By Dan Deisz, Rochester Electronics’ Vice President, Design Technology

There are many factors in any semiconductor product “puzzle” that can lead to obsolescence. These pieces range from business revenue to subcomponents of semiconductor products, including foundry process technologies, packages, substrates, lead frames, test platforms, and design resources. The puzzle pieces often include any given semiconductor company’s overall corporate or market focus. Market foci may change over time for a semiconductor company, even while a long-term system company, such as a customer, may not alter its product focus. Given the long-term availability risks inherent in any product selection, the part numbers offered by original component manufacturers extend well beyond the bill of materials (BOM) health reports provided by commercially available tools. 

How does the manufacturing supply chain impact long-term product availability? 

Most older semiconductor products are assembled in leadframe packages, such as DIP, PLCC, QFP, and PGA. However, the semiconductor market has shifted from leadframe packages as the primary volume driver to substrate-based assemblies. 

Why did the industry move away from lead frame assemblies? 

To fully understand why lead frame assemblies are disappearing, it is important to address the history of assembly locations, profit margins, and the move toward ever-increasing performance. 

Assembly offshoring started happening in earnest during the 1980s. This was before TSMC’s dominance in foundry technologies. Costs and environmental restrictions primarily drove offshore assembly, as 1980s assembly processes were less environmentally clean than those of today. The push for higher profit margins gradually eliminated numerous leadframe suppliers from the market, leaving only the largest suppliers profitable. Profit margins on lead frames were reduced to single digits, whereas most semiconductor companies’ margins trended toward 50%. Lead frame volumes peaked in the 1990s and early 2000s, concurrent with the push toward high-speed IO and the invention of BGA assembly. High-speed I/O protocols, such as PCI Express, multi-gigabit Ethernet, SATA, SAS, sRIO, and others, have demonstrated that wire bonds limit performance. The IO standards and other new standards coming online had performance roadmaps that wire bonds would never have met. As device speeds increased significantly, so did their power.

A wire bond distributes power from the chip’s exterior to the core. For higher-performance products becoming available in the 1990s, supplying power to the device from outside the die was insufficient. Flip-chip and BGAs with substrates alleviated the power distribution challenge by delivering power directly to the core and eliminating bond wires, thereby improving signal integrity for high-speed SerDes standards. As leadframe assemblies declined in the early 2000s, QFN assemblies emerged for lower-pin-count packages. QFNs are substrate-based assemblies that primarily use wire bonds in high-volume production. Today, leadframe assemblies are produced in far lower volumes than substrate-based assemblies. The highest cost of installing lead frame assemblies is the trim-and-form tooling. As the volume of lead frames has diminished, the cost of replacing leadframe trim and form tooling, coupled with the single-digit profit margins of offshore suppliers, has put enormous pressure to move away from lead frame assemblies altogether. 

The industry moved away from lead frame assemblies because technology performance demanded zero wire bonds, and the costs of continuing to produce lower-volume lead frame assemblies were prohibitive. 

Once an assembly solution is in place, a test solution must also be viable. Consider the same trends in tester technology that enable the transition to substrate assembly testing, where disconnects may result in obsolescence. The newest handlers for production Test are primarily geared toward substrate-based assemblies. Efforts to reduce costs for volume production are currently based solely on substrate assemblies. Test for lower volume production at an OSAT location is less feasible as volumes diminish, especially if that product is lead frame-based. 

Assuming wafer availability, what if a company acquired an existing OSAT supply chain to continue providing the same semiconductor product?

This is what Rochester Electronics believes is a short-term solution. Recall the manufacturing puzzle pieces we have examined, from lead frames and assembly to testing. If any link in the OSAT chain is deemed economically infeasible, an obsolescence event is expected. The risk of obsolescence increases because any company supporting the OSAT supply chain cannot drive product volume as the original semiconductor company would have. Therefore, that company cannot leverage the same level of product continuation. In the short term, OSAT chain management can keep a product in production, but it is not typically viable in the long term.

Partnering with a licensed semiconductor manufacturer, such as Rochester Electronics, can mitigate the risks of component EOL. A licensed manufacturer can produce devices no longer supplied by the OCM. When a component is discontinued, the remaining wafer and die, the assembly processes, and the original test IP, are transferred to the licensed manufacturer by the OCM. This means that previously discontinued components remain available, are newly manufactured, and fully comply with the original specifications. No additional qualifications are required, nor are any software changes. 

Find out more: www.rocelec.com

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Seeing clearly is essential for education, employment and a general sense of wellbeing. In many parts of the world, getting eyeglasses that fit properly can be a luxury good. A simple pair of prescription glasses can cost weeks or even months worth of income. For children, that means learning becomes harder; for adults, work becomes less possible. A overlooked problem, left unsolved, becomes a generational barrier to success.

GoodVision (EinDollarBrille), a nonprofit organization headquartered in Germany, is working to change that equation through engineering, local empowerment and thoughtful design. Their mission is as straightforward as it is ambitious: make vision care accessible to people who would otherwise never receive it.

At the center of the initiative is a remarkably simple and durable pair of glasses. The frame is made from lightweight, flexible wire that is bent into shape using a portable mechanical forming machine. The lenses, which are generally the most expensive and technically precise component, are standardized in shape and “clicked” into the frames based on the user’s prescription.

Sabine Adams, Design Engineer at GoodVision, explains, “We go out with vans and people that do the testing and have the glasses with them. And so, we can go anywhere and do the testing and provide the glasses in one step.”

This simplicity is not an accident. It’s the result of iterative design rooted in a clear guiding principle: if the glasses are going to help the people who need them most, they must be buildable anywhere.

Simplicity by Design

The bending machine is the backbone of the GoodVision system. It requires no electricity, no specialized infrastructure and minimal training to operate. A single machine can travel in a small van to remote rural areas where medical resources and infrastructure are scarce. The team performs vision tests on-site, selects the correct lenses, bends the frame, and assembles the glasses — all in one visit.

That “one visit” concept matters. In regions where travel is time-consuming and expensive, asking someone to return later for their glasses is often unrealistic. GoodVision eliminates that gap by creating custom-fitting glasses in real-time.

The idea originated with a German schoolteacher, Martin Aufmuth, who noticed low-cost reading glasses in a dollar shop and wondered, “If a pair of glasses could cost so little here, why were they inaccessible to millions elsewhere?” With no background in industrial manufacturing, he began experimenting in his basement, shaping prototypes by hand, and seeking a way to make them repeatable and scalable.

Designing a low-cost frame was only the first step. It needed to be manufacturable under a wide range of conditions, consistent enough to meet medical quality standards and durable enough for real-world wear. That led to the creation of the bending machine and eventually to multiple generations of improved models.

Simple Designs Still Need CAD

To achieve this level of repeatability and reliability, GoodVision used Designcenter Solid Edge from Siemens to develop their frame-bending device as well as the glasses. Aufmuth had been part of a school that was partnered with Siemens, so the transition from using the software in education to using it for philanthropic ventures was obvious. Now the organization uses Solid Edge X Premium. GoodVision also receives support from their Siemens Solution Partner, Var Group, who assisted the organization with joining the Siemens’s start-up program, and continues to provide professional support for any user issues with Solid Edge.

Leveraging Solid Edge has allowed volunteer engineers to build, refine and test designs digitally long before they reach the field. It also ensures that every component, from the frame hinge to the tiny locking fit of the lens interface, can be manufactured with the precise tolerances required for medical equipment, even in the field.

“It’s a medical product, so we have to test the glasses,” Adams explains. “For example, the insert is set up in a special way so that they always fit and we have to have certificates for that. And in some countries, we are not allowed to sell the complete glasses without certification. To get the certifications needed, we had to provide all the designs, the drawings of everything with tolerances. You need to provide how you test your product afterwards, so we not only designed the machine, we also designed tools to test our product and tools for additional tasks.”

The organization has now gone through five major generations of the bending machine. Each version focuses on refining ease of use, cost efficiency and manufacturability. Sometimes progress means tighter tolerances. Other times it means widening them to reduce costs without sacrificing function or certification.

Precision in the Field

GoodVision has now supplied more than a million pairs of glasses worldwide in countries such as Burkina Faso, Nepal, Brazil and India, just to name a few. But scaling also requires quality control, especially when it comes to medical equipment. Lenses are sourced from overseas manufacturers, and each shipment must be inspected to ensure consistent fit with the frame system. To make this process volunteer-friendly, the organization designed physical go/no-go testing gauges that indicate whether the lenses meet required specifications without requiring calipers or specific technical training.

Turning precision engineering into repeatable, human-centered workflows is where GoodVision has really taken hold.

The organization intentionally does not give glasses away for free to most adults. Charging the equivalent of one to three days’ wages ensures that the glasses carry value, supporting dignity rather than dependency. For schoolchildren, the glasses are provided at no cost because GoodVision views education as a foundational form of economic opportunity. That’s why they have developed this pricing structure to be thoughtful, culturally sensitive and rooted in long-term sustainability.

Scaling Across Continents

GoodVision now operates in multiple regions across Africa, India and South America. The challenge ahead is not just engineering, it’s adaptation. Each region has its own cultural norms, logistical realities and operational landscapes. Ensuring consistent standards across different countries while maintaining local autonomy is one of the organization’s most significant ongoing efforts.

Yet the mission remains to empower communities to produce glasses locally, using local hands, for local needs. That’s why the organization is looking to continue to grow in a number of ways. “Right now we have three different sorts of glasses, and we are looking into more of the design,” Adams says. “There’s a lot to develop at that point. We also want to continue to make the testing easier, when the frames are done, to really do the quality check.”

GoodVision reminds us that engineering is not just about designing products. It’s about designing systems that remove friction, empower communities and honor human dignity. And sometimes, the most powerful tools are the simplest ones.

To learn more, visit Designcenter Solid Edge from Siemens.

The post Simple Design for a Complex Issue appeared first on Engineering.com.

Designing modern aircraft requires extreme precision. Even a small design oversight can have severe consequences, from safety risks to costs in hundreds of millions. Long development cycles stretching years and involving thousands of interdependent components mean that minor changes can cascade across structural, aerodynamic and avionics systems.

Traditional digital design workflows often compound these challenges. Different engineering teams typically work in parallel on separate 3D CAD models, creating gaps in communication and interpretation. Without a unified spatial understanding of the aircraft, assumptions about interfaces or material properties can go unverified until late-stage reviews or physical prototype builds. At that stage, identifying and resolving issues becomes expensive and time-consuming, especially when iterations involve new tooling, complex composite structures or tightly integrated subsystems.

Siemens’ NX Immersive Designer, combined with the Sony XR head-mounted display, directly addresses these challenges by placing designers and stakeholders inside a unified, full-scale virtual environment. Instead of interpreting geometry on a 2D monitor, teams can walk through the aircraft, evaluate integration decisions in real-time and validate ergonomics and routing with far greater confidence.

One of the most immediate benefits is restoring a true sense of scale. Aerospace spans from large airframes to compact avionics bays and understanding spatial relationships is critical. Traditional 3D CAD simply cannot convey the physicality of an 85-ft wingspan or the constraints inside a cockpit. Immersive Engineering brings that intuition back.

Immersive Engineering for a blended wing body aircraft

A compelling real-world example comes from Natilus, a California-based startup developing next-generation remotely piloted cargo aircraft. Its blended wing body (BWB) design aims to deliver 50 percent more internal volume and 50-60 percent lower fuel consumption than conventional designs.

Using Siemens NX Immersive Designer with Sony’s XR headset, the engineering team could visualize the digital twin of their 85-foot-wingspan aircraft directly in their hangar. Wearing the XR headset, engineers walked around and inside the virtual airframe to examine components as if the prototype physically existed.

For example, designers reached into the cargo hold to place or rearrange components and evaluate fit. This hands-on, spatially aware workflow makes it far easier to spot interference issues or ergonomic constraints that are often overlooked in 2D drawings or traditional CAD reviews.

Perhaps the transformative benefit was the reduction in design cycle time. Issues identified during an immersive review can be addressed immediately because Siemens Immersive Designer is an integrated extension within the Designcenter NX CAD software. Any changes made during the immersive session are reflected in the master 3D model in real time. This instant feedback loop shortens iteration cycles significantly compared to traditional methods.

Immersive Engineering has also proved valuable for communication and collaboration with non-engineering stakeholders. Natilus could bring a laptop and the Sony XR headset to investor meetings or customer sites and effectively “bring the aircraft with them.” Demonstrating the aircraft’s interior space, loading mechanics and container configuration at true scale accelerated understanding and alignment.

“Natilus is one of the early adopters of this technology. With immersive tools, Natilus can virtually configure each customer’s containers inside the aircraft, walk stakeholders through the layout and even show animations of how cargo is loaded and unloaded,” says Ben Widdowson, Head of Marketing Immersive Engineering at Siemens.

Even before completing their prototype, Natilus secured more than $6 billion in initial orders for over 400 aircraft from major airlines and integrators. The immersive demonstration played a key role in building confidence. For instance, customers could validate that their standard shipping containers fit within the angled BWB cargo hold and test variations of loading sequences digitally.

This type of interactive, customer-centric validation was nearly impossible without a physical prototype in the past. Immersive Engineering now allows aerospace companies to optimize design decisions collaboratively well before manufacturing begins.

Conclusion

Immersive Engineering is emerging as a necessary evolution in aerospace development. As demonstrated by Natilus, real-time, full-scale interaction with digital aircraft twins enables accurate component placement, ergonomic evaluations, and system validations. By integrating engineering workflows with intuitive spatial understanding, immersive tools aim to reduce design risks, accelerate decision-making, and create new pathways for stakeholder engagement.

“When designers can experiment with configurations and evaluate digital twins upfront, it lowers program costs by minimizing early physical prototyping and ultimately opens the door to greater innovation in complex defense and aerospace programs,” Widdowson concludes.

Visit Siemens to learn more about Immersive Engineering with NX CAD.

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Traditional CAD tools have always been constrained by flat screens, 2D interactions and limited spatial feedback. Engineers interpreting complex geometry through a monitor often struggle to judge scale, evaluate fit and identify interferences. As products grow more complex, these limitations push decisions later into the design cycle and shift many errors downstream into physical prototyping.

“Engineers can zoom in indefinitely within a 3D CAD setting, but that also means you can quickly lose perspective on what you’re looking at. As a result, design flaws remain hidden until physical prototypes are built, whether you’re working on boats, airplanes and cars, or on compact consumer electronics,” says Ben Widdowson, Head of Marketing Immersive Engineering at Siemens.

Immersive Engineering solves these challenges by providing an intuitive environment for designers to assess geometry, ergonomics and assembly intent. Siemens is among the first to integrate Immersive Engineering and AI-driven assistance into a mainstream CAD environment through its Designcenter NX platform.

Siemens AI-enhanced Immersive Engineering platform

Siemens has long been integrating immersive capabilities as an optional module into its Designcenter NX platform. It transforms product development from a visual add-on to a fully operational engineering environment. The Immersive Designer lets users open assemblies at a true scale, modify geometry and collaborate with remote teams.

A major enabler is the purpose-built Sony XR headset designed specifically for engineering workflows. “Sony built a mixed-reality headset specifically for engineering workflows that focuses on all-day comfort, ultra-high-resolution displays and controllers tailored for precision work,” Widdowson adds.

This integration addresses one of the most significant gaps in earlier generations of VR tools: the inability to perform real engineering tasks. Siemens’ approach treats immersiveness as an alternate mode of CAD, and not an isolated experience. “Users can do everything they would normally do on a desktop, but fully immersive and collaborate in real-time,” Widdowson explains.

AI adds another dimension to this environment. Siemens is developing a foundational engineering model capable of interpreting 3D geometry, design intent, bills of materials and manufacturing rules. These are some of the areas where generic LLMs like ChatGPT and Gemini have limited understanding.

This underpins tools like NX Copilot for natural language assistance, automated DFM (Design for Manufacturing) advisors that flag manufacturing issues and ML-based productivity features such as adaptive UI and selection prediction.

“We’re developing our own foundational model that can connect to LLMs while teaching them the language of engineering. It allows AI to understand a customer’s specific products and processes, while drawing on Siemens’ aggregated industry knowledge and the broader capabilities of public models,” Widdowson notes.

Case Study: BAC Mono Supercar

The immersive tools are already in use. Briggs Automotive Company (BAC), the boutique British automaker behind the Mono supercar, demonstrates how Immersive Engineering accelerates real-world product development. As they engineer the next-generation Mono, the team uses NX Immersive Designer to evaluate and refine cockpit ergonomics, packaging and regulatory compliance.

By putting on the Sony headset, BAC designers can sit in a virtual driver’s seat and see the cockpit exactly as a driver would. They can test reach, visibility, pedal comfort, steering-wheel positioning and spatial feel with full-scale accuracy. One standout use case is the ability to reposition interior components on the fly in an immersive setting.

Designers can move the steering wheel, adjust seat geometry or reposition the pedals using the hand controllers. At the same time, other experts such as ergonomists, manufacturing engineers and regulatory reviewers, can join the same immersive session. This collaborative environment is important for navigating global compliance requirements.

“They had to meet a wide range of global regulations, so they described a design review where designers, engineers and even manufacturing stakeholders all joined the same immersive session. They evaluated something as simple as headlight placement, and whether it still meets regulations, without anyone needing CAD expertise,” says Widdowson.

Conclusion

Immersive Engineering is far more than a flashy new way to look at models. It is proving to be a transformative technology that, when combined with AI, can compress development cycles, reduce errors, and improve collaboration across the product lifecycle. The Siemens Designcenter NX integration with the Sony XR headset shows how Immersive Engineering is being used in real workflows.

“Our view is that in ten years, Immersive Engineering won’t be a new capability at all. It will simply be the way engineers work, just as naturally as using a desktop today. Our customers build everything from smartphones to airplanes. As the next generation of engineers enters the workforce, we see it as our responsibility to make engineering more exciting, intuitive and engaging,” Widdowson concludes.

Visit Siemens to learn more about Immersive Engineering with NX CAD.

The post How is Immersive Engineering transforming product development? appeared first on Engineering.com.

In Estonia, craftsmanship has never been just about making products. The country’s forests, traditions and work ethic have shaped creative practices for generations. Artem Arbor, a small woodcraft company founded by two friends, sits firmly in that lineage. While the brand produces laser-cut wooden toys and decorative pieces, the story behind Artem Arbor is less about commercial scale and more about making things.

At the center of that story is Märt Tammisaar, who balances roles as both teacher and craftsman. “I’m a teacher, and I also have a small hobby company,” he explains, describing how Artem Arbor began as a passion project outside his day-to-day work.

The name Artem Arbor comes from the Latin for “art wood.” The company was never conceived as a high-stakes startup or a shot at instant financial success. Instead, it emerged from curiosity, collaboration and the kind of creative problem-solving that happens when people have the freedom to tinker. “I teach what comes before engineering — simple tools, woodcraft, metal craft and their machines — in the eighth and ninth grade. For example, they design their own key chain, and I cut it out with the laser using plexiglass.”

That tinkering mindset didn’t appear out of nowhere. Before stepping into teaching, Tammisaar spent summers doing physically demanding industrial work like “sewer” welding while getting exposure to CAD with the military.

The experience left him with a deep respect for hands-on skill and generally understanding the need for practicality in design. It also shaped how he approaches craft today. “It really helps you when you design something,” he says. “You know how something works and how this piece comes together with that one.”

This blend of practical knowledge and thoughtful design is visible in Artem Arbor’s products. The company focuses on objects that are tactile and intentional. The products reflect Estonia’s broader cultural relationship with nature and making, where craft is not nostalgia, but continuity.

New Iterations and New Products

Even small craft brands require strategy and adaptation. Artem Arbor has developed and iterated on many products over time, sometimes with surprising results. One of their most popular items — a miniature stable — was originally a side idea, not a flagship product.

“That was just a random thought. Someone liked stables and they were popular,” Tammisaar explains. “So, we did a stable, and it’s our most popular product, not the one that we started with.”

It’s a reminder familiar to many makers that the market responds to what resonates emotionally, not just what is clever on paper. “You may think one way, but the customer is the other,” he adds.

Artem Arbor’s goal has not been rapid expansion or high-volume manufacturing. Estonia’s market is small and the company intentionally looks beyond national borders to find a broader audience, but growth is measured differently. “You want a self-sustaining company… to be able to do what you want to do,” Tammisaar explains.

Sustainability, in this sense, means time to create, refine and explore. Time to collaborate. Time to maintain the machines, solve problems and keep the workshop running. As Tammisaar puts it, with a laugh, “I’m the one who makes the machines go. If there’s maintenance and there’s something wrong with it, then I’m the guy.”

Meanwhile, his business partner is the one who handles much of the day-to-day making and ideation. Their combined efforts have led to the creation of a micro-factory for their wooden widgets and toys. It’s a partnership that isn’t built on defined roles, but rather on trust and complementary strengths.

Designing with Digital Precision

While Artem Arbor’s identity is rooted in traditional craftsmanship, digital design plays a quiet but vital role behind the scenes. Like many small businesses blending art and engineering, the team uses Siemens Solid Edge to visualize and refine concepts long before a single board is cut.

The software’s modeling environment allows them to move fluidly between idea and execution, iterating on tolerances, joinery and geometry digitally. Then with digital designs, they can easily mass produce their products on a CNC laser cutter. For a small organization, that precision shortens the gap between imagination and material.

What makes this approach valuable isn’t automation or making millions of parts, it’s control. Solid Edge’s combination of history-based and synchronous modeling lets Artem Arbor design like makers, not machine operators. The result are products that maintain a handmade soul while benefiting from engineering-grade accuracy and tools.

This collaborative approach extends to Artem Arbor’s relationship with its audience. The products feel personal because they are. They are shaped by the needs and curiosities of real people, carefully calibrated in small batches and designed to last. This is not factory production. It is something smaller and more deliberate.

Educating Leads to Good Business

Tammisaar teaches, designs, builds, repairs, experiments and adapts. His practice shows that craft can evolve without losing its grounding, and that independence in work is not only a financial condition, but a philosophical one.

Ultimately, that’s what makes Artem Arbor compelling. It isn’t trying to be something louder or flashier than it is. It is a small workshop making meaningful objects, shaped by the lived expertise of a team who has worked on making in both the digital and physical worlds.

“The last time we had the Estonian teachers conference, the shop teachers were at my place in school, and I had a little workshop where I showed them what we can do with CAD and lasers, which the other teachers would know well,” Tammisaar explains. “But I compiled all the things I did with TinkerCAD (for the younger students) and Solid Edge (for the older students) and compiled them into one room. There was 3D printed stuff, laser cut stuff, and then there was the CNC milled stuff, and their jaws dropped. They haven’t seen that much stuff done with machines in a school shop.”

As he builds both his business and his educational repertoire, Tammisaar seems to be hitting the sweet spot with digital and hands-on work. In the end, he embraces his teaching with a different perspective because he is using the same tools to both teach and grow his business.

Visit Siemens to learn more about Solid Edge for Startups program and the Solid Edge Maker Community edition.

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Manufacturing productivity has long benefited from automation, with factories regularly incorporating robotics and software-controlled equipment into their production lines. Many argue that factories could realize even greater efficiency gains with an open architecture for industrial automation. Software-defined manufacturing (SDM) is a growing area of interest, and it may be a method to enable technologies including artificial intelligence (AI), robotics automation, and data analytics.

A recent white paper, Software Defined Manufacturing: Enabling Industrial Automation aims to explain the basics of SDM, how it relates to the concept of the “digital twin,” and how it can be enabled by the efforts of the Open Process Automation Forum^TM (OPAF) and other industry-standards bodies. The paper also reviews an application example of the smart factory, as well as some of the interconnect products and technologies that enable industrial automation and chart a path to the future of software-defined manufacturing [1].

What is Software-Defined Manufacturing?

SDM includes a layer of software that oversees all manufacturing processes, from initial building of parts to final assembly and testing. The necessary hardware includes sensors, cameras, and robots throughout the factory that feed back data into the control hardware and application software. The aim is to optimize the manufacturing process, making it more flexible to support product changes and prototyping.

The critical difference between SDM and traditional hardware-centric manufacturing is the ability for operators to have a unified view of the entire production floor. Instead of optimizing individual hardware systems for a particular task, OEMs can now also optimize the entire production line, from build, to assemble, to test [2].

Benefits of an Open Automation Ecosystem

An open automation ecosystem allows OEMs to combine best-in-class components and software from a range of suppliers rather than a single vendor. This allows flexibility in choice of supplier, simplifying service and process automation, and implementing control logic across the factory—a key enabler for SDM and allowing IT services to track and trace throughout the factory [3].

In addition, standard interfaces enable OEMs to swap out existing components with new ones. This can shorten engineering and commissioning time, and modularity reduces costs during process scale up. All of these benefits can improve total cost of ownership for automation equipment in manufacturing facilities.

Enabling Products

Many industrial automation system designers choose Samtec’s Tiger Eye connectors, specifically series TFM/SFM, because they are proven for use in small, high-reliability, high-cycle, rugged applications [4]. Tiger Eye connectors can be equipped with additional ruggedizing options such as screw down, weld tab, and solder nail. In addition to being part of Samtec’s Sudden Samples program, TFM and SFM Tiger Eye products are available from Samtec’s Reserve® program, shipping quantity orders in 1 day.

Another popular product to support industrial automation systems is Samtec’s board stacking connectors, where header and socket systems are available in a variety of pitch, density, stack height, orientation, and other standard or modified options [5]. For instance, post height and body positions are specified in 0.13 mm increments, as part of the standard ordering process. Series FW micro board stackers, for example, mate with CLP low profile, dual-wipe sockets with up to 50 pins per row.

Samtec’s industry-leading expertise in rugged/power and high-performance interconnect systems, combined with on-going Extended Life Product and Severe Environment Testing initiatives, enables quick-turn, cost-effective options for the performance, reliability, and durability demands of industrial automation applications, including enduring high vibration, high power, and high mating cycle systems in small form factors.

For more information contact 1.800.CALL.TTI and visit Samtec at TTI.

References

[1] Software Defined Manufacturing: Enabling Industrial Automation – White Paper
[2] Demystifying Software-Defined Manufacturing – Bright Machines
[3] Open Automation: Where Things Stand in 2024 | Automation World
[4] Micro, Rugged Industrial Connectors: Do They Exist? – The Samtec Blog
[5] Using Board Stacking Connectors in Industrial Applications – The Samtec Blog

Sponsored Content by TTI

The post How Software Defined Manufacturing (SDM) Enables Industrial Automation appeared first on Engineering.com.

Doing things the way they have always been done is no longer enough to manage rising operational costs, production process inefficiencies, and a tight labor market. Digitalization and automation are the game changers to navigate these challenges. Manufacturers can bolster their automation systems to guarantee adaptive and flexible production, helping their business stay profitable and competitive. Contrary to popular belief, modernization does not necessarily involve replacing every single piece of old equipment with shiny, new machines. 

Most manufacturers have many legacy plants which operate a diverse pool of machinery. And factories that have successfully incorporated modern automation processes had antiquated equipment which lacked the more advanced capabilities of more modern machines such as IoT connectivity and AI integration. So, where did they start?

Achieving a more automated factory that is ready to face a volatile landscape starts with a plan. With a solid plan, manufacturers can more easily incorporate automation features into production lines. To guarantee harmony between old and new systems, manufacturers should look to the comprehensive Digital Twin. Utilizing the simulation capabilities of the comprehensive Digital Twin makes automation integration seamless and hassle free, enabling a wide range of resource-conserving testing capabilities and bringing agile, resilient operations onto the shop floor. 

Starting small, starting flexibly

Beginning a digital transformation journey leads to growth through improved efficiency and increased profitability. Becoming a digital enterprise has the added benefits of increasing productivity, improving operational efficiency, and reducing costs. It also gives organizations a chance to upskill employees while improving worker job quality and pay. However, while enhancing the versatility of the factory comes with plenty of advantages, the investment may seem intimidating at first glance.

Fortunately, this is where the comprehensive Digital Twin – the foundation of digital transformation—comes in. The comprehensive Digital Twin is a virtual representation of a product throughout its entire lifecycle, from design and production to performance. It ensures end-to-end data continuity between all stakeholders enabling cross-domain collaboration, traceability, and closed-loop feedback.

As well, the production Digital Twin is a key component of the comprehensive Digital Twin and provides a great starting point for brownfields to begin their digital transformation journey. Leveraging the Digital Twin’s simulation capabilities, they can see impressive gains from more modern forms of automation in the digital world to determine what technologies can be introduced without much interruption to their existing processes or before making any significant investments. With the power of the Digital Twin and AI, implementing adaptive automation is a worthwhile venture.

One of the key areas that companies can exploit for driving production efficiencies is with Robots.      Manufacturers that are intimidated by a full upheaval of their factories can instead look to collaborative robots, also known as cobots, or robots that aid human workers during production. Cobots work as a conduit between manual and automated operations and can be easily introduced into a brownfield environment. Using cobots, brownfields can:

• Improve the efficiency and profitability of their production processes through defect detection, data collection, and error reduction
• Alleviate workforce woes by supporting skilled workers and reducing the need for repetitive tasks
• Increase flexibility and adaptability and ultimately lower costs through scalable solutions and easy reprogramming

Cutting costs with virtual commissioning

The question becomes how best to introduce Robots and Cobots in an existing factory? It is crucial to test how and where certain processes will work before integrating Cobots, new machines, or processes onto a more traditional shop floor. The Digital Twin of the factory creates an accurate, real-time virtual representation of their factory that is both comprehensible and accessible for workers across teams and disciplines. Equipped with the near-accurate representations of potential modifications, engineers and designers can explore and then validate prototype systems and production lines to ensure they are both more productive and safer for human workers on the shop floor. 

Virtual commissioning and robot offline programming can significantly reduce the time and effort required to implement the latest automation processes into existing production environments. A Digital Twin empowers manufacturers to make informed decisions in the virtual world before investing in physical builds. A variety of trial runs of potential new systems can be done quickly without having to divert actual equipment from operations. On top of that, simulated verification can be completed sometimes within days, making it possible to have more optimized and flexible systems very quickly. 

Once the manufacturing line is up and running, the Digital Twin can be enriched with ongoing, real-time data from factory operations. Enabling factories to simulate, predict, and optimize performance in real-time helps manufacturers anticipate equipment failures before they happen. This minimizes, or even avoids, costly downtimes as maintenance can be completed before any critical errors occur. 

With the Digital Twin simulating production systems, manufacturers can focus on safely and effectively incorporating these machines into their more manual production lines. Virtual commissioning enables the factory to forecast human interactions with automated systems, improving ergonomic design and safety. By deploying these factors, brownfields have been able to introduce new, state-of-the-art equipment only where needed, quickly and at low cost.

Training robots quicker in virtual classrooms

When working in tandem with AI, the Digital Twin can also accelerate robot training and programming through the industrial metaverse, a virtual space that expands on the physical world which fosters efficiency, productivity, sustainability, and connectivity. The industrial metaverse is still new, but its training capabilities for robots are unparalleled. 

Taking full advantage of the industrial metaverse’s simulation abilities, manufacturers can create immersive settings that perfectly imitate physical factories and production lines. In this virtual classroom, robots can practice tasks, address common challenges, and develop problem-solving skills in just hours, rather than months or even years.

Unlike physical environments where engineers are limited by both time and tangible constraints, simulated environments provide settings with no restrictions, enabling robots to learn to tackle even unanticipated problems. Additionally, since the virtual classroom is digitally constructed, creating training scenarios is quicker and more cost effective than setting them up in the real world. 

Virtual classrooms are not only reducing risk and operational costs but also could potentially prepare robots to create tomorrow’s products. The Digital Twin and industrial metaverse aids deployment of automation systems with dramatically reduced setup times, meanwhile, the enhanced adaptability of AI-powered tools aids the versatility of product lines in response to changing market demands.

Bringing in AI to accelerate towards the future

Once the Digital Twin is well integrated into the factory, AI can supercharge the factory’s operations. Solutions like AI Expert Toolbox can address AI makers as well as AI users. AI makers have dedicated know-how in building AI models. AI Expert Toolbox supports bringing and operating these models on the shop floor in an industry-grade environment.

On the other side for AI users, there will be dedicated services like Citizen-AI, which combine specific AI applications and allow everyone on the shop floor to run AI-based solutions with the help of improved user interfaces, understandable monitoring, automated model retrain, and more. 

Using AI together with the Digital Twin, organizations have crafted techniques that improve robot versatility. Solutions like SIMATIC Robot Pick AI can transform standard industrial robots into complex, agile machines. Pick AI harnesses both AI and Digital Twin capabilities. Trained on synthetic data and through computer visions, Pick AI prepares robots to handle unpredictable tasks with over 98 percent accuracy.

Keeping it cheap and simple

The Digital Twin has helped manufacturers make massive strides in their journeys to accelerate modern automation and enhance resilient, adaptive operations. Using the Digital Twin, factories can gain new insights due to the combination of physics-based simulations with data analytics in a fully virtual environment. This makes it possible to realize innovations faster and more reliable, while also requiring significantly fewer real prototypes.​

Leveraging the simulation abilities of the Digital Twin and AI, adopting innovative automation routines becomes seamless, hassle-free, and accessible while adding significant improvements in efficiency and productivity. Jumpstarting your factory’s digital transformation journey and reaping the rewards of automation is only a click away. 

About the author:

Rahul Garg is Vice President for Industrial Machinery Vertical Software Strategy at Siemens Digital Industries Software.

 As a customer-centric leader, one of Rahul’s great joys is helping simplify complex problems for customers and enabling success by delivering powerful, effective solutions that support small and mid-sized businesses.

Throughout his career having worked at three start-ups and now a large enterprise, Rahul has worked closely with SMBs and in technology-led industries to overcome key challenges and drive revenue growth with strategic solutions, smarter services, and better business practices.

Connect with Rahul

Sponsored Content by Siemens Digital Industries Software

The post From brownfield to smart factory: how to retrofit the past for the future appeared first on Engineering.com.

Modern defense systems depend on a complex network of modular electronics. At the core of this technology is the VITA Standards Organization, which leads the development of open standards for embedded computing, including the VPX architectures used throughout military and aerospace applications. These standards define how boards, connectors, and backplanes fit and function within rugged environments. Building on that foundation, the Sensor Open Systems Architecture (SOSA) Consortium brings together government, industry, and academia to align system architectures across radar, communications, electronic warfare, and signals intelligence systems.

“Open standards are vital because they eliminate vendor lock-in, accelerate technology refresh cycles, and enable interoperability across platforms and suppliers,” says Domenic LoPresti, Director of Engineering at Amphenol SV. “For defense programs, that means faster deployment, reduced cost, and the ability to integrate best-in-class technologies from multiple vendors without starting from scratch.”

SV Microwave contributes directly to the development of both VITA and SOSA standards, lending its engineering expertise in RF interconnect design and testing. The company helps define test protocols, connector mechanical envelopes, and RF performance benchmarks that guide how connectors are built and evaluated.

“One of the biggest challenges is balancing signal integrity at high frequencies with the mechanical robustness required for harsh military environments,” says LoPresti. “Our goal is to ensure that when system designers choose VITA/SOSA-compliant hardware, they have absolute confidence in performance from DC to millimeter-wave frequencies.”

SV Microwave produces several connector types tailored to different performance needs, balancing size, frequency, and durability. The SMPM series is commonly used in VPX backplane applications where engineers need a compact connector that still provides strong mechanical performance and power handling. The SMPS series offers a smaller footprint while maintaining excellent electrical performance at higher frequencies.

SV Microwave has recently added NanoRF to its VITA 67.3 connector family. Able to support up to 20 RF connections within a single slot, NanoRF is the highest-density VITA 67.3 series. This ability to route a high number of RF connections within a single VPX slot without compromising signal integrity makes it well-suited for next-generation radar and signals-intelligence payloads.

To support system design and prototyping, SV Microwave has backplane developer kits, complete with ruggedized cable assemblies, and edge-launch components that help engineers integrate connectors easily into their system designs. The company also takes a system-level approach to testing.

“We don’t just qualify a connector in isolation—we test it as part of a VPX module or chassis, validating signal integrity, mating cycles, thermal performance, and shock/vibration compliance,” says LoPresti.

The verification process employs 3D electromagnetic simulation, environmental qualification, and electrical and mechanical testing to confirm that every design meets VITA and SOSA performance requirements. In addition to its internal validation work, SV Microwave provides testing tools, validation kits, and installation and removal tools to help engineers verify compliance within their own systems.

SV Microwave’s contributions to standards development are reflected in its work on the VITA 67 family of RF interconnects. “We helped define test methods for insertion loss, return loss, and durability under military environmental conditions,” says LoPresti. “These protocols are now widely adopted by system integrators and ensure that all compliant products deliver consistent, repeatable RF performance.”

The company actively sits on SOSA committees that help establish the appropriate RF signal contact types and I/O interfaces for open-architecture systems.

As VITA standards continue to evolve, two upcoming specifications—VITA 90 and VITA 100—aim to increase the speed and density of modular interconnects. VITA 90 focuses on integrating optical and RF connections, allowing both light-based and radio-frequency signals to travel through the same hardware. VITA 100 looks ahead to even higher-speed designs.

SV Microwave continues to develop hybrid optical/RF modules that combine both signal types in a single connector. Its existing VITA 66.5 product line, which already merges optical and RF links, serves as a foundation for this ongoing design work.

SV Microwave works closely with TTI to help make standards-compliant components easier to source. “Our partnership with TTI ensures that engineers have quick access to off-the-shelf, VITA/SOSA-compliant interconnect solutions backed by deep technical support,” says LoPresti. “TTI’s distribution network makes it easy for program managers and designers to prototype, scale, and deploy systems faster without long lead times or supply chain risks. This collaboration extends beyond logistics—TTI helps us educate engineers on open standards and ensure that when they specify SV products, they’re choosing solutions already aligned with VITA/SOSA requirements.”

To learn more, visit Amphenol SV at TTI.

The post Advancing open standards for the next generation of RF interconnects appeared first on Engineering.com.

All manufacturing companies must manage an ever-growing mountain of priceless inspection data. Yet measurement results, process iterations, and approval reports are scattered across hard drives and USB sticks. We live in a digital world that advances daily, but obtaining, accessing, sharing, and tracking digital files often feels like digging through an overstuffed file cabinet—hoping to locate what you want without actually knowing if it is what you need.

Now, imagine a streamlined digital data management system where all your 3D measurement files exist in a central secure, searchable hub. Doubts and time-wasting disagreements on whether metrology tasks or reports were already done or not all vanish. This is impossible to accomplish with metrology data scattered across the enterprise on equipment hard drives or USB sticks in various locations.

Add intuitive indexing, search, and filtering tools that seamlessly retrieve data based on part number, serial number, or production line and you can be sure you’re working effectively. Gigabytes of 3D data you’ve already captured are turned into accurate, timely, and secure documentation and reports. All your invaluable inspection data stays organized, up to date, and readily available to engineering and QA teams, indeed to anyone who needs it.

The Manual Past

Surprisingly, many companies still store their 3D measurement data on the hard drives of the computers connected to their devices. This practice creates data silos, consequently amplifying the risk of errors. These measurement files can also quickly achieve gigabyte status. When manually handled, they must first be copied and zipped with retrieval instructions. Each team member, whether working on-site or remotely, must then follow those instructions and copy the file onto their own computer.

This not only creates duplicates, it strips downstream comments and actions from the context set by the inspection data. Catching a mistake or suggesting an improvement means sending it through a different communication channel. And when discussion is key to collaboration and product improvement, disconnecting it from the 3D measurement data compromises its value, delays decision-making, and weakens its overall impact.

The Digital Future, Now

Now envision a manufacturing organization working with multiple suppliers. Digital 3D data management across the enterprise means engineers and QA leads access formerly scattered data instantly. Identifying, defining, and sharing design changes boosts engineering efficiency and helps catch costly design issues early, before they escalate in production phases.

Updating, saving, and later retrieving such valuable 3D measurement data when needed also ensures efficient documentation and preserves data integrity over time. Instead of starting from scratch, teams can build on the latest model iterations as the starting point for future efforts. The ability to track and manage 3D data throughout its entire lifecycle empowers companies to make better decisions fast. Valuable insights can be extracted from the data, leading to enhanced product design, optimized processes, and ultimately, higher-quality outputs.

Advanced 3D data management brings modern digital communication features— including hyperlinks, tagging, and notifications—directly into the process. It also offers a discussion thread within every inspection project to facilitate information exchange between internal and external collaborators, no matter the physical distance.

From design engineering to the shop floor, inspection practices continuously improves, data silos evaporate, and a next-generation manufacturing company emerges.

You measure to know and grow. See what PolyWorks|DataLoop next-generation 3D data management can do for your organization. Schedule a demo today.

Sponsored Content by InnovMetric

The post Achieve Smart Manufacturing with Advanced 3D Data Management appeared first on Engineering.com.

Computer modeling and simulation has been a cornerstone of engineering innovation for decades. For applications ranging from aerospace products to consumer electronics, companies have long relied on computational models to test ideas, predict performance, and guide product development. Simulation is, at its heart, a decision support tool: data goes in, knowledge comes out, and critical choices are made with greater confidence.

But while simulation is powerful, creating and running sophisticated multiphysics models typically requires specialized expertise and expensive computational resources. As a result, simulation engineers have played a central role in turning the physics into actionable insights. However, it is common that organizations only have a small group of simulation experts, making it unpractical to have direct access to simulation across the organizations. Luckily, this paradigm is changing. The rise of simulation apps, powered by multiphysics modeling, neural-network-driven surrogate models, and GPU acceleration, is democratizing access to advanced simulation. These easy-to-use applications extend the reach of simulation far beyond R&D, enabling teams in the field, on the factory floor, and in the boardroom to make real-time, physics-informed decisions. In other words, simulation apps are no longer just about engineering; they’re becoming indispensable business tools as well. 

From Models to Apps: A Shift in Accessibility

The traditional workflow of simulation engineering has always been about precision. Whether focusing on a single physical phenomenon or coupling multiple domains together in multiphysics models, simulation engineers aim to capture reality as faithfully as possible. Single-physics simulations can provide excellent accuracy when one effect dominates, while multiphysics simulations enable engineers to include interacting effects for an even greater level of realism. Models are then validated with experiments and used to forecast behavior under a wide range of conditions, delivering confidence in their predictive power. With apps, validated models are encapsulated in streamlined interfaces, enabling users to simply enter parameters into intuitive fields (e.g., geometry, material properties, operating conditions) and receive precise results in real time. These apps make it possible for nonexperts to run analyses without needing to master finite element methods or specialized multiphysics software. 

To give an example of how apps make simulation more accessible, an audio supplier for luxury car manufacturers ran into challenges with evaluating how design tweaks to car interiors affected in-cabin acoustics. The organization’s engineers built a custom app on top of their core acoustics model, and instead of waiting for the simulation specialists to rerun models, a global and cross-functional team was able to simply input design changes into the app and see how sound quality was impacted. This streamlined workflow eliminated delays across time zones and kept development aligned with fast-changing car designs. 

Extending Simulation Beyond R&D

In various industries, simulation apps are increasingly being distributed across field operations, manufacturing, and even business management. For instance, one of the world’s largest suppliers of cement rolled out a simulation app for contractors that can help them decide on concrete curing times, a critical factor for both safety and profitability. The app integrates local weather data, soil conditions, and building geometry into a multiphysics model to predict curing timelines. With this app, contractors now make onsite decisions backed by physics, avoiding costly errors and delays.

Simulation apps are also being used in power grid maintenance. For instance, a utility company built an app for field technicians diagnosing cable failures. Instead of calling in simulation engineers or guessing based on limited test data, technicians input onsite observations into an app powered by multiphysics models. The app evaluates environmental and material factors in real time, enabling faster and more accurate troubleshooting and repair.

Let’s now consider additive manufacturing facilities. Factories that produce parts via metal powder bed fusion face challenges with humidity and heat control. Poor conditions not only compromise part quality but also pose safety risks due to the flammable nature of metal powders. A U.K. manufacturer built a simulation app to model its factory layout, incorporating variables like outside climate, machine placement, and operational schedules. Factory managers use the app to adjust ventilation and workflows in a way that keeps optimal production quality and worker safety in mind. 

A simulation app for predicting the conditions of an additive manufacturing facility. Image courtesy of MTC.

Another area where apps are being used is in the global food supply chain, where cold room managers face constant challenges around limited refrigeration space and food spoilage. A Swiss-led consortium used multiphysics simulation to predict fruit shelf life based on size, peel thickness, and storage conditions. The resulting mobile app provided real-time guidance to farmers and managers in rural India, cutting post-harvest food losses by 20% and boosting farmer income by the same margin.

An app forecasting fruit freshness based on multiphysics (left) and a mobile app offering insight into the expected shelf life of a crate in storage (right) based on science and real-time information. Image courtesy of Empa.

The Role of Surrogate Models

While simulation apps are powerful, running detailed multiphysics models in real time can still be computationally expensive. This is where surrogate models, often built using neural networks or other machine-learning-based reduced-order modeling techniques, benefit workflows.

Surrogate models act as lightweight stand-ins for full-scale physics solvers. They are trained on data from high-fidelity simulations and experiments and approximate the input–output behavior of the underlying model with high accuracy. Once trained, these reduced models can run thousands of times faster than traditional solvers, enabling near-instant predictions inside apps. For example, a transformer design team may need to explore hundreds of material and geometry combinations. Instead of waiting hours per simulation, a surrogate model embedded in their app can deliver results in seconds.

Harnessing GPU Acceleration

Another enabler of advancements in simulation is GPU acceleration. GPUs are designed for massively parallel computations, which map naturally onto the numerical solvers used in simulation. Simulation usually involve solving equations in millions of variables, and GPUs provide significant speedups over CPU-only computations.

For simulation apps, GPU acceleration means:

• Real-time interactivity: Users can adjust parameters and instantly see updated results, even for complex multiphysics models.
• Scalable deployment: Apps can be hosted on GPU-accelerated cloud platforms, allowing global teams to access powerful simulation capabilities without investing in high-performance local hardware.
• Support for hybrid workflows: GPU acceleration combined with surrogate models makes it possible for apps to dynamically switch between high-fidelity physics and fast approximations depending on user needs.

Simulation as a Business Tool

Looking at the business side of innovation, traditional systems rely on statistical models or linear equations to optimize inventory, scheduling, or financial planning. Apps extend this concept by embedding the fundamental laws of physics and chemistry into the decision-making framework. The result is unprecedented realism in forecasts and recommendations. For instance, rather than asking “What parts of this system do we need to change in order to minimize cost?”, business teams can ask, “How will humidity, airflow, and material properties affect part quality, cost, and safety?” Apps provide answers that account for real-world complexity, helping organizations minimize risk, accelerate innovation, and maximize performance.

Looking Ahead

The convergence of multiphysics modeling, surrogate models, and GPU acceleration is ushering in a new era of simulation. No longer siloed within R&D, simulation apps are growing as everyday tools across teams and departments. 

To summarize the business implications of these tools, we will see: 

• Faster time to market through accelerated design iteration
• Lower costs thanks to a reduced need for physical prototypes and postproduction fixes
• Broader adoption of simulation by empowering nonexperts to make physics-informed decisions

In short, simulation apps ensure that organizations can keep pace with an ever-changing world and enable smarter and faster decisions everywhere business happens.

Sponsored Content by Comsol

The post Simulation Apps: The Future of Decision-Making in Engineering and Business appeared first on Engineering.com.