<p dir="ltr">This year, GlobalData <a href="https://www.nsmedicaldevices.com/analysis/coronavirus-ventilators-global-demand/" target="_blank">estimated</a> the need for an additional <a href="https://www.nsmedicaldevices.com/analysis/coronavirus-ventilators-global-demand/" target="_blank">880,000 ventilators worldwide</a> to cope with the demand caused by the coronavirus outbreak. Ventilators get oxygen to a person’s lungs while removing carbon dioxide, essential for patients who are too sick to breathe on their own. Using a ventilator can give the patient time to fight off the infection and recover.&nbsp;</p><p dir="ltr">Engineers at NASA’s Jet Propulsion Laboratory (JPL) took on the challenge to design a ventilator tailored to treat coronavirus (COVID-19) patients that could be mass-produced and gain government approval. It took just 37 days for the team to create a device called VITAL (Ventilator Intervention Technology Accessible Locally). VITAL will free up the nation's limited supply of traditional ventilators.&nbsp;</p><h2 dir="ltr">Fast track FDA approval</h2><p dir="ltr">NASA received expedited approval from the United States national health and medical approval body, the Food and Drug Administration (FDA) for the device via an emergency use authorization, a fast-track approval process developed for crises that take just days rather than years. Since VITAL’s development, <a href="https://medeng.jpl.nasa.gov/covid-19/ventilator/registration/" target="_blank">28 manufacturers</a> around the world have been licensed to make the device. Another iteration of the ventilator that uses an air compressor also received a ventilator Emergency Use Authorization from the FDA.</p><p dir="ltr">VITAL can be built faster and maintained more easily than a traditional ventilator and is composed of far fewer parts. It can also be modified to fit alternative health care settings such as the coronavirus specific field hospitals, which are being set up across the country and around the globe. Like all ventilators, VITAL requires patients to be sedated and an oxygen tube inserted into their airway to breathe. VITAL isn’t a replacement for traditional high-end hospital ventilators that can last for years and be used on patients with multiple complex conditions, rather the device is intended to be used during the duration of the pandemic and is specifically tailored for COVID-19 patients.</p><p dir="ltr"><span class="fr-img-caption fr-fic fr-dib" style="width: 788px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjA2ODE1MjgyNDEwLUpQTDIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ=="><span class="fr-inner" spellcheck="false">Credits: NASA/JPL-Caltech&nbsp;</span></span></span></p><h1 dir="ltr">VITAL and Supplyframe</h1><p dir="ltr">Visibility into global electronics supply chains was essential for JPL to be able to create a device that others could replicate without facing any component or part supply issues. In the video above, Erika Earl shares her experience working with the JPL team on the VITAL project. She discusses how Supplyframe’s software solutions helped her and the team quickly pinpoint components that would benefit their design and keep the pressure off conventional medical supply chains.&nbsp;</p><p dir="ltr">To build supply resiliency into the design while avoiding interfering with existing medical supply chains already under strain. Erika used Supplyframe’s design intelligence software to search for similar components to their needs outside of the medical industry. The platform allowed the hardware and supply chain engineers to see into suppliers’ stock levels and availability. Supplyframe's Design to Source Intelligence uses data from the electronics value chain to surface Insights for stakeholders across the design cycle. Read a more in-depth look at the way DSI is collapsing the electronics industry design cycles<a href="https://www.wevolver.com/profile/supplyframe" target="_blank">&nbsp;here.</a>&nbsp;</p><p dir="ltr">Supplyframe recognizes the impacts on the global electronics supply chain and has begun developing resources that can help organizations better cope with the current situation and future product designs. These resources include their white paper on the <a href="https://supplyframe.com/solutions/downloads/npi-whitepaper" target="_blank">mandate for transformation in NPI</a> and supporting a global survey of stakeholders across the electronics supply chain to identify opportunities for improvement across the industry.&nbsp;</p><h1 dir="ltr">Innovation in scarcity</h1><p dir="ltr">The demand for ventilators has spurred many design teams to deliver a robust, scalable design within a short time frame. Dyson reportedly spent 20 million pounds developing a new ventilator called CoVent in just two weeks in response to a UK government request. <a href="https://www.wevolver.com/article/combating-covid-19-with-open-source-behind-the-scenes-at-respiraworks" target="_blank">RespiraWorks</a> is an open-source volunteer-run organization developing a ventilator that is affordable and easy to build in countries with developing economies and low-resource communities. The team described their own challenges working with an under-pressure supply chain <a href="https://vimeo.com/455530740" target="_blank">in this webinar.</a>&nbsp;</p><p dir="ltr">Other ventilator related projects are also underway. Researchers at Eindhoven University have improved ventilators performance by a factor of ten using a technique based on self-learning algorithms. The <a href="https://www.ifm.eng.cam.ac.uk/" target="_blank">Institute for Manufacturing (IfM)</a> is developing a device that could be attached to a ventilator to enable two COVID patients to receive tailored respiratory support if needed in an emergency.</p><h1 dir="ltr">Looking forward</h1><p dir="ltr">The need for resilient supply chains that can respond to the fluctuations created by unexpected events such as the global coronavirus pandemic is clear. Leveraging existing data within design cycles and from the supply chain is essential to creating future-proof and resilient products and systems critical to beating this crisis while preventing the next.&nbsp;</p><hr><h1 dir="ltr"><em>About the sponsor: Supplyframe</em></h1><p dir="ltr"><em>This article is sponsored by Supplyframe. Supplyframe aligns electronics demand with supply and brings new levels of resiliency to the global electronics value chain, with transformative, intelligence-based solutions to deliver insights at key decision points throughout the entire design-to-source product lifecycle. Leveraging billions of continuous signals of design intent, demand, supply, and risk factors, Supplyframe’s Design-to-Source Intelligence (DSI) Platform is the world’s richest intelligence resource for the electronics industry. Over 10 million engineering and supply chain professionals worldwide engage with our SaaS solutions, search engines, and media properties to power rapid innovation and optimize in excess of $120 billion in annual direct materials spend. Supplyframe is headquartered in Pasadena, Calif., with offices in Austin, Belgrade, Grenoble, Oxford, San Francisco, Shanghai, and Shenzhen.</em> &nbsp;</p><p dir="ltr"><img class="fr-fic fr-dib" src="https://images.wevolver.com/eyJidWNrZXQiOiAid2V2b2x2ZXItcHJvamVjdC1pbWFnZXMiLCAia2V5IjogImZyb2FsYS8xNjA2NDk5ODY5ODEzLXN1cHBsZXlmcmFtZSBsb2dvIGJhbm5lci5qcGciLCAiZWRpdHMiOiB7InJlc2l6ZSI6IHsid2lkdGgiOiA5NTAsICJmaXQiOiAiY292ZXIifX19" style="width: 788px;"></p><p><br></p><p><br></p>

Article 3 in our PCB design series: Quickly finding relevant and available components was essential to achieving this ambitious life-saving project.

Supplyframe Aids Rapid Development of Supply Chain Resilient Ventilator

<h2>What is Generative Design?</h2><p>Generative design is an emerging engineering design methodology that combines elements from CAD, multiphysics simulations, and computer science.</p><p>Since it touches upon so many different disciplines, concisely defining what exactly generative design is can be challenging. Here’s the one that I prefer:</p><p>“Generative design is a goal-driven, computational design methodology. <a href="https://ntopology.com/generative-design-software/" target="_blank">Generative design software</a> equips engineers with digital tools that enable them to explore a large design space effectively and efficiently and converge quickly to the best possible solution.”</p><p>For engineering design, the outcome of a generative process is typically a component with an optimized geometry that meets high-level design requirements.</p><p>These can be either <em>technical&nbsp;</em>— such as strength, stiffness, weight, manufacturability, and cost — or <em>non-technical</em> — like aesthetics, serviceability, recyclability, consistency with design standards and organizational procedures, or compliance with the regulations of different countries.</p><p>Let’s explore further the key elements of the generative design process.</p><h2 dir="ltr">Generative design is goal-driven</h2><p dir="ltr">In this sense, generative design is not much different than the traditional iterative engineering design process. It begins by creating a minimal set of high-level design constraints and objectives. The main distinction is the emphasis that is put on the problem definition phase. Defining the available design space clearly is critical to obtaining a usable result.</p><h2 dir="ltr">Generative design is computational&nbsp;</h2><p dir="ltr">In generative design, the geometry is created by an algorithm and not directly by the designer. Simulations are at the core of practically every generative process. This means that generative results are partially validated — of course, a detailed analysis is necessary for mission-critical components. This high degree of automation allows the exploration of a wider design space faster and more effectively than ever before.</p><h2 dir="ltr">Generative design is a digital tool</h2><p dir="ltr">In essence, generative design is a deeply collaborative activity between the designer and the software. The outcome of most generative design algorithms is merely a solution proposal — not an engineered product. Several steps and iterations are needed to further explore, refine, and validate these results. Of course, by combining the expertise that seasoned engineers have built over the years with the power of these digital tools, you can create solutions that were previously impossible.</p><p dir="ltr"><span class="fr-img-caption fr-fic fr-dib" style="width: 788px;"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1606386967214-1606386967214.png"><span class="fr-inner"><em>Every physical attribute can be expressed as a field: geometry, simulations, experimental data. If you superimpose these fields, you can generate high-performance parts. Source: nTopology</em></span></span></span></p><h2>The Value of Generative Design</h2><p>The intrinsic value of generative design is that it flips the traditional model of first creating and then evaluating a geometry. Instead of asking, “does this shape meet my requirements?”, an engineer following a generative approach asks, “what is the shape that best meets my requirements?”</p><p><em>Generative design is a tool that unlocks rapid engineering innovation.</em> If used correctly, it can help your business unlock new opportunities for rapid engineering innovation. More specifically, generative design can:</p><p>Accelerate your product development cycles by automating manual engineering design and verification tasks</p><p>Lead to the development of better products as it produces unbiased solutions that may not immediately be obvious to a human designer</p><p>Enable you to take full advantage of advanced manufacturing technologies, such as additive manufacturing or any other robotic or digital manufacturing process</p><p><br></p><h2>The Traditional “Black Box” Paradigm</h2><p>It may surprise you that most “generative” tools today are based on the same methodology: topology optimization; a simulation-driven approach first developed back in the ’80s.</p><p>Topology optimization is a powerful tool that can generate new concepts during the early stages of the design process, but it has certain practical limitations that hinder its wider use in real-world applications of generative software that are based on it.</p><p><em>Topology optimization is very sensitive to the inputs that you give it.</em></p><p>Even a small change in a parameter or input can make a huge difference to the produced “optimum” result. You can see this in action in a recent nTop Live by our application engineers or in this presentation by one of the pioneers of topology optimization.</p><p><em>AI-powered solutions are not as good as they may seem.</em></p><p>So, you may think: “let’s use machine learning to predict what values will produce the best results.” This is the approach that many software vendors followed. But there is a big caveat: the burden of evaluating a design still falls on the engineer. Design evaluation and validation is a complex process and contemporary AI tools cannot perform such complex tasks.</p><p><em>Engineers do not work using “black box” approaches.</em></p><p>The standard approach to generative design seems to be this simple three-step approach: 1) specifying objectives and constraints, 2) wait for the algorithm to generate solutions, and 3) select the best option. In my experience, engineers do not work this way. Engineering design is characterized by multiple iterations and frequent change. It is much more complex than what can be captured by a generic workflow.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 788px;"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1606387016125-1606387016125.png"><span class="fr-inner"><em>Using Field-Driven Design, you can use simulation results or experimental data to directly drive complex geometry. Source: nTopology</em></span></span></span></p><h2>An Alternative Approach to Generative Design</h2><p>Here’s the idea in a nutshell: instead of following the steps that someone else built for you, create your own generative design workflows. This approach enables you to incorporate specific engineering knowledge that already exists in your team while gaining all the other benefits of generative design.</p><p>nTop Platform is a generative design software that gives engineers direct and predictable control over every aspect of the process and its outputs. We built our software so that you can adjust it to your engineering workflows — not the other way around.</p><p>To tackle the limitations of traditional modeling technologies, we built nTop Platform on an unbreakable implicit modeling engine. This is a technology we pioneered for mechanical engineering applications. It is fast, robust, and can easily handle geometries with high levels of complexity.</p><p>To help you create reusable and standardized engineering design processes, we created a platform where built-in and user-created capabilities seamlessly merge into reusable workflows. This way multiple engineers can collaborate to build systems that encapsulate core engineering knowledge, manufacturing methodologies, and your in-house IP. Then lock them and share them with the organization to scale-up.</p><p>To enable you to go beyond topology optimization, we developed a generative design methodology we call <a href="https://ntopology.com/field-driven-design/" target="_blank">Field-Driven Design</a>. By superimposing different fields — including, complex geometry, simulation results, or experimental data — you can create unique, optimized, and high-performing structures.</p><p>If you want to learn more about our approach, we wrote a <a href="https://ntopology.com/generative-design-guide/?utm_source=guest_blog&utm_medium=PR&utm_campaign=gen-design-PR&utm_term=&utm_content=gen-design-blog-v1&source=website&comment=" target="_blank">Guide to Generative Design</a> that is now available for download.</p><h1>Key takeaways</h1><p>Generative design is a computational approach to engineering that uses algorithms to create part geometry.</p><p>The practical value of generative design is that it can greatly speed up your engineering process and allow you to explore a wider design space.</p><p>The traditional “black box” approaches that are based on topology optimization are foreign to that way that engineers work.</p><p>nTop Platform gives you an alternative approach to generative design by giving you complete control over the whole process.</p>

Topology optimization is a great tool for lightweighting, but generative design can offer much more. Source: nTopology

Generative design is getting a lot of attention in the world of engineering, but what is it exactly? Here we explain how generative design can add value to your engineering process and why you should probably avoid the popular "black box" approaches.

Generative Design in Engineering: Two Different Approaches

<p dir="ltr">In our <a href="https://www.wevolver.com/article/the-printed-circuit-board-design-and-manufacturing-cycle-symbiotic-relationships-engage-innovation" rel="noopener noreferrer" target="_blank">previous articles&nbsp;</a>on the Printed Circuit Board (PCB) design and manufacturing cycle we focussed heavily on the role of online CAD libraries. In this new article, we look at the broader electrical design cycle and examine the services that are assisting engineers to make intelligent data-driven design decisions.</p><h2 dir="ltr">The electronics design cycle</h2><p dir="ltr">The development of any new electrical device or system requires an enormous amount of stakeholders, talents, technologies, and markets. As manufactured products across industries are increasingly electrified, this design cycle must evolve, and embrace the technologies that accelerate innovation and speed to market. Two of the most influential players in this system are the development engineers, who are designing devices and integrated systems, and the manufacturers who are providing the components for use within those systems. Each relies on the other to continue innovation, however, the gap between these two groups has been significant, resulting in an inability for either party to peer inside the design ecosystem and understand the impact of the others design considerations.&nbsp;</p><h1 dir="ltr">Designing with Intelligence</h1><p dir="ltr">The electronics design cycle involves massive amounts of data associated with parts, components, and interoperability requirements each step in the process requiring deliberate and consequential decision making. Harnessing this data, and analyzing usage trends, design intent and demand creates a massive potential for better decision making, reduced costs, faster time to market, and better collaboration. &nbsp;</p><p dir="ltr">Recognizing the value of this data and engaging in ways to collect, distill and apply it will radically improve the overall design cycle, reduce time to market, improve the resilience of product, ensure a more competitive market and create space for innovation.&nbsp;</p><h2 dir="ltr">Where is the data and how can it be captured, synthesized, and applied?</h2><p dir="ltr">This data comes from several sources. A good starting point for understanding the amount and value of the data is the way part and component assets are provided to engineers. All engineers must go through a process of researching and selecting components for use within their design, the individual properties, size, and quality of the components have a massive impact on the end product. As described in <a href="https://www.wevolver.com/article/alex-macdougall-is-on-a-mission-to-solve-a-problem-at-the-core-of-the-electronics-industry" rel="noopener noreferrer" target="_blank">previous articles</a>, the biggest change in CAD-based PCB design is the advent of free online CAD component libraries. These libraries allow engineers to download clean CAD models directly to their workspaces. &nbsp;While this supports the engineer’s efficient workflow it also creates a very valuable insight into which components are being downloaded where, essentially giving suppliers a view into the future by seeing which components will be in demand. Further analysis and integration of design tools would provide insights into exactly what products these components are being used in.</p><p dir="ltr">Looking the other way, designers using these <a href="https://www.wevolver.com/article/alex-macdougall-is-on-a-mission-to-solve-a-problem-at-the-core-of-the-electronics-industry" rel="noopener noreferrer" target="_blank">libraries</a> can see quickly the cost, inventory, and iteration of the components they choose, allowing them to make decisions that will future proof designs against lack of supply, etc. These data-gathering points can be further broken down into categories and examined for value opportunity for both designers and suppliers to the system to find the opportunity to insert intelligence into decision making across the design cycle.</p><p dir="ltr"><img class="fr-fic fr-dib" src="https://images.wevolver.com/eyJidWNrZXQiOiAid2V2b2x2ZXItcHJvamVjdC1pbWFnZXMiLCAia2V5IjogImZyb2FsYS8xNjA1NTMzMDMwMzY0LW1hbnVmYWN0dXJpbmcgZWxlY3Ryb25pY3MuanBnIiwgImVkaXRzIjogeyJyZXNpemUiOiB7IndpZHRoIjogOTUwLCAiZml0IjogImNvdmVyIn19fQ==" style="width: 788px;"></p><h2 dir="ltr">Search Intelligence</h2><p dir="ltr">As discussed above, search intelligence provides designers not only with fast high-quality CAD models for direct integration into design software, but also a way to understand the demand and inventory on these items anticipating future demand and supply which provides visibility into futureproofing, allowing the designer to decide based on this knowledge if they are making the most resilient choice. We dived deeper into the benefits of intelligent component search for designers in <a href="https://www.wevolver.com/article/samacsys-power-user-case-study-icarus-design" rel="noopener noreferrer" target="_blank">our interview</a> with PCB designer Johnnie Howman and the benefits for the supplier side in a discussion with semiconductor manufacturer, Nexperia.&nbsp;</p><h2 dir="ltr">Price analytics</h2><p dir="ltr">Insight into the price of components across manufacturers with the context of the market gives the opportunity to make informed decisions for overall product competitiveness and resilience. This data not only informs overall product cost but insights into the risk and availability of components that can affect time to market, assembly timelines, and iteration planning. From a supplier perspective, understanding the consequences of the pricing and availability data gives guidance to marketing and manufacturing design decisions.&nbsp;</p><h2 dir="ltr">Overview design history</h2><p dir="ltr">Knowing the design decisions of engineers in similar workflows to your own provides the ability to design with full authority. This use of data intelligence collapses organizational structures and increases visibility and collaboration across the industry. It can be thought of as like checking for 5-star reviews on Amazon - reassuring yourself as a potential consumer of a product that it meets the quality, performance, and availability requirements of your peers, as well as vouching for the service from the product manufacturer.&nbsp;</p><p dir="ltr">For designers, if they can see that a particular component has proved highly popular with other designers (as indicated by stock availability in the market for example, perhaps due to competitive pricing from the manufacturer) then this helps add confidence to their decision to design with it. This increased confidence has other knock-on effects such as shorter design cycles more space for innovation.&nbsp;</p><h2 dir="ltr">Behavior modeling</h2><p dir="ltr">Behavior modeling allows component manufacturers to get an early view of what parts designers are using, in order to influence their plans for the parts proving "popular". This essentially gives suppliers an ‘over the shoulder’ view of the design process that they can use to inform decisions on asset delivery and marketing as well as engage and influence decision-makers at the design end.</p><h2 dir="ltr">Data backed pricing analysis</h2><p dir="ltr">Traditional ‘request for quote’ processes is a potential bottleneck in an efficient road to market. &nbsp;Aggregating pricing data across the entire supply chain can provide an opportunity for engaging in the quoting process in a whole different way that provides benefits to all stakeholders. Suppliers can combine market intelligence with customer account purchase patterns to optimize quotes for margin. While designers can optimize designs for target costs, and mitigate the risk of downstream supply disruption.</p><h2 dir="ltr">Supply Intelligence</h2><p dir="ltr">Supply intelligence reveals stock and inventory data, as well as critical timelines that may influence design decisions. It’s hugely beneficial for all parties and is a key data point that has previously been extremely difficult to access. Take the following example; some highly popular components or at times, component categories (e.g. Tantalum capacitors) can go into long-term supply issues due to the high demand. They end up being designed-in to huge numbers of products (for all the right reasons) and hence demand soars. Usually, manufacturers forecast and position themselves to meet the demand but in some cases a critical part of supply chain breaks (perhaps cobalt supplies for Lithium-ion batteries) creating shortages and long lead-times. Many designers are oblivious to this until it's too late as they are typically separated from the purchasing/supply process. So by having true supply intelligence available at the time of designing, they can be aware of any product issues or shortages, then make appropriately informed decisions.&nbsp;</p><h1 dir="ltr">Data into intelligence</h1><p dir="ltr">It's easy to see just how much data exists in the electronics value chain and the benefits that using that data can provide. However, it's also clear that much of this data is either locked away in inaccessible channels or if possible to access is so complex, the analysis and presentation is far too resource-heavy an investment. The answer to this is two-pronged, the first is a recognition by all players across the chain that a data-driven approach is essential for the next leap in innovations, and secondly dedicated players in the space to act as the gathers and filters for the ‘data.’</p><h2 dir="ltr">Supplyframe</h2><p dir="ltr">SaaS company, Supplyframe, has built a software product that enables this existing data to be converted into insights that support decision making and offers resilience. Supplyframe’s goal is to allow engineers and suppliers to inject data-driven intelligence into their processes resulting in innovation across the space. They do this by providing a suite of applications useful for all players in the space to access relevant data and the context to apply it. For suppliers and distributors, this means delivering actionable insights that drive better decisions across new product development initiatives, full product life cycles, and strategic sourcing of direct materials. For designers and manufacturers, this is access deep into the decision-making process, transparency across component supply, and insights into design trends and strategies.&nbsp;</p><h1 dir="ltr">Conclusion</h1><p dir="ltr">The electrical design cycle is a data-rich space that requires a layer of analysis in order to create a connected, intelligent design-to-source lifecycle. The road to the ubiquitous use of data-driven intelligent decisions making for all stakeholders in the electronics design cycle is prepared and will be unlocked by engagement with the right applications across the industry.&nbsp;</p><hr><h1 dir="ltr"><em>About the sponsor: Supplyframe</em></h1><p dir="ltr"><em>This article is sponsored by Supplyframe. Supplyframe aligns electronics demand with supply and brings new levels of resiliency to the global electronics value chain, with transformative, intelligence-based solutions to deliver insights at key decision points throughout the entire design-to-source product lifecycle. Leveraging billions of continuous signals of design intent, demand, supply, and risk factors, Supplyframe’s Design-to-Source Intelligence (DSI) Platform is the world’s richest intelligence resource for the electronics industry. Over 10 million engineering and supply chain professionals worldwide engage with our SaaS solutions, search engines, and media properties to power rapid innovation and optimize in excess of $120 billion in annual direct materials spend. Supplyframe is headquartered in Pasadena, Calif., with offices in Austin, Belgrade, Grenoble, Oxford, San Francisco, Shanghai, and Shenzhen. &nbsp;</em></p><p dir="ltr">&nbsp;<img class="fr-fic fr-dib" src="https://images.wevolver.com/eyJidWNrZXQiOiAid2V2b2x2ZXItcHJvamVjdC1pbWFnZXMiLCAia2V5IjogImZyb2FsYS8xNjA1NTMyMTQxNjcyLXN1cHBsZXlmcmFtZSBsb2dvIGJhbm5lci5qcGciLCAiZWRpdHMiOiB7InJlc2l6ZSI6IHsid2lkdGgiOiA5NTAsICJmaXQiOiAiY292ZXIifX19" style="width: 788px;"></p><p dir="ltr">&nbsp;</p><p><br></p><p><br></p>

Insights derived from engagement with technical digital content are assisting designers and component makers at every stage of the electronic design process.

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Supplyframe Aids Rapid Development of Supply Chain Resilient Ventilator

Generative Design in Engineering: Two Different Approaches

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