When the history of engineering is finally written, scholars will talk about the various ages of technology, and up until now, they’ve largely concentrated on motive power. The “Age of Coal”, the “Age of Steam”, the “Age of Petroleum”, and the “Age of Electricity” are already part of the lexicon, but it’s second decade of the 21^st century, and a strong argument can be made for the “Age of Software”.

Particularly the development of the software defined machine, and nowhere is this more prevalent than in the automotive industry. Starting from simple control of electronic fuel injection through firmware maps, modern vehicles now contain hundreds of millions of lines of code, and coders now outnumber mechanical engineers in most automaker R&D departments. Vehicles are more capable, and are much more sophisticated, but the price of this advancement is complexity. Are modern cars and light trucks too complex? Jim Anderton has definite opinions.

You can watch Jim’s full Automotive 2026 Industry Outlook & Beyond webinar.

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Charlie is considering what his company’s response should be to today’s rapid technological change, including what they should do about artificial intelligence. He was hearing about the revolutionary impact AI would have on what seemed a daily basis. He knew that new companies were becoming established that provided new technology-based manufacturing engineering services and he wanted to ensure that this did not result in a reduction in the work done by his company. Charlie needed to understand the impact that these new technologies would have on his business and what his strategy should be to deal with it.

Digital transformation is the response that organisations are making to the Fourth Industrial Revolution (the world created by the rapid technological advance that is taking place today). This can mean changes in products, services and processes throughout the organisation. It can be small or large scale, radically changing business models and it means new technologies are being introduced throughout organisations with significant implications for engineering services organisations.

Engineering services are impacted by the new environment they need to support and the new tools that are available to them to do this. A wide range of technologies may be adopted in the organisation in areas that are within the scope of the work normally done by engineering services. These might include the development, implementation and support for new technology enabled processes, new automation and new decision-making systems that may or may not utilise artificial intelligence.

At the same time, technology is changing the support engineering services provide. More data is being collected and better tools exist that can be used in predictive maintenance services. New design tools enable faster, better design, some aspects of service delivery can be automated, artificial intelligence can be used for analytics, digital twins and simulation support analytics, design and management and big data can provide valuable insights.

These developments in the environment engineers support and in the tools available to them are the main factors influencing the digital transformation of engineering services. They make it essential that engineering services organisations carefully review their current situation and develop their own strategy for dealing with it. Otherwise they will be vulnerable to other providers who emerge, better prepared for the new environment.

The Engineering Services DX Assessment Tool is a simple instrument that we have developed at the University of Waterloo to help engineering services organisations consider and plan their own digital transformation. It is intended to be facilitative – prepared on a white board or flip chart by a group of engineers. Here is a blank version:

The tool is suitable for engineering services companies and engineering services within an existing organisation. It asks you to consider the following elements:

Client/Dept: The main organisations or units the engineering services are provided to. For an engineering services company this may be their main clients or client types if they are larger. For internal engineering services this would be the units they provide services to.

Change Elements: The changes in the Client/Dept that are or will be impacted by new technology. This may be specific performance improvements, equipment changes, process changes etc.

Main Tech: The main technologies being used in the change elements. This may include internet of things, artificial intelligence, digital twins, automation etc.

Implement Support: The support needed to implement the change described in the Change Elements column, such as design work, project management, impact assessment, etc.

Operate Support: The support needed to operate the change described in the Change Elements column, such as maintenance, education and training, and performance improvement.

Impact Services Now: Can your existing services provide the Implement and Operate Support that the Change Elements need now or are changes required to do this? Include here any areas of your services that may have been used by the client in the past but are not now needed due to the Change Element.

Action Needed: Review the information you have entered in this row of the chart and determine the actions that you need to take to deliver the support that your Client/Dept will require.

Charlie has completed the tool for his company, in this example:

The Engineering Services DX Assessment Tool allows you to consider the actions you might wish to take to ensure your organisation is able to continue to effectively provide engineering support. Once the chart is completed you can then consider the areas that will be your priority and become the main elements in your digital transformation strategy.

This strategy must include the impact that the Client/Dept changes will have on the skills of the members of your engineering team, along with any personnel changes you may need to make. The Client/Dept changes will require engagement and collaboration with stakeholders by engineers, utilising social skills more frequently than in the past due to the more rapid pace of change.

It should also include consideration of the technology-based tools that your team uses today (for example data analytics, simulation etc.) and investments in any new tools that may be appropriate here.

Developing and implementing your digital transformation strategy for Engineering Services is essential today. As Client/Dept organisations plan and implement their own digital transformation strategies they will consider the role existing engineering services providers can play. Be prepared with your own digital transformation strategy.

The post This low-tech tool sharpens your digital transformation strategy appeared first on Engineering.com.

Of course, that’s not how things have played out. Local Motors, which was central to the 3D printed car at IMTS, shut down in 2022. Today, the idea that our roads will soon be filled with 3D printed vehicles – even vehicles containing a substantial portion of 3D printed components – seems less likely than ever. Nevertheless, additive manufacturing (AM) still has an important part to play in the auto industry; it’s just not the one many of us expected.

Additive manufacturing uptake in the auto industry

Fadi Abro, senior director for transportation and mobility at Stratasys, distinctly remembers his first encounter with 3D printing. “I started at a company called Solid Concepts, which was acquired by Stratasys back in 2010,” he tells me. “It was literally my first day, and somebody handed me an SLA part. While they were explaining how it was 3D printed, I flexed the part ever so slightly, and it shattered. Things have changed dramatically in terms of material properties since then, but it was a quick lesson.”

No doubt there are many engineers who can recall similar early encounters with additive parts, though probably not quite so dramatic. And while additive materials have certainly advanced since those early days, those initial encounters likely shaped the perceptions of many engineers regarding the capabilities of 3D printed parts. As a result, the technology spent years largely confined to the realm of prototyping, where its lead times and capacity for iteration outweighed any issues with mechanical durability.

Of course, AM eventually found its way into other applications, specifically those involving high-value, low-volume components, chiefly in the aerospace and medical device industries. In contrast, the high volumes of the auto industry kept 3D printed parts from seeing end-use applications outside of the occasional luxury case.

As Abro sees it, part of what explains the slower adoption of AM in the auto industry versus aerospace or medical devices is that 3D printing as a technology is a double-edged sword. “The beautiful thing about additive is that it can do everything,” he explains, “The negative is that it can do everything, so people lose focus when they don’t get into it with a use case in mind.” That’s one reason that the AM industry as a whole has been shifting to emphasize specific applications of the technology over its general capabilities. In the case of the auto industry, many of the most promising applications involve jigs, fixtures, and tooling.

Automotive applications for 3D printing

“We use those terms,” Abro says, “but really it’s production support rather than production components. You can make production components on a Stratasys 3D printer but the volumes have to be low and the value of the part has to be high for it to make sense.”

However, when it comes to production support (i.e., jigs, fixtures, and tooling), the calculation of the potential value of 3D printing is different. Because the auto industry works in such high volumes, shaving seconds off of assembly times can result in six or even seven figure returns on investment. That’s why, according to Abro, “You’d be hard pressed to walk into a major OEM plant and not find a bunch of Stratasys-printed tools helping to put the cars together. Basically, the money’s in the tooling.”

What makes 3D printing such a good fit for tooling? It’s a combination of the usual advantages associated with the technology: flexibility, on-demand production, and rapid iteration. Automakers can potentially save hundreds of thousands – if not millions – of dollars in tooling costs by adopting additive manufacturing because these advantages enable them to manufacture the production supports they need and adjust them as needed without having to wait for the tooling necessary to produce them. Given that, it’s natural to wonder why, at least according to Abro, the proportion of additive tooling is still in the single-digit percentages.

“It really boils down to two things,” he tells me, “It’s awareness and confidence. Let’s say you have a Tier 2 job shop that makes a couple of different components for a Tier 1. They don’t really have the awareness that 3D printing can be industrial. They still think of it as a hobbyist’s toy. Then there’s confidence: recognizing that 3D printing can do the things that we’re saying it can do.” As an example, he cites Toyota using AM to produce plastic end-of-arm tools that would typically be fabricated in metal.

Looking a bit more closely at the automotive supply chain, the AM adoption rate is pretty much what you’d expect, with OEMs accounting for the majority, Tier 1s making up significantly less, and little to no adoption in the Tier 2s and beyond. If AM were being used for more end-use parts, that might not be the case, since the OEMs could push their suppliers more directly to adopt the technology. In the case of tooling, however, OEMs have less ability to dictate the manufacturing process, so adoption is naturally less widespread.

“It’s hard to say to a Tier 1 supplier, ‘Buy this half-million-dollar printer and you’ll recognize the revenue from it in your tooling,’” Abro explains. “They’re going to want to know that it works, and that’s what the Stratasys Tooling Center of Excellence is intended to support. If you’re a Tier 1 supplier and you have a couple of projects you want to try out, you don’t have to buy a printer. Instead, you can go to the tooling experts at the CoE to help you design and print it.”

The future of AM in automotive

Despite its 40-year history, there’s still a generational gap when it comes to how engineers see 3D printing as a technology. On the one hand, there’s the old guard who think of hobbyist machines churning out cheap plastic toys, and on the other there’s the younger engineers who grew up with 3D printing and see it as a tool that lets them tinker with designs.

As Abro notes, however, there are also the executives in between who don’t want their engineers wasting time putting glue on build plates or downloading free software to make a desktop machine work. “They want an industrial solution that just prints parts on demand,” he says, “They don’t want to see their engineers spending hours trying to make a $20 print work.”

Fortunately, we’ve come a long way from a young engineer accidentally shattering a 3D printed part on their first day. “Material development and the accuracy of the systems has been on a linear upward trajectory,” Abro claims, “especially when you look at the industrial systems.” The natural question to ask then is: What’s next?

“Our focus is going to be on size and throughput,” Abro says. “Making bigger parts faster opens up the aperture of applications, especially within the tooling space. And the specific use case in automotive will continue to be tooling, because every two to three years you have to have a brand new version of a car and that means you have to retool your plant. That’s a never ending need in the automotive industry. I’m seeing the suppliers starting to wake up and ask, ‘What’s GM doing?’ and ‘Why aren’t we doing that?’”

So, while we may never see showrooms filled with 3D printed cars, that doesn’t mean additive manufacturing won’t have a growing part to play in the future of the automotive industry.

The post Dude, where’s my 3D printed car? appeared first on Engineering.com.

The ANSI/A3 R15.06-2025 American National Standard for Industrial Robots and Robot Systems – Safety Requirements is now available and A3 says it marks the most significant advancement in industrial robot safety requirements in more than a decade.

“Publishing this safety standard is perhaps the most important thing A3 can do, as it directly impacts the safety of millions of people working in industrial environments around the world,” said Jeff Burnstein, president of A3, in a release.

This standard is available in protected PDF format and includes:
Part 1: Safety requirements for industrial robots
Part 2: Safety requirements for industrial robot applications and robot cells
Part 3: Will address safety requirements for users of industrial robot cells. It’s expected to be published later this year. Once available, it will be retroactively provided at no additional cost to anyone who purchases the full standard.

R15.06 is the U.S. national adoption of ISO 10218 Parts 1 and 2 and is a revision of ANSI/RIA R15.06-2012, which was launched by the Robotic Industries Association (RIA) before it became part of A3.

Key changes in ANSI/A3 R15.06-2025 include:

• Clarified functional safety requirements that improve usability and compliance for manufacturers and integrators
• Integrated guidance for collaborative robot applications, consolidating ISO/TS 15066
• New content on end-effectors and manual load/unload procedures, derived from ISO/TR 20218-1 and ISO/TR 20218-2
• Updated robot classifications, with corresponding safety functions and test methodologies
• Cybersecurity guidance included as part of safety planning and implementation
• Refined terminology, including the replacement of “safety-rated monitored stop” with “monitored standstill” for broader technical accuracy

“This standard delivers clearer guidance, smarter classifications, and a roadmap for safety in the era of intelligent automation,” said Carole Franklin, director of standards development, robotics at A3. “It empowers manufacturers and integrators to design and deploy safer systems more confidently while supporting innovation without compromising human well-being.”

The post Robot safety standard gets fresh update appeared first on Engineering.com.

This is why the editors at Engineering.com designed our Digital Transformation Week event—to help engineers unpack all the choices in front of them, and to help them do it at the speed and scale required to compete.

Join us for this series of lunch hour webinars to gain insights and ideas from people who have seen some best-in-class digital transformations take shape.

Registrations are open and spots are filling up fast. Here’s what we have planned for the week:

September 22: Building the Digital Thread Across the Product Lifecycle

12:00 PM Eastern Daylight Time

This webinar is the opening session for our inaugural Digital Transformation Week. We will address the real challenges of implementing digital transformation at any scale, focusing on when, why and how to leverage manufacturing data. We will discuss freeing data from its silos and using your bill of materials as a single source of truth. Finally, we will help you understand how data can fill in the gaps between design and manufacturing to create true end-to-end digital mastery.

September 23: Demystifying Digital Transformation: Scalable strategies for Small & Mid-Sized Manufacturers

12:00 PM Eastern Daylight Time

Whether your organization is just beginning its digital journey or seeking to expand successful initiatives across multiple departments, understanding the unique challenges and opportunities faced by smaller enterprises is crucial. Tailored strategies, realistic resource planning, and clear objectives empower SMBs to move beyond theory and pilot phases, transforming digital ambitions into scalable reality. By examining proven frameworks and real-world case studies, this session will demystify the process and equip you with actionable insights designed for organizations of every size and level of digital maturity.

September 24, 2025: Scaling AI in Engineering: A Practical Blueprint for Companies of Every Size

12:00 PM Eastern Daylight Time

You can’t talk about digital transformation without covering artificial intelligence. Across industries, engineering leaders are experimenting with AI pilots — but many remain uncertain about how to move from experiments to production-scale adoption. The challenge is not primarily about what algorithms or tools to select but about creating the right blueprint: where to start, how to integrate with existing workflows, and how to scale in a way that engineers trust and the business can see immediate value. We will explore how companies are combining foundation models, predictive physics AI, agentic workflow automation, and open infrastructure into a stepped roadmap that works whether you are a small team seeking efficiency gains or a global enterprise aiming to digitally transform at scale.

September 25: How to Manage Expectations for Digital Transformation

12:00 PM Eastern Daylight Time

The digital transformation trend is going strong and manufacturers of all sizes are exploring what could be potentially game-changing investments for their companies. With so much promise and so much hype, it’s hard to know what is truly possible. Special guest Brian Zakrajsek, Smart Manufacturing Leader at Deloitte Consulting LLP, will discuss what digital transformation really is and what it looks like on the ground floor of a manufacturer trying to find its way. He will chat about some common unrealistic expectations, what the realistic expectation might be for each, and how to get there.

The post Register for Digital Transformation Week 2025 appeared first on Engineering.com.

In 1908, the Ford Motor Company introduce the Model T, the first truly affordable, mass-produced automobile in history. Ford’s assembly line techniques were so advanced for the time that the Ford production system and management strategy was called “Fordism” and was regarded as the future of all manufacturing.

Today, the Ford Motor Company is attempting to do it again, with a major project to rework the massive Louisville Assembly complex into a paragon of modern automotive manufacturing, replacing the traditional linear assembly lines with a root-and-branch structure that will involve discrete assembly of major modules, based on large-format aluminum die castings. The goal is to create a $30,000 midsize electric pickup, a wide-open market that is currently unexploited.

The automotive industry is watching, and if successful, the project could give Ford a significant advantage in the transition to electric vehicles.

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The post The Model T Ford revolutionized the automotive industry. Ford is trying to do it again. appeared first on Engineering.com.

Morgan Maia, senior manager for technical partnerships at Oracle Red Bull Racing, Alba Colón, director of technical partnerships at Hendrick Motorsports, and John Church, president of JDC-Miller MotorSports sat down with moderator (and former professional racing driver and host of the YouTube motorsport engineering channel Driver61) Scott Mansell to share their unique perspectives on three different forms of motorsport: Formula One, NASCAR, and IMSA.

What follows is an edited and abridged version of their conversation.

Scott Mansell: You each represent very different forms of motorsport with very different challenges. Can you take a minute to explain your discipline?

Morgan Maia: Sure. In Formula One, the challenge is massive. We have 24 races a year, traveling around the world—from China and Japan to the U.S. and Europe. It’s difficult to always have the car in one piece because we have to trust that everything works straight off the truck without all the tools at hand.

Another challenge is the cost cap. We cannot spend more than $150 million per year. While that sounds like a lot, it goes quickly once you account for employees, parts, travel, and logistics. The challenge is to compete within those limits while ensuring both drivers perform at their best across 24 races.

Alba Colón: Can I have your budget? (laughs) NASCAR is a bit different. Imagine 40 cars running 38 weekends a year. Just last week, for the first time, we raced outside the U.S. in Mexico. We don’t only race on ovals, like in Las Vegas, we also compete on road courses and even dirt tracks. So our cars must be ready for any kind of surface on any kind of track, 38 weekends a year.

We’re holding at around 180 mph normally, with finishes sometimes separated by just 0.01 seconds between first and second place. Pit stops are under 9 seconds. So you can imagine how important precision is.

John Church: IMSA is endurance racing. We run a Porsche 963 hybrid in the Hypercar (GTP) class. Everything in endurance racing is about precision and consistency. We sometimes go through multiple body parts during a race weekend, so everything has to be built to exact specifications to ensure consistency across changes.

We start our season with a 24-hour race, then we do some shorter races that are only 100 minutes long, and we also do medium races that are two hours and forty minutes as well as some six-hour races. So whenever we’re changing parts out, it’s important that the whole car stays consistent from one race to the next throughout the weekend.

Scott Mansell: Let’s get into the technical meat of how your teams run at the top of their motorsport. Being successful in motorsports is all about measurement because you can’t improve if you can’t measure anything. So, how are you using Hexagon tools to improve your performance, both in the workshop and on the racetrack?

Morgan Maia: We use Hexagon in two main ways. First, at the factory. We’re always working with prototypes and don’t have time to test the car before heading to a race. A part might be manufactured on Thursday evening, shipped overnight, and fitted Friday morning for FP1. That means we must be absolutely sure that part is perfect, because we can’t send it back. It has to work immediately with the other 8,000 components on the car.

The second use is for regulations. We send a 3D CAD model of our car, then scan the real car at the track to overlay the two and ensure compliance. If the car isn’t in regulation, we can’t race.

Scott Mansell: So when you bolt the gearbox on, for example, you’re checking everything is perfectly aligned with the engine and chassis. What kind of tolerances are you working with?

Morgan Maia: We’re working with microns. The car is like a watch: everything must be extremely accurate. Even temperature matters. For example, if you start the engine cold, tolerances can be off enough to cause catastrophic failure. So everything must be warmed properly. Micron-level precision is how we find the extra tenths we need to win.

And the drivers feel everything. They can detect a millimeter or even a micron difference. Their feedback can sometimes be sharper than the data itself. Precision gives them confidence to push the car to its limits.

Scott Mansell: Alba, how are you using Hexagon products in NASCAR?

Alba Colón: Well, you’ll find Hexagon tools everywhere in our shop. NASCAR regulations changed a few years ago with the Gen-7 car. Before, we designed and built about 80% of the car ourselves. Now, to control costs, we buy around 80% and only design 20%.

That means we measure absolutely everything we receive: the chassis, the body, all the parts of the vehicle. Everything must be precise. Our Hexagon equipment ensures those parts meet tolerance before going out, since we’re not allowed to bring any of that equipment to the track, so we have to make sure everything we’re taking there is precisely measured.

Scott Mansell: And you’re not just measuring the bodywork, for example, to make sure it’s in tolerance. I’m sure there’s some engineering going on there to try and gain performance by mixing and matching different parts. What’s that like?

Alba Colón: Absolutely, yes. We do a lot of mixing and matching because, for example, this chassis makes more sense to use with that suspension. It’s like a chess game every week, putting together the perfect car.

Scott Mansell: John, what about IMSA?

John Church: In IMSA, when we unload at the track, we go straight to technical inspection. The whole car is scanned, top and bottom, and we’re allowed only a 3mm deviation from the datum.

So before leaving the shop, we scan the entire car and overlay it with the datum to make sure we’re within spec. If something’s off, we fix it before we even load the truck. That saves time and it means less drama with the officials. In endurance racing, everything’s precise until you start hitting things, and then when you need to replace the nose, you want to know each one is exactly the same. Consistency is what matters: your average pace is more important than your fastest lap.

Scott Mansell: Three millimeters sounds like a lot of tolerance when we’re talking about microns, but I’m sure your engineers are thinking, “Let’s go to 2.99999,” so they can get as close to the edge as possible.

John Church: Of course, you’re always trying to push the envelope where you can, but it’s more about making sure everything’s legal and, beyond that, making sure every replacement part that’s going on your car is the same as the last one so the drivers and the engineers have the confidence that it’s the same car as the previous session. If you can’t do that, that’s when the wheels start to fall off the bus.

Scott Mansell: Morgan, you mentioned the incredibly fast development cycles in Formula One. How quickly can you turn around a design to manufacturing and then get it on the actual car?

Morgan Maia: So, again, we always need to have the cost cap in mind, but we also do around a thousand upgrades on the car in a year, so almost all the parts are going to be changed between the first and last phase.

On top of that, setup varies a lot by circuit. If you look at Monza versus Monaco, the car can be almost completely different: same parts, but a completely different car. We push the setup on the track as well.

In Canada, for example, the car fared quite well in Q1, but we didn’t want to leave it at that, because maybe there’s an extra two tenths [of a second] to find. Then in Q2 we find we went a bit too extreme, so we refined again for FP3, still trying to beat FP1. So, there’s a lot of back-and-forth on the track to find the limits of the car and extract all the performance we can from it.

Scott Mansell: These changes you’re making to the toe or camber can make a huge difference in performance and drivability. How often are you making them?

Morgan Maia: There isn’t much time during a race weekend, so a lot happens in the simulator. Our drivers spend days (and sometimes nights) running laps to define the theoretical best setup. Then we reconcile that with driver preference and feel.

Alba Colón: We’re similar regarding simulators, except we can’t make trackside changes with measurement tools like you can. We only get 20–25 minutes of practice, so that’s maybe three changes at most.

At the track, you go through inspection once. If you fail, you get a second chance with the scanner. Fail again and you start losing team members or starting positions, and on some tracks that’s really not great.

Sometimes a driver goes out, does a few laps and then says, “It’s good, so don’t touch it!” And I think that’s because they’re worried we might make things worse if we chase those little changes. Of course, we always want more practice—we used to have two hours!—but now it’s 20 minutes and those are the rules of the game, so we have to do our best to take advantage of what we have in front of us.

Scott Mansell: You mentioned that you’re not allowed to take measurement equipment to the circuit, so what does the process look like when it comes back from the factory? Is it checked then or when it has a new setup for the next race?

Alba Colón: So before the car goes on the track, it goes through a scanner for a 90-second scan that’s mandated by NASCAR. Based on the color map and the tolerances, you’re cleared to race. Then, when the vehicle comes back, we scan it again to see what moved based on what we did at the track.

Within a couple of hours, the whole car is pulled apart and we take photos of measurements of everything to decide which parts will stay and which will be scrapped. By that time, the car that’s going out for the next weekend is already finished and we’re already assembling another vehicle two or three weeks in advance, so there’s constant measurement to make sure everything is working.

Scott Mansell: With such quick turnarounds, the speed of engineering must be critical.

Alba Colón: Very critical. When I left the shop last week, we were already working on the car for a race a month from now, and it’s pretty much ready. So we’re moving parts really, really quickly. If you want a job in racing, and you’re in quality control or manufacturing, trust me: we’re looking for you.

Scott Mansell: John, when your cars come back to the factory, what does that process look like for you?

John Church: Very similar to what Alba was saying. When the car comes back, the first thing we do is scan it just to see how much everything has changed from the start of the weekend. Of course, damage is always obvious, but even where there isn’t any damage, just seeing if anything moved and taking note of it to make adjustments is crucial for going forward.

I think what we’re all trying to do here is control as many variables as we can so that we can guarantee repeatability from one car to the next, one race to the next. That makes everybody’s job a lot easier because it takes the guesswork out of it.

The post Motorsport engineering insights appeared first on Engineering.com.

The report says North American companies ordered 17,635 robots valued at $1.094 billion in the first six months of 2025. Automotive OEMS led with a 34% year-over-year increase in units ordered. Other top-performing segments included plastics and rubber (+9%) and life sciences/pharma/biomed (+8%).

In Q2, companies ordered 8,571 robots worth $513 million, marking a 9% increase in units compared to Q2 2024. Life sciences/pharma/biomed posted the strongest sector growth in the quarter (+22%), followed by semiconductors/electronics/photonics (+18%) and steady gains in plastics, automotive components, and general industry.

 “It’s not just about efficiency anymore. It’s about building resilience, improving flexibility, and staying competitive in a rapidly changing global market. If these patterns hold, the North American robotics market could outperform 2024 levels by mid-single digit growth rates by the end of the year,” said Alex Shikany, Executive Vice President at A3.

Cobots’ rising influence

Collaborative robots (cobots) accounted for a growing share of the market with 3,085 units ordered in the first half of 2025, valued at $114 million. In Q2, cobots made up 23.7% of all units and 14.7% of revenue. These systems work safely alongside humans and address automation needs in space- or labor-constrained environments. A3 began tracking cobots as a distinct category in Q1 2025 and will expand future reporting to include growth trends by sector.

Automotive versus non-automotive sectors

The non-automotive sector took the lead over automotive in Q2, accounting for 56% of total units ordered. This move reflects the expanding role of automation in industries such as life sciences, electronics, and other non-automotive manufacturing sectors.

The post Report shows steady automation investment in first half of 2025 appeared first on Engineering.com.

Why is HIL testing important in automotive engineering?

In recent years, the number of electronic control units (ECUs) in automobiles has grown dramatically. These ECUs have replaced many mechanical components and handle various functions and input/output, making them prime candidates for HIL testing. By simulating the operation of ECU-guided automotive products, teams can test virtual representations of products instead of physically testing finished prototypes.

HIL testing offers numerous benefits to automotive engineers. By testing virtual models of products, teams can save significant time and expense. HIL testing can also identify potential flaws earlier in the workflow, when the flaws can be fixed more affordably and efficiently. And, with virtual models replacing physical models, HIL testing can consider numerous scenarios without the time and expense required for physical tests. It also offers safety benefits, enabling teams to simulate conditions without exposing humans to dangerous situations.

Examples of automotive HIL testing

A wide variety of automotive products and systems can benefit from HIL testing. While some systems include interaction with the user and others are controlled automatically by sensors and computer-aided devices. If over-the-air (OTA) updates are provided to update software, HIL testing can also incorporate these updates and modify testing accordingly. Here are some examples:

Engines: One or more engine ECUs govern engine operation, converting sensor measurements into actions such as adjusting air intake. HIL testing simulates engine operation and interaction with real I/O devices such as acceleration pedals. For internal combustion engines, this might include testing controllers that handle fuel consumption and emission control. For electric vehicles (EVs), HIL testing might simulate a motor-generator, battery and connections to direct-drive transmission.

Powertrains: Transmission systems, power electronics and battery management systems can be tested with real-time simulations. HIL testing simulates the operation of various components such as converters, relays, onboard power system components and charging systems. With the growth of EVs, battery management is a key design consideration.

Chassis and vehicle dynamics: This can include steering, braking, suspension and traction control systems. For example, a steering system can be tested using HIL techniques to model  vehicle handling behavior based on digital input that simulates steering wheel actions. The testing can aid development of steering controls and electro-mechanical actuators. Similarly, brake hydraulics can be simulated with HIL testing to model braking maneuvers and vehicle responses.

Advanced driver assistance systems (ADAS): Cameras, sensors and other devices can help alert drivers of potential collisions with other vehicles, detect pedestrian and roadside obstacles, and in the case of autonomous vehicles (AVs), take over driving under certain conditions. HIL testing can simulate real-life situations in developing and validating these systems.

Interior features: Seating, lighting, heating, air conditioning and other systems now rely heavily on ECUs. HIL testing can be used to test scenarios such as power-seat operation and climate-control systems, which may include heat exchangers, compressors, sensors, actuators, ductwork and other devices. HIL testing can simulate the functionality of various components and ECUs and their connection to the centralized ECU.

Entertainment and information systems: These systems connect the driver and passengers to a wide variety of information sources, including mobile devices, conventional and satellite radio, cloud resources, dashboard display systems and diagnostics. They also play a key role in coordinating OTA updates. HIL simulation can test various instrument clusters, displays and warning systems, with a real-time target machine running a virtual vehicle and direct interfaces using analog and digital signals or standard communication protocols.

What other types of testing are used with embedded systems?

In addition to HIL testing, various other types of testing are used in embedded automotive systems:

• Model-in-the-loop (MIL) testing simulates both the controller and the physical systems with virtual models instead of physical hardware. MIL testing is often used in early development stages to verify design assumptions and control algorithms.
• Software-in-the-loop (SIL) testing runs the software in a simulated environment to verify that the control algorithms are operating correctly, providing a bridge between model simulations and real-world applications.
• Processor-in-the-loop (PIL) testing executes the control algorithms on the actual processor or other device connected to the simulated environment. This technique checks for potential issues related to code generation, execution timing and processor-specific behavior, confirming that the software will perform as intended.

Several variations of HIL have also been developed. Power hardware-in-the-loop (P-HIL) testing introduces power amplifiers or other power equipment to convert low-voltage signals from a real-time system into the higher voltages of the emulated device. This approach enables teams to test power components of the control system in a framework similar to actual operating conditions.

Virtual HIL (vHIL) testing enables creation and execution of tests before the actual ECU hardware is available. With the vHIL approach, testing can begin earlier and be automated to guide subsequent testing.

What standards are applicable to HIL testing?

A variety of standards and guidelines apply to automotive HIL testing. The International Organization for Standardization (ISO) established ISO 26262 (road vehicles functional safety) as an international standard for functional safety of electrical and/or electronic systems. ISO 26262 includes requirements for HIL development processes and documentation of these processes, as well as qualification and validation. Other ISO standards applicable to automotive testing include ISO 21448 (road vehicles — safety of the intended functionality or SOTIF) and ISO 21434 (road vehicles cybersecurity engineering), which was developed in conjunction with SAE International.

The Association for Standardization for Automation and Measuring Systems published ASAM XIL, an API standard that covers multiple types of in-the-loop testing, HIL, MIL and SIL. The standard provides guidance on communication between test automation tools and test benches, facilitating the integration of HIL technology from different vendors.    

Various communication protocols apply to HIL testing. Protocols such as Ethernet, controller area network (CAN) and local interconnect network (LIN) define connections between the real-time test system and the actual embedded controller. Actuator interfaces that connect the test equipment to the simulated system use these communication protocols to accurately capture hardware responses and feed them back into the simulation for real-time analysis.

Future applications of automotive HIL testing will likely incorporate artificial intelligence (AI), automation and digital twins. AI and automation can help improve efficiency, simulating driver behavior, traffic conditions, and other complex situations. Digital twins — virtual representations of physical systems — can enhance the realism of HIL simulations, allowing for real-time synchronization between virtual and physical components.

HIL testing is also likely to become more modular and scalable, allowing for testing of different vehicle types. This enables testing to be adapted to a wide range of vehicles, ranging from compact cars to luxury sedans and commercial vehicles.

The post How is hardware-in-the-loop (HIL) testing used in automotive engineering? appeared first on Engineering.com.

This is not just a transaction between two legacy software firms. It could represent a redefinition of the industrial software landscape: Autodesk, long focused on democratizing design via the cloud, meeting PTC, grounded in enterprise-scale digital transformation for manufacturers. The overlap is clear. The complementarity? Still to be proven.

Strategy, scale, and ambition

While both companies are respected in their domains, they differ significantly in size, culture, and strategic posture:

• Autodesk reported more than $6.1 billion in FY2025 revenue (fiscal year ending January 2025), with a market cap of approximately $66.6 billion.
• PTC reported $2.3 billion in FY2024 revenue (fiscal year ending September 2024), with a current market cap around $17 billion following the takeover speculation bump.

Autodesk is more than twice PTC’s size in revenue and has traditionally focused on AEC, creative design, and mid-market engineering. PTC, in contrast, is deeply rooted in industrial manufacturing, PLM, and IoT.

This is not a merger of equals. It reflects Autodesk’s strategic ambition to move deeper into the enterprise market. With PTC, Autodesk would gain credibility and capability in core enterprise workflows. This would mark a step change for Autodesk’s portfolio maturity—from cloud-native tools for SMBs to enterprise-scale digital thread and product lifecycle platforms.

Yet, the companies have very different go-to-market approaches. Autodesk has built its SaaS business around high-volume channels, while PTC’s sales motion is enterprise direct. That contrast creates opportunity-but also serious integration risk.

Market reactions and community feedback

PTC shares surged over 17% on July 9 after Bloomberg reported Autodesk was exploring a bid. They fell 7.5% the next day. Autodesk’s stock declined nearly 8% as investors assessed the strategic rationale and integration risks. These market movements highlight the scale and sensitivity of such a transformative bet.

In professional forums and industry circles, the deal has sparked debate. Many experts have expressed skepticism about strategic alignment. They point out potential redundancy between core CAD offerings (Creo vs. Inventor/Fusion 360) and PLM solutions (Windchill vs. Fusion Manage). Others note Autodesk’s limited experience in large, complex integrations, and voice concerns about its ability to manage an enterprise-scale acquisition.

One clear thread: this would be a high-risk, high reward move. Autodesk has never made a deal of this magnitude. It could unlock new verticals—but also strain its operating model and alienate parts of its existing base.

Analysts also speculate on regulatory hurdles. The CAD and PLM market is already concentrated. A deal of this scale may face antitrust scrutiny, particularly in the US and Europe. Financing would also be a stretch, and shareholders will expect a well-articulated synergy plan. The rumored price tag of about $20 billion raises the stakes further.

Product portfolio and strategic fit

Autodesk has invested heavily in Autodesk Platform Services (APS), with Fusion 360 acting as its design collaboration anchor. PTC’s portfolio is broader in manufacturing and enterprise engineering, with Windchill+, Arena (PLM), Onshape (cloud CAD), and ThingWorx/Kepware (IoT/edge connectivity).

While the combination would offer end-to-end coverage from SMB to enterprise, the breadth creates duplication. Customers may worry about future roadmap clarity. Will Autodesk continue Fusion Manage or prioritize Windchill+? Can Creo and Inventor coexist? And does Autodesk have a plan for ThingWorx and Kepware, which do not align with its core portfolio?

Most experts believe those IoT assets will be divested. That opens new opportunities for companies like Rockwell, Schneider Electric, or Emerson—firms more focused on industrial automation and edge connectivity. These decisions will send strong signals to the market about Autodesk’s long-term intent.

Beyond the technology, there is a broader question: is Autodesk acquiring products, a platform, and/or an extended customer base? The answer is likely to be multiple. It will determine how much integration effort is required—and how much customer disruption it might cause.

Execution and leadership will define the outcome

The true test will be execution. Autodesk has evolved into a cloud-first player over the past decade, but it has little experience with large-scale enterprise integrations. PTC, though smaller, brings a strong industrial culture and a distinct go-to-market strategy that may not align with Autodesk’s creative, SMB-rooted DNA.

Cultural integration, pricing model alignment, and partner ecosystem rationalization will be complex. If poorly managed, these differences could erode customer trust and delay value realization.

Leadership will play a pivotal role. PTC’s new CEO, Neil Barua, took over in February 2024 from long-time chief Jim Heppelmann. Barua, formerly CEO of ServiceMax (acquired by PTC in 2022), brings a sharper focus on customer-driven innovation and return on investment. His strategic priorities—and openness to integration—could influence how the two companies align.

ThingWorx and Kepware, once central to PTC’s digital transformation narrative, now appear most vulnerable to divestment. Their fate may define Autodesk’s long-term industrial strategy. Rockwell Automation’s recent exit from its $1B stake in PTC in August 2023 further suggests shifting alliances and possible competitive realignments in the broader industrial software ecosystem.

This deal, if it proceeds, will not go unnoticed. Siemens, Dassault Systèmes, and other PLM leaders are likely already reassessing their positions. A successful integration would escalate the digital thread race. A failed one could reinforce the limits of M&A in an already saturated market.

In the end, the acquisition is just the beginning. The real transformation will be defined by what Autodesk chooses to keep, integrate or let go.

Editor’s update July 14 2025: In the days after this story was published Autodesk in a regulatory filing declared this deal is no longer on the table and will instead focus on more strategic priorities, as reported by Reuters.

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