professionals and owners visualize their physical assets, facilitating easy access to and interpretation of data; this is particularly beneficial when the assets are in remote locations or are dangerous, e.g., nuclear power plants, aircraft engines, and machines.
2. Digital twins with simulation technologies can analyze various outcomes
3. Digital twins use measured and derived data from sensors to diagnose/identify and troubleshoot problems; they can suggest the cause of certain issues, enabling staff to deal with them quickly before they escalate. The data also helps managers and owners view areas where the building or product is failing or aging.
4. A digital twin can predict the future state of a physical product or environment, including its future performance, potential issues that may befall it, and the best time to carry out maintenance works.

Benefits of Digital Twins

There are numerous benefits of digital twins, including:

1. Digital twins lead to better product quality thanks to the large volumes of data that engineers can employ when creating future products.
2. They improve operational efficiency by identifying issues and providing potential solutions.
3. They increase customer satisfaction due to predictive maintenance because the digital twins inform suppliers of machines when to carry out maintenance, helping their customers avoid unplanned downtime. 
4. Digital twins reduce time to market by enabling companies to iterate and innovate faster and with greater efficiency
5. Digital twins improve productivity due to less downtime
6. They enhance supply chain resilience and agility, leading to on-time delivery
7. Digital twins lead to better planning, design, and construction
8. They improve the efficiency of products, buildings, processes, and environments
9. Digital twins reduce development costs by facilitating tests that help product designers identify clashes between components and simulate different environments. (The digital twin technology can be combined with virtual prototyping for better results.) 
10. Digital twins enable collaboration between multidisciplinary and cross-functional teams.
11. They guide companies in decommissioning equipment that has reached its end-of-life. Specifically, digital twins provide data that inform decisions such as reconditioning, reusing, recycling, or scrapping the equipment.

Digital Twins and CAD: A Symbiotic Relationship

Digital twins are nothing without the data associated with the products, processes, places, or people they are supposed to represent. They are also nothing without visualization building blocks like 2D drawings, 3D models, and 3D renderings. These visualization building blocks help represent the visual aspects of the data associated with physical objects. Naturally, this is where CAD and product lifecycle management (PLM) come in. 

For a 2D drawing or 3D model to be referred to as a digital twin, it must have data associated with it. Otherwise, it remains a 2D drawing or a 3D model. Gathered by IoT sensors and technologies, this data must be sourced from the physical object it is representing. Simply put, the data converts CAD objects from mere 2D or 3D representations positioned in a virtual space into representations of the physical form and behavior of existing real-world products, environments, tasks, or people. Against this background, all digital twins are CAD models, but not all CAD models are digital twins. 

Technological Backbone: How CAD Supports Digital Twins

CAD is a fundamental building block of digital twins. It enables professionals to visualize the physical object, creating elaborate 3D models and comprehensive 2D drawings. Moreover, CAD tools enable users to create immersive 3D renderings of the physical environment that permit immersive walkthroughs using other technologies like VR, AR, and MR. Modern CAD systems, which ship with built-in computer-aided engineering (CAE) tools, also support simulations. 

Usually, CAD is a foundational step to creating a digital twin; it is the backbone. It is, therefore, accurate to say that there is no digital twin without CAD. In fact, digital twin platforms integrate with CAD and BIM solutions. For instance, Autodesk Tandem, a digital twin platform, is designed to integrate CAD geometry from Revit, geospatial data, facility management data, IoT data, and more. 

Companies have also used several solutions from Siemens Digital Industry Software to create comprehensive digital twins of their projects, with CAD and simulation tools playing a crucial role. Given the need to combine the capabilities of multiple software and tools, selecting tools and software that support interoperability is vital. For its part, Siemens packages the interoperable tools, offering them as Digital Enterprise Services.

Similarly, PTC partnered with Ansys to create a digital twin offering that combines interoperable products from both companies. The offering combines PTC’s ThingWorx, an industrial IoT software, with Ansys Twin Builder, a powerful modeling, simulation, and analysis tool to create virtual replicas of physical assets. While PTC already had IoT software, it had to partner with a company whose solution has the other building blocks of a digital twin, emphasizing CAD’s status as the backbone of digital twins.

Applications of Digital Twins in CAD

You can deploy digital twins in various industries, from logistics, agriculture, and healthcare to manufacturing and architecture, engineering, and construction (AEC).

Digital Twin in Manufacturing

The manufacturing industry has been a hotbed of implementing the digital twin. This is partly because a typical factory already has hundreds or thousands of sensors. Additionally, CAD and CAE use is commonplace during the early stages of product development, with CAM tools also featuring prominently. Thus, digital twins bring together existing technologies as opposed to introducing novel tools. 

Manufacturing organizations use digital twins for predictive maintenance, optimizing the maintenance of machines. They also use digital replicas to observe the behavior and performance of various components that make up the product. This enables them to identify parts that are wearing out faster than anticipated. Armed with this information, companies in the automotive industry, for instance, can arrest this problem early enough, which limits the number of recalls.

Digital twins of the factory floor enable managers and staff to identify issues – and quickly address them – as well as opportunities for improving operations. As a result, digital replicas enable companies to improve delivery and the performance of their facilities. To complement the use of digital twins and their benefits, manufacturing companies are also adopting other strategies.

For instance, some are implementing the model-based enterprise (MBE) strategy. An MBE is a manufacturing company that uses 3D CAD models throughout the product lifecycle to manage business processes. Such a company reaps multiple benefits of the strategy, including improved efficiency, reduced time to market, lower cost, and more.

Digital Twin in AEC

Before the onset and increased proliferation of digital twins in CAD, the AEC industry predominantly used manual workflows and paper-based information exchange. For instance, all data about a construction project or building, as well as its performance over its planned lifetime, was collected physically by personnel who had to be onsite. This means the data was directly and solely housed inside the precincts of the building. The data was then documented using static documentation like computer files and paper. But not anymore.

Digital twins in the AEC industry have obliterated this traditional practice. Now, IoT sensors are installed all through the building or structure, enabling real-time or near-real-time data collection. This means the digital twin is updated regularly to reflect the real-time characteristics of its physical replica. Which breathes life into the digital replica. This has had many advantages.

For instance, in 2021, a digital twin of an eight-decade-old bridge in Norway helped prevent a disaster. IoT sensors installed on the real-world bridge sent notifications of unusual movement – the sensors showed that the end of the bridge was moving up and down whenever a track passed. This led to the realization that there was a problem with one end of the bridge’s support. As a result, officials closed off the bridge and began constructing a new bridge.

Digital Twin in Healthcare

It might be hard to comprehend how the digital twin and CAD technologies are applied in the healthcare industry. But researchers have found that the potential uses of digital twin technology in this industry are limitless. They can be used to monitor the performance of equipment and medical devices. Digital twin and CAD systems can be used to create digital models of health facilities to monitor and analyze care delivery as well as predict the impact of personalizing care. 

Perhaps a more practical use case has been spearheaded by Dassault Systèmes through its Living Heart Project, which began in 2014. The project brought together medical, biomedical, and pharmaceutical experts with a common goal of building and validating a virtual twin of the heart. It is hoped the project will increase industry innovation and wend the way to an efficient pathway for patients to access new treatments for heart disease. The Living Heart Project has inspiredthe Living Brain, Living Lungs, and Living Liver Projects

Another potential application of the technology, which is still under development, is using digital twins of patients. These digital replicas will have the patients’ respective medical histories. Moreover, they are expected to be coupled with IoT sensors that measure and relay patients’ health information for real-time monitoring and evaluation against their medical histories.  

Digital Twin in Logistics

The logistics and shipping industry is quite complex – ensuring products reach their intended destination in good condition and on time is definitely not easy. Moreover, coordinating multiple shipments to and from disparate locations simultaneously adds to the complexity. But one thing is certain: that shipping does generate vast volumes of data that logistics companies can use to ensure faster, more efficient, more eco-friendly, and more secure shipments. That is where digital twin and CAD technologies come in. 

However, in this sector, a single digital twin does not cut it. The companies should integrate multiple digital twins that separately capture information about fulfillment centers, warehouse operations, garages, parking locations, or vehicle locations. Collating the data from these disparate sources can itself be a daunting task. Which is why it is advisable to use at-scale compute based on the cloud.

Digital twins in logistics provide in-depth insights into operations, helping professionals plan, design, and optimize shipping roots and supply chains.

Digital Twin in Agriculture

Digital twin and CAD can be used in the agriculture industry. Here, CAD and GIS systems are used to create digital twins of farms, with satellite imagery capturing data and AI and ML models analyzing it. This data can range from farming activities, weather conditions, and water availability to crop variety and health and soil quality. 

The combination of digital twin and CAD/GIS in agriculture facilitates crop yield and risk predictions. It can enable farmers to automate farming activities like soil preparation, fertilization, and crop rotation. It can also help them predict the planting and harvest times that guarantee high yields. The technology can also be used for monitoring and managing livestock as well as optimizing their population. 

Digital Twin in Mining and Energy Sector

Digital twins enable mining companies to simulate the work environment, equipment, and machinery, allowing the miners to test new methodologies and techniques and create short-term and long-term mining programs. The technology also allows the companies to create estimates of the drilling, crushing, and extraction programs and train their personnel off-site before deployment. The digital twin also facilitates predictive maintenance.

Digital Twin in Infrastructure and Urban Planning

Infrastructure organizations such as rail equipment companies, electricity transmission system operators, and state departments for infrastructure and urban planning use digital twins to simplify equipment maintenance, plan and monitor day-to-day operations, and visualize planned expansions or future projects.

Challenges and Considerations in Implementing Digital Twins in CAD

There are several challenges to implementing digital twins in CAD and, more broadly, various industries. Indeed, real-world products, environments, and processes can be complex, yet their digital twins should capture their inherently complex characteristics and behaviors to a tee. The need for precise digital matching of these physical objects can overshoot the budgetary allocations and available computing resources. It can also exceed in-house data governance capabilities and move away from the organization’s culture. 

In this section, we will discuss the challenges companies and professionals face when applying digital twins in CAD. We will also discuss the considerations they can make to limit the impacts of the challenges.

1. Prohibitive Cost

Implementing digital twins in an organization requires substantial investments in CAD software, sensors, cloud computing infrastructure, IoT dashboards, and other supporting technologies. The investment can cover 3D model and AI model development. The cost can be prohibitive, preventing companies from realizing the true potential of the digital twins. 

Fortunately, you do not have to deplete your bank account chasing a complete digital twin product. First, comparing the digital twin approach to alternative, more pocket-friendly approaches is essential. You might be shocked to discover cheaper alternatives that can deliver the same value as more expensive digital twins. You can also opt out of picking a cloud computing provider and instead use a conventional database. 

Nonetheless, the cost of technologies that enable and enhance the digital twin is dropping. This has accelerated the adoption of digital twin, CAD, and associated technologies.

2. Poor Data Quality

A good and reliable digital twin is associated with equally reliable and quality data. However, that is not always possible with large-scale projects. These projects are characterized by hundreds or thousands of sensors that operate in ever-changing and demanding field environments and communicate over flaky networks. Unfortunately, these factors work in concert to lower the data quality, limiting the creation of good digital twins.

To get around this problem, companies will need to come up with methodologies to identify and isolate the poor-quality data. Moreover, they will have to find ways to bridge the information gaps and inconsistencies arising from these measures.

3. Imprecise Representation

A digital twin should replicate its physical counterpart exactly. However, it is not feasibly possible, at least presently, to match the thermal, electric, chemical, and physical properties and characteristics of physical objects. And in cases where it is possible, the process is costly, time-consuming, and challenging. This challenge forces engineers and designers to simplify their creations and make assumptions. These considerations enable them to find a middle ground where there is an ideal balance between the desired characteristics of the twin and the cost-related and technical constraints.

4. Data Security and Intellectual Property (IP) Protection

As we have repeatedly mentioned, a digital twin is a creation of data. Usually, this data is proprietary. It can relate to patented or copyrighted products or product designs that are considered trade secrets. Moreover, the digital twin may contain sensitive data relating to usage and customer processes. 

The sheer volume of data required to create a digital twin gives rise to challenges around data security and IP protection. In this regard, companies should use up-to-date measures to secure their data to prevent costly data breaches.

5. Cybersecurity Threats

The various building blocks of digital twins form a large attack surface that cybercriminals can target. And given the need for hundreds or thousands of internet-connected sensors, the attack surface grows even larger. Of course, criminals’ intentions can be driven by the importance of digital twins and their associated data to organizations’ operations. By accessing proprietary data, criminals may want to extort companies into giving them large sums of cash so they do not release their illegally obtained find or compromise the digital twin. 

The various unwanted outcomes of security breaches point to the need to prioritize cybersecurity. But the effective management of the cybersecurity of digital twins may not be easy for some organizations given the sheer number of software, parts, and professionals needed to create a working digital twin.

6. Difficult Change Management and Capacity Building

Whenever management opts to introduce digital twin technology to an organization that has previously not implemented it, there is bound to be resistance or sluggish adoption. Change is hard, and when the change involves as complex a technology as the digital twin, then it becomes even harder. This presents a critical challenge around change management and capacity building. 

Organizations must make sure their employees possess the necessary skills to work on digital twins. Moreover, companies must find ways to motivate their employees sufficiently to make the shift. While these requirements are not easy to achieve because of the need to profoundly shift the organizational culture, companies can turn to education to solve this challenge, seeking the instructional guidance of experts in digital twins and technological transition.

7. Lack of Interoperability and Data Standardization

A digital twin is a summation of numerous parts, most of which are provided by different vendors and suppliers. While they are supposed to work in congruence, at least in theory, this is not the case in practice. Moreover, AI and simulation tools, which are expected to all serve the same function, may not support this capability. It is not uncommon to find an AI tool or simulation application from one provider that is incapable of replicating the capabilities of another supplier’s product. This creates the challenge of interoperability.

Another challenge is the lack of data standardization. This challenge prevents data from one building block of a data twin from being integrated into another. For instance, data from a digital twin CAD software may be stored in a proprietary file format that cannot be opened using any other tool. To get around this problem, organizations should use standardized file formats and look for tools that support interoperability.

Conclusion

Digital twins are increasingly becoming commonplace in multiple industries, shaping the future. The growing adoption of digital twin technology is driven by the convergence and increased evolution of technologies like the IoT, sensors, artificial intelligence, machine learning, cloud computing, simulations, and more. The technology is using data to breathe life into the once-static CAD models. With it, many benefits abound. 

Digital twins can describe physical assets, diagnose problems, analyze outcomes, and predict future events. This value has seen companies and organizations in the manufacturing, healthcare, mining, infrastructure and planning, agriculture, and logistics industries adopt digital twins. However, their implementation has not been without a fair share of challenges. From poor data quality and lack of data standardization to difficult change management, cybersecurity threats, imprecise representation, and the need for IP protection. Fortunately, there are ways to get around this problem.

However, digitalization in manufacturing and construction has led to significant process improvements, changing the traditional narrative. Manufacturers are now focusing more on validating complex part designs, reducing waste, enhancing existing products, cutting costs, and minimizing environmental impact. Similarly, professionals in the architecture, engineering, and construction (AEC) industry are keen on achieving similar results with their designs. 

To address these needs, professionals are adopting virtual prototyping, backed by computer-aided design (CAD) solutions. This article explores virtual prototyping in CAD, discussing how it is implemented in CAD/CAE/CAM systems, how it is integrated with various technologies, and its role in supporting sustainable design. But first, what is prototyping?

What is Prototyping?

In the early stages of design, many aspects of a product or building are mere ideas. And with ideas, it is harder to conceptualize worthy alternatives, test theories, or evaluate performance. Usually, it is easier to understand the mechanics of a product if there is a realistic representation or physical model to see and use. This is where a prototype comes in. The term ‘prototype’ refers to the sample or initial version of a part that is used to test the aesthetic and usage characteristics, confirm performance, or explore design alternatives.

Prototyping, therefore, refers to the process of creating prototypes to evaluate the designs of products under development and correct errors and flaws in the conceptual designs. This process can be implemented in three main ways, considered the main types of prototyping: 

• Physical prototyping
• Rapid prototyping
• Virtual prototyping

Physical Prototyping

In physical prototyping (PP), professionals in the industrial product sector develop a partially or fully working part or product. However, this process is costly and should not be performed at the early stages of the design phase. Instead, physical prototyping should be reserved for the later stage of design. 

At this juncture, most – if not all – of the design issues should have been identified and potentially addressed. Developing physical prototypes is nonetheless advantageous as it enables designers to interact with the product in real time. Generally, physical prototypes are fabricated using CNC machines and CNC machining processes.

Rapid Prototyping

On the other hand, rapid prototyping (RP) refers to techniques and technology that aid the fabrication of scale models of a product. This implementation of the concept of prototyping is cheaper and faster than physical prototyping. But it creates less comprehensive models than products created using physical prototyping techniques. Virtual prototyping offers a solution: a quick and cost-effective way to create a comprehensive product representation.

Virtual Prototyping

So, what is virtual prototyping? Virtual prototyping (VP) refers to the process of creating and testing virtual products. It helps design professionals visualize and envisage the virtual representations of products by creating their detailed digital twins. 

To paint the full picture, VP involves constructing the design and parametric product model in computer-aided design (CAD), carrying out part or product performance simulations and reliability analysis using computer-aided engineering (CAE), and conducting manufacturing simulations and cost estimations using computer-aided manufacturing (CAM) and computer-integrated manufacturing (CIM) systems. To this end, integrated CAD/CAE/CAM systems, along with other supporting technology, are the backbone of virtual prototyping.

Virtual Prototyping vs. Rapid Prototyping and Prototyping

VP solves some of the individual problems associated with rapid prototypes and prototypes. Prototypes are expensive, while rapid prototypes are usually not detailed or comprehensive enough to support the validation of various characteristics of their design. Nonetheless, virtual prototyping has emerged as a formidable solution to these two problems. It is inexpensive yet creates comprehensive virtual prototypes with which designers can virtually interact and perform tests. 

This practice enables designers and other team members to perform comprehensive design reviews prior to physically creating the products. As a result, virtual prototyping substantially lowers the cost associated with design, including design creation and validation, because it reduces the need for numerous physical prototypes. 

In addition, virtual prototyping facilitates the creation of different iterations and variants of the design that are enriched with new information, permitting virtual but direct comparisons. The virtual prototypes can also be shared with other off-site teams. Put simply, virtual prototypes answer core questions of the design and development process at least as well as prototypes.

Virtual prototyping can be applied in a myriad of industries, including software engineering. However, this article explores virtual prototyping as it relates to computer-aided design. In this context, virtual prototyping can be applied in the AEC and manufacturing industries.

The Mechanism of Virtual Prototyping in CAD

Virtual prototyping relies on CAD/CAE/CAM solutions, which come equipped with tools and modules for simulation and testing. But what CAD tools are used in virtual prototyping? How do commercial software publishers implement virtual prototyping in their software? Let’s find out.

Virtual Prototyping Tools in CAD Software

Design and Modeling Tools

Virtual prototypes are created using design and modeling tools found in most commercial CAD software. This means the foundational aspect of virtual prototyping is design and modeling because it turns ideas into geometric objects and models that can be viewed on a screen. You can create the models using either the direct modeling approach or feature-based parametric modeling. 

Direct modeling allows you to create or modify models without setting constraints, relationships, or parameters. Instead, all you have to do is create geometric objects and then use the boundaries that define these objects – namely, the faces, edges, and other features – to shape the objects. This modeling paradigm enables designers to easily create and change prototypes’ shapes and dimensions, especially if the product has simplistic geometry. 

Conversely, parametric modeling involves defining dimensions and relationships that shape the part’s geometry, allowing changes to one dimension to automatically update the entire model. Parametric modeling is ideal when creating virtual prototypes with complex geometries. This is because any change to one dimension is automatically propagated to the entire model. Therefore, parametric modeling allows design engineers to explore multiple alternatives conveniently and very easily.

Motion Simulation and Analysis Tools

Motion simulation and analysis tools accurately simulate and analyze the motion of parts in an assembly. These tools are designed to incorporate the effects of friction, external forces, dampers, and springs, for example. It also considers the material properties, mass, motion constraints, and more. Besides providing accurate information regarding the motion of the parts, motion analysis also calculates loads that can be fed into structural analysis calculations.

Selecting the appropriate joints is crucial for accurately simulating the mechanical system’s behavior in models. Nonetheless, some CAD applications ship with intelligent modeling capabilities that automatically specify the correct joints based on the relations between the various parts in an assembly or subassembly.

Collision Detection Tools

Collision detection tools identify specific points of contact between assembly parts, resulting from their intended movement. The contact can be intentional or unintentional. In cases where the contact is intentional, the collision detection tool enables design engineers to ascertain whether the contact is made as originally envisioned. If not, they can modify the dimensions accordingly. In cases where the contact is unintended, the collisions can lead to product failure. In such instances, the collision detection tool enables design engineers to find unintended collisions and correct the geometry of the parts to prevent unintended contact. 

Product Performance Analysis Tools

Built-in CAE tools in CAD software facilitate a range of product performance analyses, such as structural, fatigue, buckling, and fracture analyses. Design engineers can also use 3D models to carry out extensive tests such as noise analysis, vibration analysis, thermal analysis, tolerance analysis, human factor analysis, frequency analysis, lighting, energy consumption, and fire tests. 

Virtual Assembly and Manufacturing Tools

Some CAD software applications include virtual prototype assembly tools that allow engineers to evaluate the performance of multiple assemblies before anything physical is ever created. Other CAD/CAM systems have virtual manufacturing modules that simulate the entire manufacturing process, identifying issues that can be addressed before production begins. 

Some systems include CAM modules for virtual machining processes like turning, drilling, welding, casting, molding, and milling. To use such modules, a designer or engineer incorporates the part designs and inputs vital information such as the cutting parameters, cutting tools, nature of the workpiece, and fixtures. 

The modules will then generate a toolpath, simulate the machining process, calculate the machining time, and produce data related to the cutter location. This information enables the engineers to plan and quantify the assembly time, machining time, and labor costs. It also enables them to rectify any mistakes that might otherwise lead to scrap.

Implementation of Virtual Prototyping in CAD

Commercial CAD solutions offer virtual prototyping capabilities, but the implementation varies across different platforms. Some software publishers have created standalone products that are purely dedicated to analysis and testing. These products are known as computer-aided engineering (CAE) software. Examples of such publishers include Siemens Digital Industries Software, Ansys, and PTC.

Siemens offers analysis and data acquisition software called Simcenter Testlab durability, vibration, and noise testing. This software supports virtual prototype assembly (VPA), which lets test and simulation engineers explore the performance of multiple assemblies without creating a physical prototype. Ansys offers a comprehensive suite of simulation software covering all fields of engineering. PTC has created Creo Simulation, a standalone simulation software that comes complete with vibration, thermal, and structural analysis tools as well as finite element analysis (FEA) capabilities.

But perhaps the more popular implementation of virtual prototyping in CAD involves integrating design, analysis, simulation, and manufacturing capabilities within a single system. Such solutions are known as CAD/CAE/CAM or CAD/CAM systems. They support design and modeling and have built-in analysis and simulation tools. They can also carry out manufacturing simulations.

Leading software publishers like PTC, Dassault Systèmes, Siemens, and Autodesk have followed this more popular implementation. Software like Creo (by PTC), CATIA (by Dassault Systèmes), and NX (by Siemens) are integrated CAD/CAM systems. This means they support the entire gamut of processes that constitute virtual prototyping. 

Other mid-range software, like SolidWorks, Solid Edge, Inventor, and Fusion 360, can perform CAD and CAE-related tasks but lack CAM capabilities. However, such software supports CAM add-ons, which add the unavailable capabilities, supporting all the steps required to complete virtual prototyping.

Integration of Virtual Prototyping with Other Technologies

Virtual prototyping integrates seamlessly with technologies that enhance visualization and interaction with virtual models for designers and engineers. They include:

• Virtual reality (VR)
• Augmented reality (AR)
• Mixed reality (MR)

Virtual Reality

Meta Quest 3 VR Headset (source)

Virtual reality (VR) uses computing power to create simulations of real or imagined environments and objects. The simulated environment appears on screens within the VR headset. (These headsets do not allow light from outside to enter the wearer’s view.) These environments can resemble the real world, as in simulations for Formula 1 driver training or pilot training. Alternatively, it can be an imagined environment that significantly differs from reality. A great example of the latter is the simulated worlds that form the basis of VR games. 

Both real and imagined VR environments primarily rely on visual simulations. But the evolution of VR technology has birthed other capabilities. Most modern advanced VR applications and solutions not only include hyper-realistic, high-fidelity, and real-time visualization techniques and capabilities but also support multi-modal interactions anchored in visual, haptic, and auditory feedback. Such solutions have speakers that render sound. Also, they can be natively connected to haptic devices to deliver tactile and force-feedback information. 

The use of virtual reality in CAD is not exactly a new concept. It was, in fact, the brainchild of Ivan Sutherland, a key figure in the history of CAD. (Sutherland developed the first 2D engineering design and drafting software to pioneer human-computer interaction.) Many years later, VR is still crucial to CAD and is one of the technologies that aid virtual prototyping. 

VR in Virtual Prototyping

VR technologies enable design engineers to visualize and interact with virtual prototypes. They are particularly effective as they help the engineers to validate the aesthetic properties of products. Moreover, their support for multi-modal interactions has been shown to achieve accurate and effective validation of the behavior of the products. This is because VR technologies can visualize virtual models that have the same characteristics and behavior as the corresponding physical product. Therefore, they enable designers and engineers to interact with the evolving shapes of the product using their hands, ears, and eyes. 

Augmented Reality (AR) and Mixed Reality (MR)

Magic Leap 2 AR Glasses (source)

Augmented reality (AR) overlays computer-generated images and digital content onto the real world, visible through wearable devices like AR glasses or handheld devices. (The device must have a camera and a screen, which enable the device to parse a video feed.) AR aims to enhance the real world with computer-generated information that, though superimposed on a screen, does not block the user from seeing or perceiving what they would have otherwise seen had the screen not been present.

Mixed reality (MR) merges the capabilities of VR and AR. MR devices enable users to interact with both virtual and physical objects simultaneously. It, therefore, involves mixing the virtual and real worlds, i.e., mixing reality.

AR and MR in Virtual Prototyping

AR devices are particularly appropriate for the design world. Imagine a scenario where a designer can walk around a virtual prototype, examining its characteristics from every angle as if it were an actual product. AR technologies crystallize this imagined scenario, making it a reality. They enable designers to bring products to life and modify the designs according to their analysis and observations before a physical prototype is built.

MR solutions can also be a great design and virtual prototyping tool, particularly in cases where designers want to improve the designs of existing products. They can attach a virtual prototype to an existing product and compare certain characteristics. 

Interaction with Virtual Prototypes

Designers and engineers can interact with virtual prototypes in myriad ways. This depends on the technology they have used to visualize the virtual prototype. The traditional method is, of course, based on the use of a keyboard, mouse, and computer monitor. Nonetheless, VR, AR, and MR systems have emerged. They enable designers and users to interact with virtual products in ways that more or less mimic real interactions. For instance, VR, MR, and AR technologies support haptic, visual, and sonic feedback, which supports the evaluation of products’ mechanics in a more realistic way.

The Role of Virtual Prototyping in Sustainable Design and Engineering

Sustainable design focuses on using natural resources efficiently, reducing waste, and minimizing environmental impact. Sustainable design not only focuses on the concept of ‘reduce, reuse or repurpose, and recycle’ but is also about value addition and designing products that solve environmental challenges. It encourages trade-offs. Sustainable design also has a cost element to it – it reduces the cost of manufacturing or construction. 

Indeed, sustainable design is particularly effective if it starts delivering benefits as early as possible during the design conceptualization and validation stages. This is where virtual prototyping comes in. 

Virtual prototyping allows companies to drastically reduce the number of prototypes needed, from hundreds to an average of one to three, before finalizing a product. This is because VP and supporting visualization technologies like VR, AR, and MR enable designers to visualize virtual products in their entirety. These technologies enable designers to walk around the scaled versions of the products. 

As a result of using virtual prototyping, designers can notice – and correct – flaws and shortcomings in the original designs. They can also identify ways of improving their designs in what can further minimize waste. Thus, VP plays multiple roles in supporting sustainable design and engineering:

• Virtual prototyping promotes zero-waste designs by allowing designers to eliminate unnecessary parts of a product or building, avoiding the use of excess material without functional benefit
• Virtual prototyping eliminates the need for multiple physical prototypes, minimizing waste
• Virtual prototyping enables designers to identify ways to create designs that reduce energy consumption during the creation of the physical prototype and market-ready product as well as the manufacturing time, thus reducing environmental impact

Conclusion

Virtual prototyping is a different way of representing products and buildings. It relies on CAD/CAE/CAM systems, which create virtual prototypes that are meant to be used in the same way as physical prototypes, albeit in a virtual environment. The virtual prototypes are solely meant to help designers and engineers identify flaws and shortcomings in their designs through simulation and testing. 

Armed with the test and simulation data, design professionals can then come up with better designs that minimize both waste and environmental impact. Virtual prototyping reduces the need to create multiple physical prototypes way before finalizing the product design. This way, VP promotes sustainable design. It is also worth noting that VP can be integrated with other technologies, including VR, AR, and MR. These technologies enable designers to better visualize and interact with their virtual creations. 

Perhaps less recognized – compared to the likes of ChatGPT – is how AI is used in the CAD industry. As tech companies – small, mid-market, and large – have been hard at work developing AI-driven solutions for their target consumers, so too have developers like PTC Inc., Autodesk, Siemens Digital Industries Software, Nemetschek Group (parent company of Graphisoft and Vectorworks), and Dassault Systèmes. It is thanks to the efforts of the latter group of companies that we now look at the role of artificial intelligence in the CAD industry.

Brief Overview of AI in CAD Industry

Intelligent designs are not a new concept. So old is it, in fact, that a 2022 research paper notes that the first proposal of intelligent designs was in the 1960s at the early stage of CAD development. Nonetheless, AI in the CAD industry has only become more prominent in the last few years, thanks to cutting-edge developments in the tech world led by the likes of Nvidia, whose chips power AI data centers. 

In the CAD world, like anywhere else, computer systems are trained using data and models to become intelligent. Here, model-based reasoning (MBR) merges CAD with AI. The systems use qualitative and quantitative analysis to predict what should exist next or between various parts of a design. 

The training data often includes design data and documentation from completed projects as well as real-time software usage by veteran users. Upon synthesizing this data, the systems can now utilize the knowledge to come up with intelligent suggestions that designers and engineers can use to guide their decision making. The systems can also identify patterns in data from different sources, offering better and more profound insights or bettering design practices.

AI-Powered CAD Design and Modeling

Developers of CAD software are increasingly acknowledging the power of AI in eliminating repetitive tasks, improving productivity, and providing intelligent and helpful suggestions. As a result, they are increasingly integrating AI-driven solutions into their products.

For instance, software products now use AI algorithms to generate multiple permutations of designs based on user-defined objectives. They then parade the permutations within a single user interface, enabling the user to evaluate them visually. Additionally, some products feature evaluation metrics that simplify the comparison process. This is known as generative design, and it uses automation to provide better insights regarding a design, thus enabling faster and better decision making. 

Thanks to AI, repetitive tasks, such as selecting similar components, can be automated. AI can even offer suggestions that improve the workflow, resulting in better productivity. Additionally, the AI-driven speed-recognition capabilities eliminate the need to manually select frequently used commands. As if that’s not enough, some software solutions can be trained to recognize new commands beyond what they had initially been programmed to accept.

Companies and Software Using AI for Design and Modeling

1. Autodesk with Revit

The Generative Design tool in Autodesk Revit produces multiple design options based on your goals (such as maximizing or minimizing the total cost, value per year, or volume outside zoning), constraints, and inputs. It then allows you to evaluate each design against the project objectives. If you did not get it right on the first try, Revit’s Generative Design feature allows you to tweak various aspects of the inputs and goals to generate additional design options. This way, the software enables you to find the best solution possible. 

2. PTC with Creo

Creo offers AI-driven generative design to help you deliver only the best designs in less time. The tool generates several optimal designs for a particular engineering problem based on an array of user-defined design requirements. It mandates you, the user, to specify your goals and requirements, including your preferred manufacturing processes and materials. Thereafter, the software generates the best manufacture-ready design. The tool enables engineers to create superior designs and drive quick and efficient product innovation. It also improves productivity and delivers designs that will result in high-quality, lower-cost, and manufacturable solutions.

3. Siemens Digital Industries Software with Siemens NX

Siemens NX is a comprehensive mechanical engineering software package. It leverages AI and machine learning in three primary ways: personalization, smart human interactions, and intelligent suggestions. Importantly, it does this without explicitly programming these characteristics or rules therein. The smart interactions are in the form of predictions – the software uses AI to quickly identify geometrically similar components. Additionally, the software supports voice commands, enabling users to use speech to invoke commands, teach the system phrases or words that enable it to carry out everyday tasks, and navigate menus and operations.

Regarding personalization, NX monitors how a user uses the software to solve a problem, collects this data, uncovers the underlying patterns, and subsequently personalizes the problem-solving experience. More specifically, the software determines the commands that the user uses and their preferred location on the user interface. It then only serves these contextual commands, thus boosting productivity. Moreover, NX learns the efficient workflow of experienced users when they complete a task and uses that knowledge to teach/train new users on how to complete it.

4. Dassault Systèmes with SolidWorks 

SolidWorks’ 3D Creator and 3D Sculptor enable users to enjoy the power of AI and ML through the Design Assistant tool. Designed to reduce the number of repetitive tasks, this tool is equipped with a number of AI-driven solutions. These include:

• Selection Helper: it identifies components such as chamfers, fillets, or edges that are similar or symmetrical to what you had picked. It uses AI to predict the components you are likely to select based on what you have done so far
• Mate Helper: It enables you to automatically add or insert additional instances of duplicate objects or components, such as bolts and fasteners. It does this by suggesting locations where such components can fit.
• Sketch Helper: It predicts what you will sketch next based on your earlier sketches. It also quickly creates a duplicate of your earlier sketches. Moreover, it can add these sketches to multiple locations provided they have similar characteristics and features as the geometry surrounding or underlying the first sketch.
• Smart Mate: It automatically creates mates whenever you drag and hold a component in a position where you want it to mate with the surrounding components. This solution automatically recognizes the correct mating faces, enabling it to create fully constrained mates.

AI-Powered Mate Helper Feature in SolidWorks (source)

SolidWorks has another trick up its sleeves: these tools learn from your workflows, adapting in real time. To put it simply, SolidWorks’ AI algorithms use the data generated as you use the software to gain more insights about your preferences and become even more intelligent.

AI-Powered CAD Analysis and Simulation

CAD analysis and simulation utilizes a number of techniques, ranging from finite element analysis (FEA) and finite volume methods (FVMs) to finite-difference time-domain (FDTD) and dynamic visualization. These techniques have been developed over more than five decades to increase solver efficiency and user-friendliness. Still, challenges remain, with simulations requiring a number of simultaneous trade-offs that revolve around the accuracy and speed of results and the robustness and ease of use of the workflow. 

Take the example of FEA. In order to perform an accurate simulation using this technique, the software must prepare the geometry of a 3D model and subsequently create nodes that represent the shape of the geometry. It is the collection of these nodes that is known as a mesh. However, geometry preparation and meshing are considered two of the most time-consuming, expertise-extensive, and error-prone tasks performed in a conventional simulation. How so? 

If the meshes are coarse – a situation whereby the nodes are sparsely distributed – the result will be a loss of accuracy even though the simulation will be completed faster. The inverse is also true. Similarly, an easy-to-use workflow with simple meshes will lower the accuracy and trigger other issues.

In such a case, AI can be used to solve these problems. It can, for instance, improve the accuracy and speed of results while ensuring the workflow is robust and easy to use. This way, AI-powered CAD analysis and simulation solutions can boost productivity and help narrow the gap between the ideal world and what happens in reality. 

Companies and Software Using AI for Analysis and Simulations

1. Altria with SimSolid

AI-driven analysis and simulation solutions exist. For instance, Altria SimSolid®, a structural analysis tool, enables quick design iterations by generating simulations without meshing and geometry preparation. This way, it reduces the time taken to perform analyses and simulations. SimSolid generally uses a meshless approach to calculating stresses and deflections. More specifically, it utilizes AI and machine learning algorithms to analyze the geometry of a 3D model. It relies on training data that comprises past simulations of numerous models to come up with accurate measures of deflections and stresses.

AI-Powered CAD Building Information Modeling (BIM)

AI-powered BIM solutions aid in intelligent project management. They also enhance safety and mitigate risks. Below are some examples of how BIM solutions have implemented AI.

Companies and Software Using AI for Building Information Modeling

1. Bricsys with BricsCAD BIM

Bricsys utilizes the power of AI and ML in some of its products. Its BricsCAD BIM software, for example, uses AI and ML algorithms to automatically classify building objects or elements. This solution is available via the software’s BIMIFY tool. It allows you to conceptualize and create any shape or object without stipulating the classification. Once you complete the demanding design phase, you can use BIMIFY to add this metadata on your behalf. And while it does this automatically, the software gives you the ability to manually change the classification.  

Other BricsCAD AI-driven tools include: 

• BricsCAD BIM’s generative design functionality automatically converts a set of solid objects into a building
• Its style guide uses AI to identify a model’s elements and styles and copy it into another project
• The Propagate tool allows you to copy detailed and complex connections between walls and floor slabs, for example, to a similar location on a model

2. Autodesk with Construction IQ

Autodesk Construction IQ is a BIM solution that enables project teams to mitigate risk and improve day-to-day performance. It uses construction language analysis, an AI method, alongside algorithms to understand and predict complex project issues and automatically assigns priority to the most pressing ones. It also learns from the descriptions that quality managers across projects use and subsequently generates issue-specific descriptions. 

Moreover, it calculates the risk associated with the issue. What’s more, Construction IQ considers a number of factors surrounding the party responsible for fixing the issue. For instance, it takes into account their past behavior of issue management and current workload, as well as the importance of the issues for which they are responsible. The solution also scans all safety issues on a job site and identifies those that could cause potential fatality. It then brings that knowledge to the attention of safety managers.

Construction IQ’s AI-Powered Risk Management Tab (source)

AI-Powered CAD Manufacturing

AI in CAD manufacturing can be a boon for manufacturers. Firstly, it boosts productivity by enabling designers and engineers in both senior and junior positions to produce quality designs within a short time. For instance, generative design tools produce an array of designs that have been intelligently created to conform to user-defined goals and requirements. Such designs take into account the manufacturing method as well as the materials to be used. To put it simply, AI-powered CAD manufacturing tools create designs that are optimized for particular goals. Additionally, these designs result in lighter, less expensive, stronger, and more efficient products than those designed using traditional approaches, particularly because the designs are tailored to your preferred manufacturing method.

Additionally, some developers offer AI-reliant tools that monitor the entire manufacturing process. These solutions can predict failure by leveraging an extensive data set that contains parameters associated with certain incidents. Using the power of AI, such solutions can establish when parts will likely fail, the reason for failure, and the exact parts that will fail. Armed with this knowledge, manufacturers can schedule maintenance, preventing unexpected downtime. This way, the solutions optimize the manufacturing process.

Companies and Software Using AI for CAD Manufacturing

1. Autodesk with Fusion 360

Autodesk’s Fusion 360 uses AI to accelerate the entire design to manufacture pipeline through what the developer refers to as generative design in Fusion 360. This tool generates multiple CAD-ready solutions based on manufacturing constraints (such as manufacturing method used), costs, and product performance requirements. 

For the software to generate a design, it requires you, as the user, to stipulate the essential geometrical aspects of a problem. For instance, you can select regions that must remain, the load that the part must withstand, and the areas that should be avoided. You should also enter your preferred material options and objectives (e.g., a prompt to achieve a specific factor of safety and maximize stiffness). Once the software generates the designs, it allows you to compare them based on properties that are important to you.

Generative Designs in Fusion 360 (source)

Fusion 360’s generative design in manufacturing offers the following domain-specific benefits: 

• CNC machining: It improves consistency across a variety of CNC machines, including 2.5-axis, 3-axis, and 5-axis machines
• Injection molding: It optimizes the effectiveness of high-volume injection molding, achieving higher production rates with lower cycle times
• Casting: It enables the casting of complex shapes, intricate sections, and products with greater mechanical properties; it also reduces the production costs
• Additive manufacturing: It reduces material and time waste and results in better quality time by enhancing innovation and improving design freedom

2. PTC with ThingWorx 

PTC Inc. offers an AI-powered industrial internet of things (IIoT) solutions platform called ThingWorx. Among the solutions that form part of this platform is a predictive maintenance tool that uses AI to detect failure by identifying parameters that could cause incidents and predict parts that will fail, why they will fail, and when they will fail. This way, it prevents downtime and optimizes service calls. Moreover, ThingWorx utilizes AI to enable manufacturers to improve overall manufacturing efficiency, optimize production by augmenting equipment effectiveness, and perform remote asset monitoring.

AI-Powered CAD Data Management

Indeed, data management can be laborious, as it involves everything from collection, cleaning, integration, organization, labeling, and cataloging. But AI-driven solutions are increasingly being applied to deal with some of these labor-intensive tasks. In fact, AI has been shown to increase the quality, security, and accessibility of data. For instance, AI can classify data from different sources, including documents, designs, process plans, and more. Furthermore, it can catalog this data, helping users to locate it much faster. Finally, AI reduces errors by handling classification, data collection, structuring, and cataloging. 

1. PTC with ThingWorx Navigate

ThingWorx Navigate gives quick and easy access to product lifecycle management (PLM) data such as documents, process plans, drawings, and change requests and notices. It provides ready access to such data via a simple interface, helping users spend less time searching for data.

AI and the Future of the CAD Industry

Increased Adoption of AI in CAD Industry

The future of AI in the CAD industry looks bright, with companies hinting at new AI-driven products. For instance, Ansys, a software company that has created the Ansys engineering simulation software, is currently exploring how it can use AI to improve the accuracy and speed of simulations while making the associated workflow both robust and easy to use. 

Similarly, in a late 2022 interview, Graphisoft CEO Huw Roberts hinted at initiatives that will leverage AI. As a subsidiary of Nemetschek Group, Graphisoft is exploring whether to use AI natively on its ArchiCAD software or connect the software to APIs, enabling it to harness the power of AI through the cloud.

But while Graphisoft and Ansys have yet to provide concrete timelines, Dassault Systèmes has, and its prospects are nothing short of exciting. Starting July 1, 2023, according to a presentation by Board Chair and CEO Bernard Charlès during the 3DExperience World 2023 convention, users will enjoy even more AI-powered capabilities on the company’s 3DExperience platform. 

For instance, the updated platform will boast better generative designs. It will automatically regenerate the specs of designs created using CAD software and recreate the best possible design, enabling users to reassess and elevate the quality of a design. It will also regenerate designs from scans, with the regenerated design featuring specs that are as close to the scans’ as possible. In this regard, it will save time as it will not require users to manually create the designs. More details will, of course, be made available as the launch nears.

Indeed, these solutions are bound to make AI more available, with the associated impacts being undeniably widespread in the future. For instance, more designers and engineers will get to enjoy more productivity and efficiency, reduced costs and errors, better and more efficient designs, and more optimized manufacturing processes. 

Challenges, Risks, and Concerns

But as AI becomes even more widespread, so too are concerns around the following:

•  Ethics: AI models have to be trained using data. However, the source of that data may pose ethical questions. For instance, is the data sourced appropriately from the copyright owners?
• Algorithmic bias: AI is only as good as the training data used. Thus, if that data is biased, the AI-driven solution will also have some bias. In the context of CAD, it can lead to the generation of designs that only favor certain conditions while ignoring others.
• Privacy concerns: AI computer systems collect and process huge volumes of data. As such, there is always a risk that the data might be mishandled due to a data breach or intentional data leaks. What happens then when the data leak includes designs of sensitive projects or those that constitute trade secrets? 
• Misuse: AI empowers even less experienced CAD users to create robust designs. If such solutions land in the hands of individuals with malicious intent, they can develop products that cause harm.

Conclusion

Artificial intelligence plays a crucial role in the CAD space. It is used to generate designs, improve the quality and speed of simulations, mitigate risks, promote safety, and optimize manufacturing processes. Moving forward, CAD developers are likely to integrate AI into more of their solutions, making the technology available to more users. At the same time, however, it is important to be mindful that AI is not always positive. It has inherent risks and challenges. These include ethical questions, privacy concerns, risk of misuse, and bias. 

What is Parametric Modeling?

Parametric modeling is a design paradigm that involves stipulating dimensions that define the geometry of a part and subsequently establishing and outlining the relations between the dimensions both across and within the part. Thus, the entire model will be automatically modified or rebuilt whenever one or more dimension values are changed. This captures the design intent. After all, all the dimensions have a predefined relationship. 

Generally, the design intent in parametric modeling is captured by:

• The relationship between the base block (unmodified block or parent) and any newly introduced entity (child), also known as a parent-child relationship
• Parametric relationship between dimensions
• Relations within the sketch profile (sketch relations)

This paradigm is sometimes also known as feature-based parametric modeling. This is for a good reason. You see, a conventional 3D model comprises primitive geometric entities such as curves and points and solid primitives such as cylinders, cones, spheres, boxes, and wedges. Dealing with these primitives is less desirable, especially when designing complex parts. In fact, design professionals rarely think along the lines of these primitives whenever they are creating a part. Instead, they think about features, like faces and edges, that correspond to the model’s physical entities.

How Parametric Modeling Works

Figure 1: Parametric Modeling Example (source)

To better understand how parametric modeling works, let us consider figure 1 above. A designer wants the hole in the block shown (figure 1a) to remain centered even when the length of the block changes. To capture this design intent, the engineer must create a sketch profile of the block (figure 1b) with dimension d2 as the design variable.

Next, the hole must then be placed on the sketch profile, as shown in figure 1c. This time, however, the designer must specify the relationship between the center of the hole and dimension d2. Given the hole must remain centered even if the length is changed, the following relation must be stipulated, d1 (distance of the center of the hole from one edge) should be equal to half d2. Again, this can be simplified as d1 = 0.5d2.

Based on the discussion above, parametric modeling is also known as procedural modeling, history-based parametric modeling, or unidirectional modeling. This is because for d1 to be defined, d2 must be defined first. Thus, d1 is dependent on d2. As a result, the solution to the equation must be done sequentially. 

Generally, parametric modeling requires design professionals to anticipate design changes (think ahead) and consequently define features with this in mind. It also mandates them to add parametric relations to sketch profiles. To boost this process, the software creates a history tree that contains all the sequences of features or changes generated by the user using the predefined relations. In addition, it stores data associated with any modification to the geometry. 

Benefits of Parametric Modeling

The advantages of parametric modeling include the following:

1. It enables design automation because every aspect of the design is stored in a history tree
2. Parametric modeling promotes and simplifies the creation of family-driven or platform-based products, e.g., shelves or tools that vary in size but are based on the same platform

Disadvantages of Parametric Modeling

The disadvantages of parametric modeling include:

1. Capturing design intent in complex models is not always straightforward as it requires considerable effort from the designer, planning, and careful implementation
2. Parametric modeling tools are difficult to use
3. The parametric design process can be slow
4. Parametric modeling is not flexible, as the designer must always consider the relations between dimensions
5. It requires a steep learning curve
6. A model created in software A cannot be opened or used in software B because the importation does not include the history tree
7. Models can become disorganized if the designer does not follow a logical sequence 
8. The computation required to regenerate the model increases as the number of features in the history tree grows, which can slow down the workflow

Parametric Modeling Software

Parametric modeling is popular and has been implemented in equal measure by developers of most of the 3D modeling software in the market. From Onshape, CATIA, FreeCAD, and SolidWorks to PTC Creo, Siemens NX, Solid Edge, and Autodesk Inventor. 

1.     Creo Design and Creo Parametric

PTC Creo was the first to market with parametric modeling capabilities when it launched as Pro/Engineer back in 1988. In 2011, PTC Inc. renamed Pro/Engineer to Creo and created different software products. What came of the rebrand were, among others, Creo Parametric, Creo Design, and, as we will discuss below, Creo Direct.

Creo Design is a powerful, all-encompassing software with industry-standard 3D CAD capabilities. These include parametric modeling and surfacing, 3D part and assembly design, sheet metal design, additive manufacturing, augmented reality, mechanism design, and automatic 2D drawing creation, just to mention a few. 

On the other hand, Creo Parametric is an advanced 3D modeling software with capabilities like additive manufacturing, generative design, augmented reality, smart connected design, model-based definition, and more. In addition to offering parametric modeling capabilities, it supports direct modeling to a certain degree. As highlighted below, it is an example of a hybrid system. 

2.     SolidWorks

SolidWorks’ parametric modeling allows users to define parameters for a 3D model within a history or feature tree known as FeatureManager Design Tree. Generally, SolidWorks then automatically enters these parameters into equations that it then uses to represent mathematical relationships between two or more dimensions in assemblies or parts. The relationships between dimensions can also be defined using dimension names and measurements, other equations, mathematical functions, and file properties.

3.     CATIA

CATIA offers parametric modeling capabilities through a number of options. The first, which is parametric modeling using CATIA V5, works by automatically creating intrinsic parameters as the user creates geometries and features. Alternatively, the user can create user-defined parameters that then control the dimensions. In addition, the software allows users to utilize formulas to define relationships between parameters and geometries. 

In addition, the parameters can be defined in a CATIA design table, creating different configurations of the same model. For instance, if a model calls for five cylinders with different thicknesses and diameters, the design table is created, and all these measurements are entered. Thereafter, whenever a given configuration is selected, CATIA generates a variation of the cylinder. 

Secondly, users can use CATIA | SFE CONCEPT, which allows for the implicit creation and modification of parametric surface models. Others include the ParaMagic plugin for CATIA’s MagicDraw product. 

4.     Autodesk Inventor

Autodesk Inventor’s parametric modeling captures the design intent in history trees that stores all features as well as Boolean relations between them. The tree also includes the various steps the user took to create the model. As a result, previous features and definitions of the model can be used to regenerate the model whenever a new entity is added. 

Furthermore, whenever a user creates a dimension, Inventor automatically regards it as a parameter for the model. The parameters can be used in equations to create new parameters. To put it simply, Inventor uses parametric equations to define the relationships between parameters.

5.     Onshape

Onshape is available as a software-as-a-service, accessible via a web browser. This means you must have an internet connection to use the software. Though the software is a relatively new entrant in the CAD space, having launched in the early 2010s, it still packs a punch. Over the years, the developer has fundamentally improved parametric modeling within the software. 

Parametric modeling with Onshape allows users to create multiple parts within a single design space. This means common features and inter-part relationships are built in one place. As a result, these parts share the same parametric history, meaning the users do not have to import or open other files whenever they wish to add the parts to an assembly. 

Additionally, like SolidWorks, Onshape allows users to create different configurations of the same product. Furthermore, being a cloud-based app, Onshape allows modelers to create in-context relationships without worrying about the complexity of updating a part relative to an out-of-date assembly. The software achieves this through robust database architecture that updates all related files.

More on this in our discussion of the best parametric modeling software products today.

While parametric modeling is as powerful as it is popular and mainstream, it still competes with the relatively newer direct modeling technique for the attention of many a design professional. 

What is Direct Modeling?

Direct modeling involves the creation of a model by simply manipulating its geometry. Generally, it is based on how the boundaries, namely the faces, edges, and other features, define or represent the model. As such, all the design professional has to do is pull or push these boundary elements to achieve a given shape, akin to working with clay. However, this time, instead of using hands to mold the clay, the designer just clicks the mouse cursor and moves the geometry as they wish.

In direct modeling, the 3D modeling software does not store the sequence of features or geometry creation. This means this modeling paradigm does not involve the creation of a history tree. Additionally, the designer does not have to define constraints, use parameters to represent the design intent, or provide feature-based information. Overall, the lack of these attributes makes direct modeling faster. This subsequently increases productivity and reduces development costs and design times. In fact, designers can easily use direct modeling to edit, modify, and repurpose solid models, something that is not possible with parametric modeling.

Advantages of Direct Modeling

The advantages of direct modeling are:

1. A user can cut and paste elements from an existing design and begin building an entirely new model
2. Direct modeling is intuitive and easy to learn
3. It is easy to use as it eliminates the need to understand all constraints, meaning it simplifies the process of creating and modifying simple geometries
4. This design paradigm promotes rapid iteration and prototyping as the designs can be altered easily
5. Direct modeling saves time and money
6. It boosts productivity
7. It protects CAD models, which are assets to companies, by allowing designers to change a model without worrying about breaking it
8. Direct modeling is ideal for one-off designs
9. It simplifies the process of making unexpected or late changes in the design process
10. It exhibits greater interoperability because files can be exported and imported from one software to another without loss of design information

Disadvantages of Direct Modeling

Direct modeling is disadvantageous in the following ways:

1. It is sometimes unpredictable because editing the dimensions does not always yield a predictable result
2. Direct modeling is relatively newer than parametric modeling, meaning most experienced CAD modelers are not used to it

Direct Modeling Software

1.     Creo Direct

Like Creo Parametric above, Creo Direct is a dedicated direct modeling software. As a standalone software that is only meant for direct modeling, it is easy to use, intuitive, and flexible. It enables users to achieve faster design cycles, especially because it can allow more users to access and use the 3D CAD data. Creo Direct, therefore, promotes collaboration. It is noteworthy, however, that Creo Direct uses direct modeling alongside a history tree, but it hides the tree from the user.

2.     Shapr3D

Shapr3D primarily uses direct modeling to create 3D models. It is based on Siemens’ Parasolid® geometric kernel, which underlies the workings of Solid Edge and NX. The Parasolid kernel supports a number of 3D geometric modeling techniques, one of which is direct modeling, as well as graphical and rendering support.

3.     BricsCAD

Developed by Bricsys, BricsCAD is a 2D and 3D CAD software that supports dedicated direct modeling. Do note, however, that, unlike Shapr3D, which is primarily a direct modeling software, BricsCAD also supports parametric modeling. That said, its direct modeling commands, which include rotate, chamfer, fillet, deform, stitch, thicken, and push and pull, enable the creation of both solid and surface geometry. These commands are available in various packages, including BIM, Pro, Mechanical, and Ultimate, each of which has its own BricsCAD pricing.

4.     Fusion 360

Indeed, Fusion 360 supports both parametric and direct modeling. However, it allows users to easily switch between the two by simply enabling or disabling the software’s ability to capture design history. Unlike other software products that combine parametric and direct modeling capabilities within the same space, Fusion 360 does not. Upon choosing the ‘Do not capture Design History’ option, the software shifts all workflow to the direct modeling workflow. For instance, it does not store any changes to the model in a history tree. As a result, direct modeling with Fusion 360 is fast, straightforward, and offers flexibility.

Figure 2: Autodesk Fusion 360 Preferences Dialog Box (source)

How do Parametric Modeling and Direct Modeling Compare?

In this section, we will use several design aspects to compare parametric modeling to direct modeling. The table below summarizes how these two modeling paradigms differ.

Which Modeling Method is Right for You?

You may have wondered which modeling method suits you as a design professional. To help you out, we look at several factors you should consider:

1.     Collaboration Needs

Are you part of a team wherein each modeler has their preferred software, yet you must collaborate by modifying aspects of the models? In such a case, direct modeling should be your go-to paradigm. Given that it does not involve the use of history trees to capture the design intent, this paradigm promotes interoperability. Thus, a model created and saved using software A can be imported and modified using software B without losing vital information.

2.     Design Complexity and Sophistication

Parametric modeling is preferred when creating complex models, while direct modeling is ideal for simple, one-off designs. However, remember that the former requires greater planning and effort to create a parametric model. 

3.   Learning Curve

If you are a beginner, we recommend choosing direct modeling. This is because it is easy to learn and use. Moreover, it is flexible and does not require considerable effort or planning to achieve a desired solid model. Thus, direct modeling is perfect for workflows that do not require modelers to dedicate a lot of resources – time and money.

4.   Ease of Use and Workflow

If you are looking for a design paradigm that will not require a lot of planning; one that is straightforward and a tad simplistic, consider the direct modeling paradigm. However, if you prefer dedicating a lot of effort into understanding your model before you can even begin the modeling process, parametric modeling is exactly what you are looking for. It enables you to capture your design intent and define relationships between dimensions and other parameters.

5.     Level of Design Iteration and Changes

If you foresee that the model will undergo a lot of changes throughout the design process and may be worked on by new modelers, consider choosing direct modeling. This will simplify the updates by eliminating the need to understand the history tree. On the other hand, if the design iterations will be minimal, consider using parametric modeling.

Hybrid Systems

From the discussion above, it is clear that direct modeling is more advantageous than parametric modeling. But this does not mean that the latter does not have its own strengths. In recognizing the strengths of each of these modeling paradigms, software developers such as Dassault Systèmes, PTC Inc., and Autodesk are, in fact, increasingly creating hybrid systems that merge the capabilities of the history-based modeling approach with the direct modeling approach. This has resulted in the varied implementation of the paradigms. Such software can help you, especially if you are undecided on what to choose between parametric and direct modeling.

Examples of hybrid systems include:

1.     Siemens NX and Solid Edge

Siemens NX and Solid Edge enable users to change the geometry of models by moving the mouse or editing the dimensions. The software then preserves the design intent using a unique technology known as synchronous technology, which is nothing similar to the history tree. This way, these applications sidestep the problems that arise whenever software developers implement direct modeling as part of a history tree. Thus, a designer can modify complex 3D models without knowing the relationships and dependencies or how the model was initially constructed.

2.     SolidWorks

SolidWorks includes intelligent features that convert non-native imported geometry into intelligent native features that can then be manipulated directly or parametrically. The former can be accomplished using built-in direct modeling tools aptly named Direct Model Editing. However, unlike Creo Direct, which is primarily dedicated to direct modeling, SolidWorks’ tool is simply a feature-based parametric modeling tool. This tool lets users perform direct editing using such functions as drag, push, copy, split, replace, offset, and more. The software then adds the edited features to a model tree. 

3.     Autodesk Inventor

Autodesk Inventor is primarily a parametric software. Still, it allows users to use direct modeling techniques to scale, resize, rotate, delete, and move geometries. It is noteworthy, however, that this paradigm is mostly used with imported geometries rather than native ones. Autodesk incorporates direct modeling into Inventor to help modelers make edits fast. Users can use the drag handles or the dynamic input to make the changes regardless of the complexity of the part or assembly. In this way, Inventor promotes collaboration.

4.     CATIA

CATIA uses a free modeling approach. Although this approach looks similar to direct modeling, it takes a declarative route, with the modeler required to declare the specification to promote precision and capture the design intent. Other than that, CATIA’s system is similar to SolidWorks.

Conclusion

Parametric modeling is a paradigm that requires a modeler to use relationships between features and dimensions to capture their design intent. It mandates the dedication of effort and time to create just a single model. On the other hand, direct modeling uses a push-and-pull approach to building and editing models. It is simple, easy to use and learn, and saves time and money. Over the years, however, software developers have merged the capabilities of both paradigms to create hybrid systems. Still, parametric modeling and direct modeling can exist in isolation, begging the question: which should you use? This article has detailed four factors you should consider when choosing between the two paradigms.

That said, we recommend practicing with each of these paradigms to determine what tickles your fancy. Indeed, if you are a seasoned modeler, you will likely go with parametric modeling. But this does not mean you cannot apply direct modeling in certain aspects of your workflow. In fact, you will likely appreciate the additional advantages of the latter, which can draw you even closer to this relatively newer modeling approach. The same goes for modelers who are not used to parametric modeling. By giving it a try, you might realize it is not as complicated as many set it out to be. This can be particularly true if you use software with which you already have experience.

We covered several big developments over the last few weeks, including how PTC’s Vuforia Spatial Toolbox is being used to speed up the development of robotics interface; MSC’s unique business model which lets engineers innovate remotely anytime even during the COVID-19 pandemic; and Dassault Systemes’ revenue reports and forecast.

Other stories we followed include how BIM reviews are using virtual reality nowadays; the transformation of low-cost printers into high-tech output producers; and the effect of the coronavirus pandemic on the architects of the world.

There’s so much interesting things to read about in this edition of our news round-up, so let’s get things started!

PTC’s Vuforia Spatial Toolbox Designed to Speed Up Robotics Interface Development

PTC Reality Lab has released its open-source platform called Vuforia Spatial Toolbox which is intended to let developers solve various spatial computing problems in a much more efficient way.

PTC’s announcement said, “Innovators and academic researchers can explore the power of Industrial Internet of Things [IIoT] and spatial computing, accelerate prototyping for machines, and develop leading-edge spatial augmented reality (AR) and IoT use cases to support digital transformation initiatives.”

According to PTC, this spatial computing platform can assist team in improving the operation of complex manufacturing environments and also grant easier control to IoT-enabled machines as far as on-the-fly programming. Developers can utilize the Vuforia Spatial Toolbox to create intuitive user interfaces that control and operate robots, and also allow them to build interfaces that improve the interaction between humans and machines.

Mike Campbell, executive vice president and general manager of augmented reality for PTC, said, “Many developers, innovators, and researchers recognize that AR can help democratize the programming and control of connected machines. What they need are solutions that help alleviate development overhead for prototyping these innovative, next-gen AR tools. PTC is helping them develop tools and interfaces to spatially interact with and program the world of interconnected things around them.”

CAE Leader MSC Changes Business Model So Engineers Can Work Remotely During COVID-19

MSC Software Corporation (MSC), one of the world’s leaders in the Computer-Aided Engineering (CAE) simulation software and services, has recently announced that it will give customers free offline licensing and remote access options to allow them to remain productive, especially while working from home during the COVID-19 pandemic.

Roger Assaker, Chief Customer Engagement Officer for MSC Software, announced, “We are adapting to the needs of our customers, and are also adding a helping hand to support their business continuity so they can continue to design, engineer and perform virtual testing outside their place of work. We are facilitating the access to our software, knowledge base and support to enable the creation of even more value with our tools, helping companies to maintain productivity and innovation when many manufacturing lines are down.”

He added, “We appreciate that these are very challenging times for many of our customers, and we can guarantee that we will be supporting them to the best of our ability, every step of the way.”

Some of the offerings from MSC Software specific to this season of pandemic lockdowns include extension of licenses for work-from-home support or alternative access options for MSC Software CAE solutions, and free access to online learning resources for MSC Software products.

The manufacturing industry has always found remote work particularly challenging because many of its tools and system processes still revolve around old-fashioned workflows. As more and more companies are forced to find ways to work remotely, CAE and simulation tools are particularly useful in the migration.

Dassault Systemes Revenue Forecasts Lower Than Expected

Dassault Systemes SE announced on Wednesday that revenues for the first quarter of the year should grow 14% to 17%, based on preliminary data. This is lower than originally expected by Dassault, or about 2.5% to 5% lower than original projections because of lower new license revenue and services activity.

Still, Dassault stated that recurring software revenue, which makes up about 84% of its software revenue for the quarter, was still relatively in line with initial guidance and was the main driver of growth for this time period, mainly because of the good performance of its recent acquisition Medidata.

Other stories we followed this month:

• Firms all over the world are offering or utilizing BIM-enabled virtual reality setups during the pandemic.
• The United States Army has a new multi-polymer filament for desktop 3D printers, turning these printers into high-tech producers.
• Architects are finding creative ways to cope with the COVID-19 pandemic and prepare for the future as the industry also grapples with the global situation.

Some of the stories we thought you should not miss include the STEM challenge initiated by several engineering groups designed for pupils who are currently staying at home due to COVID-19 lockdowns; how BLOX is building hospitals in an Alabama facility to be sent to sites all over the United States; and how AI is being used along with radiology technologies in China in the continued fight versus COVID-19.

Additional stories we covered include Dassault Systemes’ efforts to produce a virtual of the human body; and how Autodesk has been recognized as one of the world’s most innovative companies in 2020.

This edition of Coffee Break News is packed with information, so let’s get right to it!

Great Exhibition at Home Challenge launched for UK students

With so many students worldwide currently unable to attend their classes due to lockdown and stay-at-home orders in place, educators and other concerned groups are coming up with innovative ways to keep students learning at home. The Royal Academy of Engineering and Big Ideas have collaborated on the “Great Exhibition at Home” challenge designed to encourage students to continue their STEM learning activities.

Taking inspiration from the Great Exhibition of 1851, the Great Exhibition at Home Challenge encourages learners to come up with various ideas for how engineers can use their skills and knowledge in protecting the planet.

Dr. Virginia Crompton, CEO of Big Ideas, said, “Our every day lives may have changed beyond recognition, but that’s all the more reason to offer engaging and meaningful content for young people, especially as schools are closing.”

This challenge has been formatted to be done in both the classroom and the home, for primary and secondary learners, and can be done alone or with a group. Students in the UK who will be participating in this challenge will join a seven-week project which will culminate in a video.

Dr Hayaatun Sillem CBE, CEO of the Royal Academy of Engineering, explained, “Young people are natural engineers – creative, problem solving, adaptable. This is an amazing opportunity for them to think about how they might use engineering to help protect the planet and showcase their ideas, in the style of the famous Great Exhibition of 1851.”

BLOX using BIM, digitization to build hospitals and structures

Construction firm BLOX is using a manufacturing-forward approach to design and build structures with the efficiency and productivity level of a factory assembly line, utilizing BIM and digital workflow processes. Termed industrialized construction, this process brings together practices from different industries to enhance innovation and speed up the overall process.

BLOX is the brainchild of designer Chris Giattina, who drew inspiration from the practices in the automotive and aircraft manufacturing industries, including manufacturing their complex products using a series of prefabricated assembly lines.

From this concept, the team at BLOX came up with a modular method that Giattina called the Design Manufacture Construct (DMC). In this process, buildings are designed as a series of pre-assembled parts, then shipped and assembled at the building site itself, this cutting traditional construction times.

This DMC process is presently being applied for several hospital building projects across the United States. BLOX says using DMC, it can build up to 15 projects every year. “You can make a whole building in about three weeks and just keep them coming,” according to Giattina.

AI-assisted radiology technologies help in the fight against COVID-19 in China

Artificial intelligence has played a vital part alongside radiology technologies in the continued effort to stem the COVID-19 pandemic, particularly in mainland China. In particular, computed tomography medical imaging is being used to detect abnormalities in the patients’ lungs. Radiological features of COVID-19 were included as one of the determining clinical manifestations to confirm that a suspected patient of COVID-19 does have the virus. CT images were enhanced with artificial intelligence (AI) algorithms that quickly triage patients to radiomic COVID-19 image signatures.

Through the use of AI, radiological reviews and diagnoses of COVID-19 patients have become faster, while also increasing the workload for radiologists and physicians. Another advantage of AI is allowing the radiologist or technician to guide the patient through the examination process completely contact-free, thus protecting the medical practitioner while also saving the consumption of personal protection equipment (PPE) which otherwise must be worn.

Other stories we followed this month:

• Dassault Systemes is pledging to come through with its plans of creating a virtual twin of the human body via its 3DExperience platform, in line with the company’s vision of helping to cure patients and expanding life spans.

• Fast Company has included Autodesk in its annual list of the World’s Most Innovative Companies for 2020, along with other companies reflecting the resilience and optimism of various industries despite global volatility.

Other newsbits we checked out for this month include the use of 3D printing for producing safer helmet padding; how machine software can help in reducing waster from 3D printing; and the release of the world’s first fossil-free crib from Vattenfall.

There is so much to explore in this month’s Coffee Break News, so let’s go straight into it.

Dassault Systemes and Xometry Partner Up For Instant Parts Production

Dassault Systemes and Xometry are teaming up to provide their customers with a seamless and integrated way to produce parts in the manufacturing process. Engineers who utilize SolidWorks and Catia will have access to Xometry price quotes via the MAKE Marketplace for manufacturing parts without having to exit their design environment, thus allowing them to have a greater role in not only the design and manufacturing aspect of parts production, but also the cost to produce it.

The partnership was announced during the 3DEXPERIENCE World 2020 in Nashville, Tennessee. With this new development, manufacturing price quotes from service providers can now be done instantaneously and in a one-click immersive experience using integration with SolidWorks and Catia, rather than having to go to a separate web interface that requires more clicks. Engineers will have access to Xometry price quotes in their design context, with the option to get manual or instant quotes from MAKE Marketplace suppliers.

Sebastian Massart, head of corporate strategy for Dassault Systemes, said, “We launched the MAKE Marketplace in 2018 to make it easy for customers to design and manufacture. Our partnership with Xometry takes this a step further. Customers can order high-quality additive manufacturing or CNC machining parts in one click at the right price, thanks to Xometry instant quoting capabilities. This is all part of our vision to continuously reduce the friction that customers face going from design to manufacturing.”

The partnership positions Xometry as the first “prime partner” of Dassault Systemes’ MAKE Marketplace. Randy Altschuler, CEO of Xometry, said, “Engineers need the right tools to do their job successfully, and this includes working with a responsive, trusted manufacturing partner. As the leader in 3D printing and on-demand manufacturing, we have served many customers in the MAKE Marketplace since its launch. Through our deeper partnership with Dassault Systèmes, we can directly connect with customers and make a commitment to provide a quote on every customer query. It’s all about faster manufacturing.”

Augmented Reality is Increasing Workforce Productivity in Manufacturing

The advent of augmented reality (AR), specifically the integration of high bandwidth, imaging technologies, and digitized information, has paved the way for a powerful new tool that increases industrial workforce productivity, thus becoming an advantage for assemblers, operators, and technicians.

This is the subject of an article by Tim Shinbara, CTO and vice president of manufacturing technology of the Association of Manufacturing Technology, published on MachineDesign.com, which talks about how augmented reality has allowed information, data, images, experience, and skills that workers can access easily and in real-time via their smartphones, tablets, or other smart devices has increased worker productivity and sped up the manufacturing process.

Amar Dhaliwal, CEO of Atheer Inc., said, “Augmented reality offers the promise of providing every member of the industrial workforce with relevant, contextual and customized information and guidance from across the enterprise into their field of view in a seamless, hands-free, intuitive manner that transforms the way they work.”

Specific areas that AR has benefitted positively include: maintenance and repair (diagnostics, maintenance, and repair of production equipment); technical field support (i.e. delivering remote support from the OEM without the need for physical delivery); inspection and surveying (reduced transport costs via drones and other unattended platforms); cargo and warehouse operations (efficient actions and applications through AR instead of paper printouts); and training and compliance (such as remote workforce training).

AR is expected to continue to grow quickly, with PwC estimating that up to 14 million workers will be wearing smart glasses by 2025, from just 400,000 in 2016. Dhaliwal said, “We have found that the manufacturing market still has a few misconceptions about AR, but when customers see that the applications of AR are extremely practical and straightforward, they understand how it can potentially benefit them. They often look for opportunities where the technology is likely to provide a step level change in their business, something with a 10 to 20% impact on ROI.”

Jon Peddie Research Releases 2020 CAD Report

Jon Peddie Research (JPR) has released its 2020 CAD Report and is predicting a CAD market that is stronger than ever and continuing to grow, boosted by digitalization and other advances in design and engineering. According to the report, the CAD market is predicted to grow 2.4% over the forecast period 2018-2022, and reach revenue of US$9 billion by 2022.

Synergies are fueling strong growth in the CAD industry, particularly customers from automotive, construction, aeronautic, machine design, power, and process industries. These customers are rapidly adopting systems design and technological developments now accessible in the CAD market.

Analyst Kathleen Maher explains, “The leading CAD companies are finding room to forge their way in specialized markets as world industries transform their workflows via digitalization. The transition to 3D workflows is enabling CAD customers to build digital twins to test and model designs before they are built and monitor them in operation.”

The JPR report concentrates on 10 market leaders in the CAD industry, including Autodesk, Dassault, PTC, Siemens Digital Industries, Aveva, and Hexagon, and also collates data from 36 other CAD companies.

Other stories we checked out this month:

• 3D printing is now being used to create safer padding for helmets by a team from the US Army Combat Capabilities Development Command’s Army Research Laboratory and its HRL Laboratories partners.

• Researchers from USC Viterbi School of Engineering in California claim that machine learning algorithms and PrintFixer software are helping to increase accuracy and reduce waste in 3D printing.

• Vattenfall has announced the world’s first fossil-free crib, created without the use of any gas, oil, or coal, and it only cost $28,885 to build.

This month’s Coffee Break News is loaded with so much important information we thought you should not miss. Stories we covered include a timely reminder on how the world can get back on track in meeting its 2030 Sustainable Development Goals; the launch of IronCAD’s Design Collaboration Suite 2020; and the development of a soft polymer material by a group of researchers at Georgia Institute of Technology introduction of the Carbon Fiber 3D printer by Desktop Metal.

Additional stories we are featuring in this edition of the news round-up include the introduction of the Carbon Fiber 3D printer by Desktop Metal; the results of the House Challenge 2019 with the Desert House theme; and Phase Four’s launch of a new electric propulsion system using Xometry’s platform.

There’s a lot to read about so let’s get right into it!

Nature.com publishes editorial on 2030 Sustainable Development Goals

A timely editorial put out by Nature.com seeks to call the attention of all stakeholders and leaders on how the world can get back on track to meet its 2030 Sustainable Development Goals. It should be remembered that back in 2015, world leaders met at a summit in New York organized by the United Nations with the aim of ending poverty, stopping environmental destruction, and improving the overall well-being of the global population. The world leaders signed on to the SDGs, a package of 17 different goals which include the eradication of hunger and extreme poverty, reducing economic inequality, taking steps to manage climate change, ending the loss of important ecosystems and biodiversity, and other targets, all within the 2030 timeframe.

According to the editorial, the world is poised to miss most of the goals as set forth in the 2015 agreement. “Just two of them — eliminating preventable deaths among newborns and under-fives, and getting children into primary schools — are closest among all the goals to being achieved. By contrast, the goal to eliminate extreme poverty will not be met because some 430 million people are expected still to be living in such conditions in 2030,” according to the article.

Particular areas of concern are climate change and environmental protection. “Targets to end hunger and to protect climate and biodiversity are completely off track. Whereas some of the richer countries are making a degree of progress in the SDGs overall, two-thirds of poorer ones are not expected to meet those that relate even to their most basic needs,” the editorial points out.

The editorial asserts that in order for the world to get back on track to meet these goals, international compliance needs to be stepped up. “To be achieved, the SDGs need to become mandatory — not necessarily in the legal sense, but in the sense that nations have to know that there’s no alternative but to make them happen,” the article reads.

Design Collaboration Suite 2020 by IronCAD Out Now

IronCAD, a popular 3D CAD platform in the metal fabrication and custom machine manufacturing industries, has launched IRONCAD 2020. The newly-unveiled Design Collaboration Suite was designed to enhance productivity for software users who need to get their products out in the market at a faster rate, while also improving performance and design functionality.

IronCAD relied on user feedback to focus on areas that needed enhancement in its 2020 release, and key improvements were centered on large assembly performance, streamlined workflows, and better design presentation and communication. “This year’s release, the main focus was on improving the ICD (IronCAD Drawing Environment) to increase productivity. With this in mind, our goal was to improve the 3D to 2D detailing process to reduce the design to manufacturing timing with better performance, improved commands, better accessibility to common commands, faster drawing creation with our automated bulk view creation tool that enable users to go from concept to manufactured products faster,” IronCAD’s official press release said.

Cary O’Connor, Vice President of Marketing for IronCAD, said, “Expanding on our recent 20th year release capabilities, IronCAD 2020 gains a significant leap in the ability to work and manage large assembly files commonly used among our custom machinery manufacturers. Users will feel improvements to the performance while working in 3D all the way through to the final production drawing output with the many improvements developed in the IronCAD Drawing Environment to speed up and aid the detailing process.”

Researchers develop soft polymer material using magnetic fields

A combined group of researchers from the Georgia Institute of Technology and Ohio State University has been able to develop a soft polymer material that uses magnetic fields to transform into different shapes. The material, called magnetic shape memory polymer, could usher in new possibilities in various applications and manufacturing purposes.

The new material was developed from a mixture of two types of magnetic particles, one for inductive heat and the other for strong magnetic attraction, as well as shape-memory polymers for locking shape changes into place.

Jerry Qi, a professor at Georgia Tech’s George W. Woodruff School of Mechanical Engineering, said, “This is the first material that combines the strengths of all of these individual components into a single system capable of rapid and reprogrammable shape changes that are lockable and reversible.”

He added, “We envision this material being useful for situations where a robotic arm would need to lift a very delicate object without damaging it, such as in the food industry or for chemical or biomedical applications.”

Other stories we followed this month:

• Desktop Metal has introduced its Carbon Fiber 3D printer, already its third 3D printing platform.

• The results of House Challenge 2019 competition with the Desert House theme have been released, and applicants came up with some very exciting concepts for temporary houses compatible with the harsh desert environment.

• Space propulsion startup company Phase Four utilized Xometry in developing a new electric propulsion system that is more cost-efficient, thus better equipped for the mass production of satellites.

Other stories we looked at this month include a focus on how quickly multi-material 3D printing is able to manufacture complex objects; the use of defect-detecting drones at Wembley Park to see structural issues; and how the Thanksgiving holiday in the US has become a high-tech event.

These stories are definitely worth checking out, so let’s get right to them!

Rwanda’s progressive architecture for the future

Transformation has become evident throughout the country of Rwanda, a country that is rebuilding after more than two decades of civil war and other tragedies. Contemporary architecture has become a symbol of the ongoing economic and societal reforms throughout the country.

Rwanda is one of the smallest countries in the continent of Africa, yet it has one of the fastest-growing economies globally. With a predominantly rural population, Rwanda’s cities are undergoing transformation through an organized series of initiatives and beautification campaigns started by the government.

The shift in architecture started when people began to reside in the cities of Rwanda during the 1980s. Development was adjusted to the country’s geography and varied landscapes. For instance, the Bisate Lodge by Nicholas Plewman Architects reflects Rwanda’s organic culture and rolling hills, with its spherical rooms and lush foliage.

Another structure, the Rwanda Cricket Stadium, was a project of Light Earth Designs and was built using local construction techniques, thus avoiding having to import materials, while also lowering carbon emissions and supporting the local economy. The cricket stadium’s main enclosure was inspired by Mediterranean tile-vaulting, with geogrid reinforcing. The vaults of the cricket stadium follow the natural resolution of forces, thus looking like the hillside views of Rwanda.

Holographic beam shaping is enhancing additive manufacturing

A team from Cambridge University’s engineering department, with funding from EPSRC, is launching a three-year research program that will utilize computer-generated holography to control the laser’s energy distribution in three dimensions.

Tim Wilkinson, professor of photonic engineering and the project leader, explained, “Rather than using a single beam with a scanning mirror, we can use multiple beams at the same time. We can build up our structure in a more three-dimensional way, which allows us to control things like thermal stresses.”

Currently, one of the disadvantages of the process is the difficulty of predicting or controlling the intense heat at the focus of the laser. This fuses the metallic powder in additive manufacturing and causes thermal stress or distortion in the part being manufactured. The holographic approach, however, can correct for limitations.

According to Wilkinson, the hologram can be changed hundreds or thousands of times per second for energy distribution, and there are algorithms that can be utilized to correct for material properties, optical aberrations, and other aspects.

“The holographic approach allows us to make things which were impossible before. There are certain structures you can’t make because of the thermal stresses,” Wilkinson said.

Eviation completes prototype of zero-emission electric aircraft

Electric air mobility pioneer Eviation Aircraft has completed the first prototype of a zero-emission, fully-electric regional commuter aircraft called Alice. The electric air mobility company used Dassault Systemes’ 3DEXPERIENCE cloud platform to develop the prototype.

Omer Bar-Yohay, CEO of Eviation Aircraft, said, “The electrification of aircraft isn’t a question of if, but when. As we aim to make clean regional air travel accessible for all, we needed to be able to make a product that people trust, sit in and fly, and do it quickly.”

With regard to their choice of using the 3DExperience platform, Bar-Yohay explained, “he right way to go about it was to use tools that we would want to use in the long run, and to work in the cloud to ensure fast, secure access and global collaboration. When we selected the 3DEXPERIENCE platform, we were an early stage startup with limited resources and time. We’ve developed our commercial-stage prototype faster than we imagined, and have already signed our first customer in the U.S.”

Once the Alice prototype is commercialized, it will be the first all-electric regional commuter airplane in the world, with the capability of carrying nine passengers and two crew members for 650 miles, flying at 10,000 feet and with a single charge.

Dassault Systemes’ David Ziegler, the Vice President for Aerospace and Defense Industry, commented, “Dassault Systèmes works with companies of all sizes, including new companies like Eviation Aircraft that participate in a true Aerospace Renaissance, changing the way the world travels and commutes. The 3DEXPERIENCE platform delivers solutions tailored for these innovators to implement new ways to conceptualize, design, manufacture, test, certify and operate their programs.”

More stories we followed this month:

• With a new method called multimaterial multinozzle 3D that allows 3D printing with up to 8 different inks at up to 50 times per second, 3D printing becomes faster and easier.

• A fleet of drones will be used by contractor John Sisk and Son to conduct quality checks on the external structure of PRP’s tower projects at Wembley Park.

• Technology has now taken over Thanksgiving as well, as 3D printing and IoT devices are now being used in cooking and preparing Thanksgiving dishes in the US.

Other stories we are serving up in this roundup include the successful 3D printing of a miniature human heart by US scientists, the support of New York’s designers and architects in the recent Global Climate Strike, and Fieldwire raising the stakes in its bid to compete with PlanGrid.

Enjoy reading this month’s news lineup! 

AutoDesk and ANSYS’ automotive Partnership

Major software names Autodesk and ANSYS have recently announced that they are collaborating in a new partnership that is geared towards the automotive industry. This collaboration will feature the integration of Autodesk’s automotive visualization and prototyping application VRED with ANSYS’s lighting simulation tools. 

Autodesk’s Thomas Heermann explained, “VRED is the leading-edge, industry-standard 3D visualization and digital decision-making tool in the automotive design studio. With the ANSYS collaboration, we can offer an integrated workflow—merging physics-based simulated optical ray files with complex and dynamic lighting scenarios directly into VRED.”

According to the two firms, this integration will allow automotive designers to produce photorealistic visual representations of vehicles they are working on, and this will, in turn, improve workflows and accuracies in physical reflections. 

For their part, ANSYS’s Eric Bantegnie said, “We are excited to collaborate with Autodesk to bring automakers our gold-standard lighting simulation. This collaboration represents a win-win scenario for both companies—but more importantly, for our joint customers who are looking to rapidly take advantage of industry megatrends like next-generation autonomous driving and electrification.”

UK and Korea collaborating on space battery designs

The UK’s Leicester University and National Nuclear Laboratory are teaming up with the Korea Atomic Energy Research Institute in designing space batteries. The organizations announced their agreement which will focus on combining research on radioisotope thermoelectric power generators for utilization in space explorations. These technologies are designed to power space missions that probe distant, cold, dark environments in space. 

Aside from the cooperation on research and development, the partners will also develop international standards and safety protocols that are associated with these systems. 

Leicester University and National Nuclear Laboratory are part of a European Space Agency program which is developing radioisotope generators and heater units. According to Prof. Iain Gillespie, the pro-vice-chancellor of research and engineering for Leicester University, said, “Missions using nuclear power offer greater versatility in challenging environments. In many cases nuclear systems can enable missions that would otherwise be impossible.”

Meanwhile, Dr. Young Uk Jeong, the senior vice president for quantum science convergence for Korea Atomic Energy Research Institute or KAERI, said, “This memorandum of understanding will provide our respective countries with opportunities to pursue new avenues of collaboration and to discuss ways of increasing substantive cooperation in space nuclear power systems.”

Dassault joins AMRC

Dassault Systemes has officially joined the University of Sheffield Advanced Manufacturing Research Center (AMRC). The partnership was recently announced by Dassault Systemes, the French software company that envisioned the 3DEXPERIENCE platform. The collaboration is intended to accelerate the manufacturing industry in the UK. 

Severine Trouillet, Global Affairs Director for EuroNorth at Dassault Systemes, said, “We strongly believe that we have entered the Industry Renaissance, a new era where experience will be at the heart of everything we do, from the way we innovate to the way we produce goods. The tools of the Fourth Industrial Revolution, whether automation, robotics or visualization, are the basis on which we are building a radically new world where entire sectors will be turned upside down.”

The AMRC was founded in 2001 and is the center of numerous research projects revolving around manufacturing, machining, and advanced materials. It counts over 100 partners. Recent collaborations include its hybrid 3D printing THREAD collaboration with engineers from the NASA Jet Propulsion Laboratory and its project with Toyota Motorsport GmbH to develop new lightweight automotive materials. 

Specifically, the team-up with Dassault Systems will focus on the Made Smarter initiative with UK manufacturers, with the goal of developing an open-access Smart Factory testbed where companies can enhance productivity, minimize defects, and reduce the time it takes to reach the market. 

Rab Scott, Head of Digital for AMRC, said, “With Dassault Systèmes as a Tier 1 partner, the AMRC is ideally placed to deliver the sustainable step-changes in productivity that the UK economy desperately needs. Its suite of digital technologies strengthens the AMRC’s portfolio of advanced manufacturing capabilities and puts us at the forefront of Industry 4.0 research and development.”

More stories we followed this month:

• Scientists from Chicago-based biotech company Biolife4D have successfully 3D printed a miniature human heart. This is a major step towards the goal of eventually being able to produce a full-sized human heart that is viable for transplants. The miniature heart featured the standard structure of a full-sized heart, including four internal chambers.
• Architects and designers from renowned firms in the New York City area joined the Global Climate Strike on September 20 spearheaded by 16-year-old Swedish activist Greta Thunberg. Designers and architects from Snohetta, Joe Ducet, Selldorf Architects, and Wood Bagot were among those in attendance at the event which was simultaneously held in over 150 countries to call for swift climate action.
• Fieldwire, known for its task management software for commercial construction teams, just raised an additional $33.5 million in Series C funding, led by Menlo Ventures, Brick & Mortar Ventures, Hilti Group, and Formation 8. The funding props up Fieldwire’s bid to better compete with rival PlanGrid, which was purchased last year by Autodesk for $875 million. 

This month, some stories that tickled our fancy include these proposed alternatives for keeping buildings cool aside from airconditioning; a new Reverb VR headset from HP geared towards CAD engineers; and Vectorworks’ acquisition of ConnectCAD. Other happenings we thought you should not miss include this survey indicating that employees would rather be replaced by robots than real people; the widespread use of 3D printing technology in the US military establishment; and how waste material is being converted to jet fuel on Humber Estuary.

There’s a lot to cover, so let’s get started!

Innovations in cooling buildings

Air-conditioning accounts for 10% of the world’s energy consumption, and in 2016 contributed to about 1045 metric tons of CO2 emissions worldwide. According to the International Energy Agency, by 2050 air-conditioning will reach 37% of the global total energy demand. Because of this, architects and engineers are coming up with various creative ways to keep buildings cool while reducing the need for air-conditioning. 

Popular building materials used nowadays because of their heat-insulation properties include stone, earth, and concrete. These dense materials have excellent thermal conductivity properties (for passive cooling), thermal lag (slowing down the transmission of heat), lower redistribution of heat or reflectivity, and higher volumetric heat capacity. Projects that have successfully utilized these materials include Santorini’s Summer Cave House by Kapsimalis Architects and A-cero’s Concrete House II. 

Also becoming popular is the use of green roofs, which provide shade, reduce heat from the air, lessen temperature, and also provide aesthetic appeal. Structures that utilize green roofs include the California Academy of Sciences (designed by Renzo Piano), Nanyang School of Art (designed by CPG), and Villa Bio (a project of Enric Ruiz-Geli). 

Could HP’s Reverb become a common tool for the CAD Engineer?

A new VR headset from HP, the HP Reverb, is being geared towards professionals with deeper pockets and with more demands on comfort as well as high definition sound. The HP Reverb has a $600 price tag, and it even has an enterprise version that will set you back $649. The HP Reverb is being pitted against other mainstream VR headsets: the Samsung Odyssey and the HTC Vive Pro. 

The Reverb features specs that edge out competitors: 2160×2160 resolution per eye, 114-degree field of view, 2.89-inch LCD displays over OLED, squircle-shaped view, asymmetrical Fresnel lenses, and a display of 24 to 25 pixels per degree. 

The HP Reverb also features built-in headphones, a 3.5mm headphone jack, and Bluetooth in-headset for convenient pairing. The $600 consumer version is sold with a machine-washable foam facepiece, while the $649 enterprise version has a leather facepiece. 

The initial rollout of the HP Reverb ran into some stocking and display issues, but the problems have since been resolved and HP has assured its customers that the VR headset should be available at the HP website and through their retail partners. 

Vectorworks acquires ConnectCAD

Design and BIM software solutions provider Vectorworks has acquired connectCAD, a systems design solution that caters mostly to the AV industry. connectCAD has been available since 2009 as a plugin for Vectorworks software, with functions for designing broadcast, AV, IT and lighting networks, and other connected systems. 

Vectorworks CEO Dr. Biplab Sarkar said, “connectCAD has been a great partner product for Vectorworks over the years and has gradually built a product for Vectorworks that creates a powerful, yet intuitive interface for generating audiovisual system designs and reports. In response to the growing audio needs for our customers, connectCAD was an obvious choice because it’s a high-quality product that naturally extends our AV capabilities for our users.”

With the acquisition, connectCAD’s Founder, Managing Director, and Programmer for tools Conrad Preen will commit to at least two years with Vectorworks in order to continue developing connectCAD. Top priority will be the conversion of Vectorscript tools and commands to C++ utilizing Vectorworks SDK in order to enhance the connectCAD plugin’s performance. 

Vectorworks CEO Sarkar added, “The driving force for the acquisition was to get our foot in the door of the AV installation market. This will help us not only better serve those that do AV installations, but also those involved with broadcast and systems designs. The capabilities of the Vectorworks Spotlight product—plus the capabilities we’ve added in other new modules and acquisitions—has helped us to evolve our product offering into one that is built to be a total design and production solution for the entertainment industry.”

Here are some more stories worth checking out this month:

• According to a study by the Technical University of Munich (TUM) and Rotterdam’s Erasmus University, most employees from Europe and North America would much rather be replaced in their own jobs by robots rather than other employees.
• The United States military has been actively embracing the potential of 3D printing or additive manufacturing, especially as the technology offers a powerful and efficient method of manufacturing. 
• A consortium which includes Shell and British Airways is building Europe’s very first waste-to-jet-fuel plant on the Humber Estuary, with the goal of converting up to half a million tons of household and commercial waste to jet fuel every year. 

Other stories we thought you might find interesting include: the new Joyride shoes from Nike designed to make your runs more comfortable; a knee-powered energy harvester for electronic devices; and a new probiotic clothing concept for healthy skin, activated by sweat!

There’s so much to get into in this month’s Coffee Break News, so let’s get started. 

Autodesk earmarks undisclosed investment towards prefab construction firm Factory OS

The construction firm is known for its heavy use of software in its construction of homes, thereby minimizing waste while also speeding up the process. Two years ago, Google worked with Factory OS in a $30 million project to construct short-term housing for its employees in the San Francisco Bay area. Autodesk has already partnered with Factory OS previously via its foundation arm, giving the firm free use of donated software licenses to help the startup in its initial phases. This investment, however, will be the first impact investment made by Autodesk towards Factory OS. 

Joe Speicher, executive director of Autodesk Foundation, explained, “I would argue that looking at the short-term horizon, modular construction looks to be ripe to solve some of our housing challenges. Engaging in this deeper relationship allows us to explore how we can add value.”

Autodesk and Factory OS are looking to integrate and streamline their software platforms in order to simplify design, fabrication, and supply chain management processes. The deal will also maximize Factory OS’s waste material reduction abilities in construction through the use of new digital technologies. Speicher added, “Most companies are very aware that automation and machine learning are disrupting many sectors. They are actually doing something about it.”

Aside from Autodesk, there are several other tech companies channeling substantial investments towards innovative strategies for solving the problem of affordable housing in hot markets such as Seattle and Silicon Valley. Recent investments have included Amazon’s $6.7 million-Series A funding for Plant Prefab.

AMD launches the new Radeon Pro WX 3200 graphics card

The product was launched with relatively little fanfare, but this graphics card is seen to fill a niche that AMD sees a lot of potential in, which is the AEC (architecture, engineering, construction) and manufacturing industries. The Radeon Pro WX 3200 is ISV-certified, fits into small-form CAD workstations, and is quite affordable, staying in the under-$200 budget. 

AMD touted its compact and cost-efficient graphics card in a blog post which also detailed the software programs compatible with the new product, including ANSYS, Autodesk Inventor, Autodesk Revit, CNC Software Mastercam, Dassault Systemes Abaqus, Graphisoft ArchiCAD, Siemens PLM Software Solid Edge, and many more. 

According to AMD, the Radeon Pro WX 3200 is about 33 percent faster than the WX 3100 which came before it. The graphics card works with 4GB of GDDR5 memory, 128-bit interface. The driver set for the graphics card is AMD Radeon Pro Software for Enterprise, along with other AMD Radeon Pro GPUs. 

Design firm Morpholio is now using augmented reality to bring to life a range of iconic furniture designs

Morpholio is teaming up with manufacturer Knoll and leading AR visualization company Thei Interactive to showcase the works of such known designers like Eero Saarinen, Mies van der Rohe, and Marcel Breuer, with the help of AR. 

Morpholio is pushing the limits of how far they can use Augmented Reality in this industry. Anna Kenoff, the co-founder of Morpholio, said, “Knoll’s collection is not only beautiful; the attention to detail made the furniture a perfect argument for why AR needed to go further using Apple’s new USDZ 3D file format.”

The team needed to hurdle two major obstacles, the first one being the detail. As Kenoff explained, “Consumers and interior designers do not rely on cartoonish shapes to make critical decisions about color, space, scale and texture. They need to see detailed finishes, patterns and even stitching to understand how something might really work in an environment.” Morpholio’s popular Board App now combines the abilities of Apple’s ARKit, USDZ 3D file format, iOS13’s “People Occlusion”, and Theia’s AR expertise to solve the detail conundrum.

The other obstacle was answering the question of why AR would be needed in this regard in the first place. Morpholio’s goal was to make AR part of an even bigger process. Mark Collins, co-founder of Morpholio, said, “This isn’t about hitting the buy button on a single piece of furniture. This is powerful visualization technology that needed to be plugged into the entire interior design workflow, helping homeowners and designers alike to imagine and curate spaces holistically.”

Bill Fishkin of Theia sums it up, “By bringing these pieces into AR, we’ve changed the way people can interact with and consider the furniture that will surround them when creating their ideal home or office.  The result is a first in the space and truly redefines how we understand what good AR can do for the design industry.”

Other stories we thought you should check out:

• Nike’s new Joyride shoes use tiny beads and an adaptable cushioning system to make your runs more comfortable. 

• A new knee-powered energy harvester from researchers at the Chinese University of Hong Kong generates enough power to keep small electronic gadgets working. 

• Researcher and designer Rosie Broadhead has collaborated with microbiologist Dr. Callewaert of Ghent University to develop a probiotic clothing concept activated by sweat. 

In this edition of Coffee Break News, we will talk about popular AutoCAD alternative DraftSight no longer being free, forecasts ahead for the CNC market as a whole, and tiny-home treehouses designed by Studio Precht for Baumbau. Also included are stories on innovations of outdoor workspaces in an office block in Nice, how demolition waste is being repurposed into chandeliers and candelabra, and airless tires which would be available to consumers by 2024.

There’s a lot to cover in this edition, so let’s get right down to it!

DraftSight 2019 is no longer free

Dassault Systemes has announced that Draftsight 2019 for Windows will only be offered in paid versions. This means if you are using a free version of DraftSight (2018 or earlier), it will no longer run after December 31, 2019.

Meanwhile, users who download and install the free 30-day trial or the purchased version of DraftSight 2019 will no longer be able to download or access previous free versions of DraftSight.

According to Dassault Systemes, DraftSight 2019 is a major software upgrade showcasing user-requested capabilities and functions, with powerful new features and flexibility. 

For the DraftSight Standard, there will now be an annual charge of $99. The purchase can be made directly from the DraftSight Online store. DraftSight Professional is available at an annual subscription price of $199, while DraftSight premium clocks in at $499 per year. 

The CNC market is expected to continue growing

According to industry forecasts, the CNC market will continue to grow from 2019-2024 at a projected rate of 7.3%. This is according to ResearchAndMarkets.com’s report entitled “The Computer Numerical Controls (CNC) Market – Worldwide Growth, Trends, and Forecast (2019-2024). According to the report, the market growth will be driven by the continued increase in demand for productions efficiency.

Production efficiency refers to the ability of CNC machines to streamline various operational processes through reduced production time and minimal operator error. In addition, the increased competition in the market has made rivals more focused on enhancing the efficiency of their manufacturing and production techniques, through redesigned facilities and equipment.

One area of interest is Asia-Pacific, where the rapid establishment of manufacturing facilities has driven up the usage of CNC in various sectors. Developing economies in the region, including China and India, have seen rapid industrialization growth, thus contributing to the increased demand for CNC. According to the report, automated manufacturing in the industrial sector is another reason for the growing demand for CNC machines, as well as power generation.

Modular treehouses are coming to Baumbau

Design firm Studio Precht has created truncated timber treehouses for eco-building start-up company Baumbau, with the concepts created by Chris Precht and his spouse Fei Tang Precht. The modular houses are inspired by a mood of playfulness and shaped by the actual forest, with the perspective of children looking at nature and architecture. 

This is the first time that Precht and Baumbau have collaborated on a project. Baumbau is a start-up that focuses on building tiny homes, treehouses, and buildings mainly for alternative tourism. According to Precht, “We took a playful look at this project and wanted to create a rather unique character than a conventional building. A quirky looking character that becomes part of the wildlife of a forest. I think this quirkiness can create feelings and emotions. And maybe these are attributes in architecture that are missing these days.”

The truncated treehouse design is called Bert, and the modular building system consists of prefabricated factory parts which are then assembled on-site. The houses have solar panels, a composting toilet, and a water treatment facility located on the ground floor. The first structures are expected to be completed by spring of 2020.

Other stories you should check out this month:

• This unique Anis office block in Nice is covered in outdoor workspaces, designed by architects Dimitri Roussel and Nicolas Laisne.
• London design studio JamesPlumb has been using demolition waste to create a unique collection of chandeliers and candelabra. 
• Automotive giants GM and Michelin are teaming up to bring airless tires to passenger cars by 2024. 

There’s a lot of exciting news for us to cover in this edition of Coffee Break News. There’s billionaire Jeff Bezos’ announcements of a concept for a lunar lander as well as plans for orbital space colonies, the 19_19 concept car from Citroen which promises to be as smooth as a “magic carpet ride” for passengers, and the big reveal of this year’s “Big Ideas for Small Lots NYC”.

Other stories we thought you shouldn’t miss include the release of Mola’s third Structural Kit to Kickstarter, a proposal from MIT’s Self-Assembly Lab on how islands and coastlines can be grown in the face of climate change, and the release of a Robo-Walker designed to give mobility to kids with cerebral palsy.

Let’s get right down to it!

Bezos’ Blue Origin unveils the lunar lander and plans to put up orbital space colonies

Amazon CEO Jeff Bezos gave the public a look into the Blue Moon Lander, designed by his company Blue Origin. The announcement was made on May 9 during a special event held by Blue Origin.

The Blue Moon Lander has a cargo variant which is designed to 3.6 metric tons to the lunar surface. There is also a human-rated ascent stage variant of the lunar lander with a carrying capacity of 6.5 metric tons. The lunar lander, according to Blue Origin, can comply with the current US administration’s goal of putting Americans on the moon by 2024.

The lunar lander is powered by the BE-7 engine with a 40Kn (10,000 lbf) thrust specified for large-scale lunar payload transport. The engine is propelled by a combination of liquid oxygen and liquid hydrogen. The Blue Moon is multifunctional and a double-decker lander with the capability of deploying a maximum of four rovers from its landing site. It can also launch orbital satellites.

Aside from the Blue Moon Lander, Bezos also detailed the company’s grandiose plans of launching orbital space colonies in the near future. The colonies will be housed in rotating cylinders, complete with simulated gravity, vegetation, and accommodation.

The concept was inspired by a proposal from Gerard O’Neill, a physicist who first came up with the idea in his 1976 book called The High Frontier. In the original concept, the cylinders featured illumination from reflected sunlight or artificial light, with the capability of supporting plant life.

“This is Maui on its best day, all year long,” according to Bezos. “No rain. No earthquakes. People are going to want to live here.”

Marking its 100th anniversary, French automotive brand Citroen announced its 19_19 concept car.

This fully electric and autonomous vehicle was described as a “living room on wheels”, borrowing from aviation design with its streamlined car body very similar to an aircraft fuselage.

The concept car also has a helicopter-like transparent bubble, and a suspended cabin supported by Citroen’s Progressive Hydraulic Cushion. This suspension makes the car body look and feel as if it were levitating above the wheels, thus eliminating bumps or potholes and offering an experience akin to a magic carpet ride.

In addition to the elevated cabin and suspension, the car also has oversized 30-inch wheels developed together with Goodyear. The wheels have a porous texture designed to absorb impact and eliminate noise. The tires come with embedded smart sensors monitoring road conditions when the car goes into autonomous mode. The 19_19 reaches speeds up to 100 kilometers per hour in 5 seconds, and a top speed of 200 kilometers per hour.

Pierre Leclercq, head of design for Citroen, said, “With 19_19 Concept, we sought to rewrite the automotive rule book with a high-impact vehicle featuring a strong and powerful design inspired by the world of aviation.”

Finalists for the Big Ideas for Small Lots NYC design competition have been announced

The competition was announced in February 2019 calling for proposals from architects and designers to develop high-quality and affordable housing concepts on small, irregular lots spread out across New York City.

‘System for Narrow Living’ by design firm Only If. (Source)

444 proposals from 36 nations were submitted to the competition which is part of the city mayor’s Housing New York 2.0 plan. The plan enhances efforts by the city to identify and find solutions for various housing sites that are particularly difficult to develop due to their size or irregular characteristic. Spearheaded by the New York City Department of Housing Preservation and Development and the American Institute of Architects New York Chapter, the competition narrowed down the proposals to five finalists.

Finalists included the Michael Sorkin Studio, 101+Kane AUD, OBJ, Only If Architecture, and Palette Architecture.

More stories we loved this month

• Mola releases their third Structural Kit to Kickstarter
• MIT’s Self-Assembly Lab proposes new way of growing islands and coastlines and minimize the effects of climate change 
• Kids with cerebral palsy now have a better way of moving around, thanks to this Robo-Walker

Designs for the new London concert hall are nothing short of stunning

A 2000-seat London concert hall for the London Symphony Orchestra is being planned, and the first designs for the £288M centre for music have been released. The new concert hall will be built on the current site of the Museum of London, and the concept incorporates a pedestrian plaza and foyer, four levels of commercial space, a restaurant, and a smaller venue on the top floor for other musical performances, with a view overlooking St. Paul’s Cathedral.

The massive project will be funded from private donations, according to Sir Simon Rattle, the music director of LSO. “This is not something that we are trying to do with public money, this is something we are attempting to do ourselves and we are trying to make a difference.”

American architect Liz Diller, who is best known for her work on New York’s High Line, designed the wooden  concert hall with inspiration from geological formations of layered strata. Every seat in the hall will have an optimum view of the stage, and there will even be breakout areas within the audience where musicians can also perform.

The London Centre for Music is being touted as a “concert hall for the 21st century” inside a pyramid-shaped tower. It will also feature an outdoor stairway doubling as an ampitheatre and linking the hall to the Barbican highwalk network. “A vital public space seamlessly connects to the foyer and extends a welcome to everyone, with or without a performance ticket,” Diller said.

Diller added that the venue will have various activities throughout the day and can accommodate beyond just the LSO. “We imagine a concert hall for the 21st century that embraces both a bespoke and a loose fit approach: tailored for exceptional symphonic sound, yet agile enough to accommodate creative work across disciplines and genres.”

Nike’s self-lacing shoes go on sale

Nike’s decades-long dream of creating a self-lacing pair of athletic sneakers that can adapt to the wearer’s feet is finally a reality. The Adapt BB, which is a Bluetooth-enabled smart shoe, is designed to detect blood pressure and loosen automatically.

The Adapt BB does that exactly: adapt to what the wearer is doing and figure out what you want to do. “That is the broader vision, or the biggest dream, that the product becomes so synergistic to your body. It just knows almost kind of what you’re thinking,” explains Eric Avar, VP and creative director at Nike Innovation. “It’s a natural extension of your body.”

Through a paired app on the wearer’s phone, the Adapt BB will remember your preferred settings and how tight or loose you like to wear the shoe in various situations, such as warm-ups, games, and when taking a break.

This is not the first time that Nike has attempted self-lacing shoes. In 2016, the manufacturer unveiled the HyperAdapt 1.0 at a cost of $720. The shoes were bulkier and only released on a limited run. Another iteration, the high-top Mags, were also sold in limited quantities that same year.

The Adapt BB is a completely different design, as it does away with any lace whatsoever. Instead, wearers use Bluetooth to tighten or loosen their shoes right from their phones. Two popular NBA players, Jayson Tatum and Luka Doncic, will be the first athletes to don the sneakers.

The Adapt BB officially went on sale on February 17 in Nike stores and online, as well as through the SNKRS app. The cost is $350.

MIT researchers reverse engineer 3D models

Researchers from the Massachusetts Institute of Technology (MIT) have devised a software that makes use of the ‘program synthesis’ technique. This system breaks down CAD models into their original and individual shapes, including circles or cubes. The technique reverses the process by disassembling the CAD model into editable shapes, analyzing them individually, and then figuring out how the shapes were assembled into the final CAD model.

This is opposite to the constructive solid geometry (CSG) tehnique which is more widely used in creating CAD models. CSG utilizes basic shapes and adjustble parameters to assemble single objects, utilizing a mesh of 3D triangles to define the final shape. However, this process involves more work and takes more time. Also, converting triangle meshes back into shapes typically produce results that do not scale well to more complicated models, and accuracy is compromised in low-resolution files.

MIT researchers built a dataset of 50 3D CAD models that had different complexities and used this in experiments to reverse engineer CAD files made of up to 100 basic shapes. “At a high level, the problem is reverse engineering a triangle mesh into a simple tree,” according to Tao Du, a PhD student of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and part of the Computational Fabrication group behind the project.

“Ideally, if you want to customise an object, it would be best to have access to the original shapes — what their dimensions are and how they’re combined. But once you combine everything into a triangle mesh, you have nothing but a list of triangles to work with, and that information is lost. Once we recover the metadata, it’s easier for other people to modify designs,” Du explained, adding that this process could be especially helpful for manufacturing or 3D printing.

The findings of the group’s research were debuted during the SIGGRAPH Asia 2018, a computer graphics and interactive technology exhibition which was held in December.

Meanwhile, here are some other interesting stories on architecture, design, engineering, and CAD that caught our attention over the last month:

• This nine-minute video showcasing the architecture collections at the Victoria and Albert Museum is well worth the watch. Whether you are a practitioner or an enthusiast, this video will make you want to visit the actual museum very soon.
• Vention, a digital manufacturing platform for building customized factory equipment, announced that it has completed a $17M Series A financing round and is also releasing its second major platform upgrade. Vention’s main goal is to transform how companies design and order custom equipment for their operation, cutting the design-to-build workflow from months to as little as three days.
• Finally, Advance Market Analytics (AMA) released its Global Market Outlook to 2024 for the overall CAD market, including MCAD, Technology, Offerings, End User, Players, Region, etc. You can request a sample report or view the synopsis and table of contents on the page.

100-year anniversary of Bauhaus and its everlasting influence

Established in 1919 in Weimar, German’s Bauhaus art and design school marked a turning point in the approach to design, aesthetics and mass production. The school’s founder, architect Walter Gropius, sought to unite craft and creation. This followed the idea that there should be no distinction between form and function. Students from diverse social and ethnic backgrounds were immersed in hands-on workshops ranging from metalwork to furniture making to typography.

The school later moved to a new base in Dessau—designed by Gropius—in 1925. By 1932, the school was forced to move yet again due to the Nazi Party’s growing control of Dessau. Their move to Berlin wasn’t long successful, however. Soon enough, political pressure against the Bauhaus reached an all-time high. The school was branded “un-German” and was believed to be a front for communists and social liberals. By 1933, Adolf Hitler became Chancellor and the school gave into the pressure to shut down.

Source: Bauhaus Dessau

The closure of the Bauhaus, however, didn’t have the impact intended by the Nazis. Instead of stomping out the movement, they simply aided in its rapid expansion. Key figures involved with the school—including teachers and students—emigrated to countries like the US and Israel. They were then able to spread key philosophies and, ultimately, inspire future generations of architects and designers across the world. Iconic works inspired by Bauhaus include Marcel Breur’s chair designs, Marianne Brandt’s teapot, and Wilhelm Wagenfield’s WA24 Lamp.

Even today, as we celebrate the Bauhaus Centenary, we can still see its influence on modern design and architecture around the world—from Tel Aviv’s White City to Ikea’s furniture to the iPhone. Although a century might have passed since its inception, it’s clear that the minimalist elegance and simplicity associated with Bauhaus is still as important as ever.

Rio de Janeiro named first World Capital of Architecture

On 18 January, UNESCO announced that the city of Rio de Janeiro will be the World Capital of Architecture for 2020. The Brazilian city will be the first to receive this designation from UNESCO. The heritage body worked with the International Union of Architects (UIA) to push for the designation in the hopes that it “will become a global forum for discussion on the pressing challenges of our world”, not to mention developing solutions for the benefit of future generations through culture. 

Ernesto Ottone, UNESCO’s assistant director-general, said that the initiative would not only “create new synergies between culture and architecture in an increasingly urban world”, but also ensure that “these cities are also perceived as open and creative spaces for exchange, invention and innovation”. UIA President Thomas Vonier added, “We want to highlight how architects, with the help of local governments and communities can play a key role in identifying solutions that benefit communities.”

UNESCO will designate the World Capital of Architecture every three years. This will coincide with the UIA’s World Congress event. The winning city will host the event and follow a chosen theme. Rio de Janeiro’s 2020 theme is “All the worlds. Just one world”, linking back to Goal 11 of UNESCO and UIA’s Sustainable Development Agenda for 2030: “Make cities and human settlements inclusive, safe, resilient and sustainable”. 

Candida Höfer’s In Mexico: 600 years of architecture, culture and design

Source: Sean Kelly Gallery

Due to open in Sean Kelly’s New York Gallery next month, the In Mexico exhibition pulls together the collection of interior architectural photographs taken by German photographer Candida Höfer, during her trip across Mexico in 2015. Renowned for her large-scale color images of empty interiors and social spaces, Höfer toured Mexico as part of the Mexico-Germany Dual Year exchange programme.

During her trip, Höfer traveled across cities like Mexico City and Oaxaca, capturing the interiors of cultural and institutional buildings—including churches, libraries and museums—dating back to the 15th century. From the National Museum of the Viceroyalty of New Spain to the Church of Santo Domingo de Guzmán, Höfer was able to capture over 600 years’ worth of architectural history. The Sean Kelly Gallery praised Höfer’s works for documenting “not only the physical details of these interiors but also […] the spirit and essence of each space”.

Indeed, Höfer’s work is most notably devoid of people. By doing so, she instead draws our attention to the intricate architectural details of each space. When describing her work and the resounding absence of people, Höfer commented that “it became apparent to me that what people do in these spaces—and what the spaces do to them—is more obvious when nobody is present”.

The In Mexico exhibit will run from February 2 to March 16.

Autodesk successfully acquires BuildingConnected

We don’t seem to be able to go to more than a month or so without mentioning one particular CAD powerhouse: Autodesk. In December, Autodesk announced its planned acquisition of BuildingConnected in a move to further bolster their already impressive portfolio. This month, they completed their acquisition for $275 million net of cash acquired.

BuildingConnected currently stands as one of the biggest digital networks in the construction industry—boasting over 700,000 professional users. It allows owners, contractors and subcontractors to streamline their businesses and communication with a suite of preconstruction software tools. Additionally, it enables users to quickly find and select subcontractors, not to mention respond to project opportunities. Notable customers of the platform include Turner Construction, StructureTone and AECOM.

Autodesk’s plan is to fully integrate workflows between BuildingConnected and Autodesk products including BIM 360, Revit and AutoCAD. By doing so, Autodesk hopes to increase construction productivity and make communication across project teams more efficient. Furthermore, they hope to offer a full construction solution that “addresses the critical processes and workflows across the project lifecycle from start-to-finish”.

Dassault Systèmes: life in the city of 2030

During the Consumer Electronics Show (CES), the annual gathering for those in consumer technology, Dassault Systèmes unveiled a study on US consumer expectations in life in the city of 2030. Dassault conducted this study in partnership with CITE Research. CITE asked a series of questions to a sample of 1,000 American consumers on topics such as home, health, travel and retail. Looking at the results, it’s clear that consumers expect an increase of automation in almost every area of their lives.

Artificial Intelligence (AI) plays a heavy role in consumer predictions, with 73% expecting to use remotely monitored appliances at home and 40% believing they’ll be using virtual home robots. When it comes to travel, 63% of consumers expect to be using an autonomous car, 51% expect to travel by hyperloop and 38% believe it’s likely that they’ll be using air taxis by 2030. The most expectation from consumers, however, seems to lie in healthcare, with a strong 83% expecting personalized preventative plans based on nutrition and behavior. Additionally, 81% expect to be using innovative devices to dispense treatments at home.

It’s safe to say that consumers are pretty confident in the upward trajectory of autonomous technology and breakthroughs. With its 3DEXPERIENCE platform, Dassault Systèmes hope to meet these consumer expectations and then some!

More stories we loved this month

Whilst we’d love to discuss every interesting story that caught our eye in January, we simply don’t have the time or space! We would, however, like to highlight a few extra stories that we loved from the world of CAD, architecture and design.

• Business of Architecture interviewed a managing partner of a Vancouver-based architecture firm, giving us a glimpse at how creating a multidisciplinary practice can bring in new opportunities and strengthen relationships with clients.
• We always love to hear about 3D printed-related news, especially when it revolves around improving lives. This month, Osseus Fusion System’s 3D printed titanium spinal implants were implemented successfully for the first time.
• In a particularly interesting opinion piece, Darran Anderson argues that we must develop a new form of architecture to adapt to major environmental changes. Instead of imagining Utopian landscapes based on optimism, “to survive, cities will have to embrace their environmental aspect“.
• We’ll finish off our list with a look to what 2019 might hold for interior design. According to Michelle Ogundehin’s trend report, interior design will see an increase in interest around well-being, comfort and more.