Throughout my career, I have had exposure to several types of legacy software in different companies and industries. Organizations deal with the idea of transforming to a digital platform in one of three ways: they view the legacy software as crucial and must be integrated (high resistance), they keep using it in parallel to a digital approach regardless of the high cost, or they transition completely to a digital system, which is surprisingly the least common approach.

During my time working for a global automotive company, I encountered a semi-collaborative approach to data sharing and working together. The main problem for engineering was working together in a private ecosystem. This was caused by several factors— different rules and regulations at each location, legacy software and a legacy mentality driven by several acquisitions that were never fully integrated. Our north star became the migration to a digital platform that bridged the divide and got the locations to work together. This approach was ultimately successful, and members of the organization could easily work on their projects from any location.

 Of course, issues appeared with the transition to a digital thread, including numbering schemes and streamlining or adapting processes to local needs. I learned that it is very easy to fall down the rabbit hole if you entertain every little detail. Instead, your main drive should always be to the agreed scope. During this transition, I had to quell a lot of debates on minor things that could have derailed the scope of our projects, and there were a lot of projects in the initial phase, such as our desired outcomes from moving to a complete digital thread, which software to migrate or discontinue, vendor selection and many others.

Indeed, it’s worth taking time at the beginning to design your solution as thoroughly as possible—it saves a lot of headaches down the road and most importantly, saves money. The role of an engineer in this specific spot is to balance out the budget with features. First and foremost, in this role you must bridge the divide between design and manufacturing, this was one of the first things that I learned as I was cutting my teeth in my first engineering job. You can design a product or a solution as neat as possible, but at the end you must produce it and to produce a product is a whole other beast than just drawing it on your computer. Understanding both the design component and having a surface understanding of how the product is manufactured gave me enough credit with the shopfloor people that I became the go to person for the head of manufacturing to present their topics and work with them to be able to incorporate them in the implementation process.

One of the most important but frequently ignored topics is user acceptance. People who are working with a specific software are usually SME (subject matter experts) and know the software in detail. Because of this, it can be tough to gain buy-in, but they are your most important asset in a legacy software to digital thread transformation. They have depth of knowledge that is critical to a successful migration or transition. Who knows LS outputs? Who knows how the processes were designed? Who knows which person down the process needs to be informed? The subject matter expert will make your life a thousandfold easier, so include them as early as possible, align on scope and have them help you build it.

If I were to choose one thing to avoid at all costs during a digital transformation, it would be ignoring parts of the organization. My success in this project was a result of the frequent consultation with the people handling day-to-day business of the organization. Since we started with several locations during ramp up, we ended up working very closely with people from all over the production process. This resulted in rapid feedback on anything that we did—especially on what we did wrong. That feedback is crucial, as we could incorporate it and adapt from sprint to sprint.

Legacy software is still present in many companies, but it should not be seen as malign pieces of a process that would kill a project before it starts. Rather, it was an important piece of the puzzle that fit the organization at a specific time in its existence, and as organizations mature and digital becomes the new norm, legacy software should be considered an important aspect of a migration scenario, even if it will ultimately be replaced.

Andrei Lucian Rosca is an engineer with a bachelor’s in mechanical engineering focusing on CAD software with more than 10 years of experience in Digital Transformation projects in several industries, from automotive to consumer goods. I am currently exploring innovative solutions (e.g. IoT, AI) and how to include them in future projects.

The post Dealing with legacy software during a digital overhaul appeared first on Engineering.com.

The program includes live demonstrations of VI-grade’s hardware and software platforms, including dynamic driving simulators, such as the DiM250, and HiL systems, such as AutoHawk. Engineers will also be able to interact with real-time simulation tools for vehicle dynamics (VI-CarRealTime), ADAS development (VI-WorldSim), and NVH analysis (VI-NVHSim). Other stations will show how human-machine interface (HMI) concepts are evaluated in virtual environments.

Engineers from companies such as Honda Motors, Hitachi Astemo, Mcity, and Multimatic will present a range of technical sessions and case studies. These will cover applications of simulation in vehicle design, system integration, and validation.

One portion of the event is dedicated to NVH simulation. In the afternoon, VI-grade will host a focused NVH user group session featuring updates to VI-NVHSim (releases 2025.1 SP1 and 2025.2), and discussion topics including sound design, CAE-test correlation, and electric vehicle sound simulation. The session will conclude with an open Q&A for users to provide feedback and discuss future development needs.

Zero Prototypes Day is intended for engineers working in ride and handling, ADAS, NVH, and HMI development, offering a practical look at how simulation tools integrate into modern automotive workflows.

The North American event piggybacks off of VI-grade’s 2025 Zero Prototypes Summit, held May 13 to 15 at its SimCenter in Udine, Italy. The global event attracted over 1,500 participants, with approximately 300 attending on-site and more than 1,200 tuning in via livestream. The event drew representatives from 24 OEMs, 17 Tier 1 suppliers, and six academic and research institutions, supported by 27 industry sponsors.

Across three days, attendees accessed nearly 1,000 hands-on demo sessions spanning VI-grade’s software suite, dynamic simulators, and HiL systems. Key technical sessions and customer case studies covered applications in vehicle dynamics, ADAS, NVH, and HMI development. Notable contributor brands included Alpine, Hyundai METC, Aston Martin Lagonda, Ferrari, Ford Werke, Honda R&D, Multimatic, Porsche Engineering, Stellantis, Volvo, and others.

Two major product launches were introduced at the Summit:

• HexaRev: a 6‑DOF motion platform designed to deliver smoother, quieter, and more precise driver-in‑the‑loop simulation through a new mechanical design that eliminates belts, gears, and ball-screws.
• VI‑DataDrive Cloud: a cloud-based simulation and data analytics platform aimed at reducing high-fidelity model run times and enabling scalable, collaborative workflows via AI-enhanced digital twins.

Senior management from VI-grade noted that the event demonstrated a strong and growing industry commitment to simulation-first vehicle development. The Summit’s regional scope is expanding, with a North American Zero Prototypes Day scheduled for June 12 in Michigan and a planned Japanese edition in Tokyo on September 12.

See you in Novi

Engineering.com is attending the 2025 North American Zero Prototypes Day at SimCenter Detroit in Novi, Michigan. Follow Editor-in-Chief Rachael Pasini on LinkedIn for live coverage and stay tuned for a full report on the latest technology. Live or work nearby? Registration is still open and free of charge.

The post Get set for the 2025 North American Zero Prototypes Day in Detroit appeared first on Engineering.com.

This episode of Designing the Future is brought to you by TE Connectivity.

In the automotive industry, the wiring harness has always been the nervous system of vehicles on and off the road. System architecture has used 12 volts DC since the 1950s, and for years, automotive engineers looked at a future of higher voltages, to generate more power for accessory laden vehicles, and to reduce cost and weight. However, as vehicles evolve with greater electrification and increasingly complex systems, the need for a more robust electrical architecture has become apparent.

Enter 48V technology, a game-changer poised to redefine automotive electrical systems. With its ability to deliver higher power for advanced vehicle systems while reducing cost, weight, and energy loss, a shift to 48V offers an efficient and practical solution to the demands of modern automotive design. Is the industry ready for its first major electrical overhaul in decades?

Engineering.com’s Jim Anderton spoke with TE Connectivity’s Helio Wu, a product manager in their automotive business, about how now is the time for the first major revamp in auto electrical architecture in decades.

* * * 
Learn more about TE Connectivity’s 48V electrical and electronic systems.

The post 48-volt architecture: The future of automotive electrical systems  appeared first on Engineering.com.

CoT as structured engineering reasoning

Chain of Thought formalizes what expert engineers intuitively do: breaking complex problems into logical, sequential steps that can be examined, validated, and improved. Enhanced with AI partnership, this structured reasoning becomes scalable organizational intelligence rather than individual expertise.

At its core, leveraging AI is about mastering the art of questioning. The transformation occurs when engineers move from asking AI “What is the solution?” to guiding AI through “How do we systematically analyze this problem?” This creates transparent reasoning pathways that preserve knowledge, enable collaboration, and generate solutions teams can understand and build upon.

As such, here is a reusable CoT template for technical decision-making:

“To solve [engineering challenge], break this down systematically:

1. Identify core constraints: [performance/cost/regulatory requirements],
2. Analyze trade-offs between [options] considering [specific criteria],
3. Evaluate effects on [downstream systems/processes],
4. Assess implementation risks and mitigation strategies.”

This template works across domains—thermal management, software architecture, regulatory compliance—because it mirrors the structured thinking that defines engineering excellence.

Practical applications in product innovation

CoT methodology proves most powerful in early-stage ideation, complex trade-off analysis, and compliance reasoning where traditional approaches miss critical interdependencies. Based on the target persona, this can translate in various use cases, such as:

Early-stage product ideation:

“To develop [product concept], systematically explore: 1) User pain points and current solutions, 2) Technical feasibility and core challenges, 3) Market positioning and competitive advantage, 4) Minimum viable approach to validate assumptions.”

Engineering trade-off analysis:

“When choosing between [options], evaluate: 1) Performance implications on [key metrics], 2) Cost analysis including lifecycle expenses, 3) Risk assessment and failure mode mitigation, 4) Integration requirements and future modification impacts.”

Compliance and regulatory reasoning:

“To ensure [system] meets [requirements], structure analysis: 1) Requirement mapping to measurable criteria, 2) Design constraint implications, 3) Verification strategy and documentation needs, 4) Change management for ongoing compliance.”

These frameworks transform AI from answer-generator to reasoning partner, helping engineers think systematically while preserving logic for team collaboration and future reference.

PLM integration—CoT as a digital thread enabler

CoT becomes particularly powerful when integrated into Product Lifecycle Management (PLM) and related enterprise resource systems—creating data threads that preserve not just what was decided, but why decisions were made and how they connect across development lifecycle. Just imagine these scenarios:

Design intent preservation:

“For [design decision], document reasoning: 1) Requirements analysis driving this choice, 2) Alternative evaluation and rejection rationale, 3) Implementation factors influencing approach, 4) Future assumptions that might affect this decision.”

Cross-functional integration:

“When [engineering decision] affects multiple disciplines, analyze: 1) Mechanical implications for structure/thermal/manufacturing, 2) Software considerations for control/interface/processing, 3) Regulatory impact and verification needs, 4) Supply chain effects on sourcing/cost/scalability.”

Digital thread connection points:

• Link design decisions to original requirements and customer needs.
• Connect material choices to performance targets and compliance requirements.
• Trace software architecture to system-level performance goals.
• Map manufacturing choices to cost targets and quality requirements.

This ensures that when teams change or requirements evolve, critical decision reasoning remains accessible and actionable rather than locked in individual expertise. From a business outcome perspective, this can contribute to continuity across product generations and reduce time spent retracing design decisions during audits, updates, or supplier transitions.

Strategic reality: revolution or evolution?

While CoT methodology delivers measurable improvements, the strategic question remains whether this represents fundamental transformation or sophisticated evolution.

Evidence for transformation: Though evidence remains scarce, early adopters of structured CoT approaches report measurable improvements in knowledge transfer efficiency, design review effectiveness, and decision consistency. Organizations consistently cite enhanced team collaboration, reduced rework cycles, and improved knowledge retention when engineering reasoning becomes explicit and traceable. These patterns suggest systematic capability enhancement rather than marginal improvement.

Case for evolution: Critics argue CoT merely formalizes what competent engineers have always done. Revolutionary breakthroughs—the transistor, World Wide Web, breakthrough materials—often emerge from intuitive leaps that defy structured frameworks, suggesting excessive systematization might constrain innovation. Regardless, the accelerating sophistication of AI demands that engineers critically assess not just what they build, but how they think.

Strategic balance: Successful engineering organizations are not choosing between structured reasoning and creative innovation—they are developing meta-skills for knowing when each approach adds value. CoT excels in complex, multi-constraint problems where systematic analysis prevents costly oversights. Pure creativity dominates breakthrough innovation where paradigm shifts matter more than optimization.

Future-proofing perspective: As AI capabilities accelerate from text generation to multimodal reasoning to autonomous design, organizations building frameworks for continuous methodology evaluation—rather than optimizing current techniques—will maintain competitive advantages through technological transitions.

Chain of Thought may represent the beginning of engineering’s AI integration rather than its culmination. The methodology’s emphasis on explicit reasoning provides tools for navigating technological uncertainty itself, perhaps its most valuable contribution to engineering’s digital future. CoT may be the missing link between today’s prompt-based AI assistants and tomorrow’s agentic co-engineers—moving from reactive support to proactive design collaboration.

Whether revolution or evolution, CoT offers engineers systematic approaches for amplifying problem-solving capabilities in an increasingly AI-integrated technical landscape.

The post How Chain of Thought drives competitive advantage appeared first on Engineering.com.

The increased role of computer software in manufactured products has added to the complexity of product testing. For example, automobiles and aerospace vehicles contain numerous electronic control units (ECUs) that handle various functions and input/output (I/O), making comprehensive testing difficult.

Software can also become part of the solution, as computer-based simulation offers ways to perform virtual testing. Instead of physically testing finished prototypes, manufacturing and engineering teams can simulate actual conditions and perform testing on digital models of products, saving time and expenses. While this helps accelerate testing, software simulations sometimes fail to identify issues encountered in physical testing.

To handle testing complexities, manufacturers often turn to hardware-in-the-loop (HIL) testing, which simulates real-world conditions for assembled products or components. By connecting a controller to a system simulating the operation of the product in real-world conditions, product teams can test products early and often in the design cycle while keeping testing as realistic as possible. HIL testing essentially replaces a physical model, such as an automobile transmission system, with a virtual representation of that system that simulates the physical model.

HIL process overview

HIL testing typically connects real controller hardware with a simulated system via a combination of analog and digital I/O connections. The simulated system is typically a mathematical model of the actual system. The model is executed in real time to simulate the behavior of the actual system based on inputs from the controller hardware.

Specific HIL testing processes vary by industry and application, but in general, the process starts with creating a digital model that simulates the physical system. The model may be created with commercial or custom-built software capable of modeling electrical, mechanical and hydraulic components as well as physical behavior related to fluid mechanics, thermodynamics and other physics-based specialties.

Before connecting the system to the controller, the model is typically run on a test system to simulate responses from controller hardware inputs and verify the system reacts in a realistic manner. Once verified, the controller hardware is connected to the simulation hardware to interact with the simulated system. The I/O connections may use communication protocols such as Ethernet, CAN and ARINC to send signals that emulate physical behaviors.

HIL testing with the real controller hardware generates a variety of data acquired from the controller and simulated system. The data is used to provide feedback to the controller, enabling the controller to adjust its behavior based on the simulated system’s responses. Measurement and verification include a wide variety of tests, ranging from normal operating conditions to fault conditions. Numerous iterations and refinements can be run to verify model accuracy and system performance.

Benefits of HIL testing

HIL testing offers numerous benefits to product designers and manufacturers. Because testing can be conducted before final assembly, it can identify potential flaws when they can be fixed more affordably and efficiently. Tests can be rerun to determine the efficacy of major fixes and minor adjustments. Such testing can also consider numerous scenarios without the time and expense required for physical tests. Automation can be used to conduct multiple scenarios, sometimes simultaneously, to accelerate testing and development.

By connecting real controller hardware to a simulated system, HIL testing offers more realistic testing than software-only simulation. It essentially combines aspects of both physical testing and software-based modeling. This combination also enables more collaboration amongst professionals with various backgrounds. Using primarily digital methods, test results can be shared readily with other stakeholders. Pure physical and software testing are often conducted by experts with specific expertise in those areas who report results back to product managers and others less interactively. HIL testing often involves collaboration up front and more ongoing access to hardware and system data throughout the process.

HIL testing also offers safety benefits, enabling teams to simulate conditions without exposing humans to dangerous situations. For example, an automobile braking system or other safety-critical systems can be tested using HIL techniques before testing in actual conditions.

Challenges of HIL testing

While typically not as expensive as physical testing of finished prototypes, HIL testing can be time-consuming and costly. Significant planning and development are required to build a simulation model, prepare the hardware controller for connection to the HIL system and monitor the testing.

The accuracy of HIL simulation can also be a challenge. Even with sophisticated hardware and software, it may not perfectly emulate actual systems, requiring ongoing testing and adjustment.

Collaboration among multidisciplinary teams can also prove challenging. While a wide range of perspectives can be beneficial, it can also require additional coordination and “cat herding” to achieve consensus on the approach and interpretation of results.

Present and future applications

A wealth of opportunities are available for teams able to properly address the various challenges. For example, the automotive industry has been particularly active in employing HIL testing. In addition to the previously mentioned transmission and braking examples, it can be used to test vehicle dynamics, steering systems, cruise control systems, advanced driver assistance systems (ADASs) and other systems employing ECUs.

In the aerospace industry, HIL testing can be used for flight control systems, avionics, navigation modules and a host of other areas. With the ability to perform real-time simulation, HIL has proven helpful for certifying aerospace systems and components.

It has also been used in the energy industry to simulate power plant behavior and grid reliability, in the electronics industry to test components and systems, and in industrial automation systems to evaluate system effectiveness before deployment. Infrastructure systems, such as water and wastewater treatment facilities, can use HIL to simulate scenarios such as peak demand and emergency scenarios.

Looking ahead, HIL testing will likely employ artificial intelligence and machine learning to further automate and refine testing procedures. A variation called virtual HIL (vHIL) testing is being used to create and execute tests before the actual ECU hardware is available. With the vHIL approach, testing can begin earlier and be automated to guide subsequent testing. As manufactured products become more complex, HIL and other methods will also become more advanced to meet the needs of product manufacturers.

The post How does hardware-in-the-loop (HIL) testing work? appeared first on Engineering.com.

Volkswagen’s recent strategic moves highlight a company at the crossroads of transformation. On one hand, VW is making bold investments in AI-driven engineering and forging strategic alliances to position itself as a leader in next-generation automotive innovation. On the other, it faces the stark realities of large-scale execution—rising manufacturing costs, operational challenges, new electric vehicle (EV) entrant competition, and financial pressures.

To stay competitive, VW has embraced generative AI, digital twins, and software-defined vehicles. Announced in December 2024, its partnerships with PTC and Microsoft to develop Codebeamer Copilot aims to revolutionize Application Lifecycle Management (ALM) with AI automation. Meanwhile, the adoption of Dassault Systèmes’ 3DEXPERIENCE platform signals a commitment to integrating model-based engineering (MBE) for optimized vehicle development.

At the same time, Volkswagen’s $5.8 billion investment in an alliance with Rivian showcases a strategic bet on the future of electric mobility. However, alongside these forward-looking investments, Volkswagen must grapple with fundamental execution challenges—managing rising production costs, navigating supply chain disruptions, and ensuring that its transformation efforts deliver tangible business outcomes.

Accelerating engineering transformation

Volkswagen’s collaboration with PTC and Microsoft to develop Codebeamer Copilot signals a strong commitment to leveraging generative AI in Application Lifecycle Management (ALM). Codebeamer is being augmented with AI-driven automation to enhance software development efficiency, a critical step as automotive manufacturers increasingly shift towards software-defined vehicles.

Software is no longer just an enabler; it is now at the heart of automotive product differentiation. For Volkswagen, a legacy automaker, competing with software-native disruptors requires a fundamental shift in how vehicle development is structured. Codebeamer Copilot represents more than an AI-enhanced ALM tool—it is part of a broader shift toward agile, continuous software deployment, ensuring that VW’s vehicles remain at the forefront of digital innovation.

Simultaneously, VW’s adoption of Dassault Systèmes’ 3DEXPERIENCE platform aims to optimize vehicle development processes. This move reinforces the industry’s pivot towards integrated digital twins, where real-time collaboration and model-based engineering (MBE) accelerate product lifecycle governance. The 3DEXPERIENCE platform aligns with the growing need for cross-functional collaboration between mechanical, electrical, and software engineering teams, bridging gaps that have historically slowed down the development process. While these investments showcase Volkswagen’s intent to streamline development, execution remains key—successful deployment will hinge on cultural adoption and seamless integration with legacy systems.

Strategic EV alliances: the Rivian gambit

Volkswagen’s $5.8 billion partnership with Rivian announced in November 2024 signals a strategic hedge against legacy constraints. The alliance provides VW with access to Rivian’s advanced EV architecture, allowing the German automaker to accelerate its EV portfolio without reinventing the wheel. In return, Rivian gains the financial backing and industrial scale necessary to compete in an increasingly saturated EV market.

This collaboration is emblematic of a broader trend in the automotive industry: the shift from closed innovation models to open collaboration. OEMs are recognizing that building everything in-house is neither cost-effective nor agile enough for the rapid technological shifts defining the industry. By working with Rivian, VW positions itself to benefit from the startup’s agility while bringing its own mass-production expertise to the table.

However, alliances alone are not enough. To realize the full potential of this partnership, VW must overcome internal friction—balancing traditional automotive development processes with the more iterative, software-driven approach championed by Rivian. Success will depend on VW’s ability to integrate new ways of working without disrupting existing operations.

Executing transformation amid industrial pressures

While Volkswagen continues to push forward with its digital and electrification strategies, operational challenges remain a persistent theme. Rising material costs, supply chain bottlenecks, and production inefficiencies have placed significant financial pressure on the company. In 2024, VW reported 4.8 million vehicle deliveries—an impressive figure, but one that comes against the backdrop of increasing competition from Tesla, Chinese automakers such as local market leader BYD, and emerging EV startups.

Manufacturing complexity is another hurdle. Unlike Tesla, which designs its vehicles with highly streamlined production methods, VW is contending with legacy platforms that require significant re-engineering to accommodate next-generation propulsion systems and digital architectures. This tension between past and future is not unique to VW but serves as a reminder that digital transformation is as much about unlearning as it is about innovation.

To bridge this gap, Volkswagen must double down on operational efficiency while ensuring that its transformation investments deliver clear, measurable returns. This means refining its global production footprint, streamlining supplier relationships, and investing in workforce upskilling to ensure that its employees are equipped for the future of mobility.

Balancing disruption with execution

Volkswagen’s trajectory exemplifies the duality of digital transformation: bold investments in AI-driven engineering and strategic alliances, juxtaposed with the realities of industrial-scale execution. The success of these initiatives will depend on VW’s ability to navigate integration complexities, mitigate disruption risks, and sustain operational resilience.

For manufacturing engineering leaders, the key takeaway is clear: transformation is not just about adopting new technologies but ensuring their successful convergence with business imperatives. It requires a relentless focus on execution—aligning investments in AI, ALM, PLM, and EV strategy with pragmatic, scalable implementation roadmaps. The future of Volkswagen, and indeed the broader automotive industry, will be defined by those who can master this balancing act.

As digital and physical converge faster than ever, Volkswagen’s journey serves as a crucial case study that highlights both the promise and pitfalls of large-scale digital reinvention. The automaker’s success will hinge on its ability to harmonize technology adoption with industrial pragmatism, ensuring that innovation is not just pursued but effectively realized at scale.

The post VW’s digital journey balances bold moves with the realities of execution appeared first on Engineering.com.

Robot path planning is a complex, with most workcells using multiple robots requiring tedious work to create interference zones and interlock signals that ensure there are no collisions during manufacturing.

Manually validating the mechanical design, planning robot paths, determining sequencing to hit optimal cycle time targets, and defining those interlocks can take a team well over 100,000 hours for a single project. This complexity often leads to failures in hitting cycle time targets, adding significant rework.

Resolver works by selecting and testing potential solutions tens to thousands of times faster than a human programmer. The goal is to quickly generate optimal, collision-free motion paths and interlock signals. This can accelerate workcell design from months to days.

The company says Resolver is essentially infinitely scalable robotic simulation power that can used to reduce the time required for many tasks, including:

• Generating accurate proposals
• Designing optimal tools and fixtures
• Producing optimal robot programs
• Adjusting for as-built deviations during commissioning
• Assessing and minimizing the impact of product design changes

“It is widely understood that the future of the manufacturing industry lies in robotics and automation. However, that future is slow to materialize because of the outdated, time-consuming, and inefficient processes commonplace in the industry,” said Peter Howard, CEO of Realtime Robotics. “Few manufacturers have the time or resources needed to enact real change. We’ve engineered Resolver to help manufacturers improve their engineering, programming and production processes – and drive greater value from their current and future investments in robots.”

How it works

Realtime Robotics’ Resolver supports path planning with any number of robots, at any phase of the workflow, generating results in minutes. The solution requires minimal onboarding and currently allows users to work directly within Siemens Process Simulate. Support for other leading simulation platforms will be rolled out later in the year, enabling teams to work directly within their preferred simulation tool.

“Resolver has the computational power to generate better motion paths than human programmers in both simple and complex workcells,” added Howard. “This is because Resolver searches the possibilities open to robotic arms, while humans tend to stay within the possibilities of the human arm.”

Users upload the workcell information, configure their sequencing and conditions, and execute a run. In minutes, Resolver will generate motion paths—including interlocks. The longer Resolver runs, the more options it provides, shortening the cycle time until the desired outcome is reached. The paths and interlocks can then be easily imported back into the simulation software for validation and operation.

Beyond determining optimal motion plans and interlocks, Resolver can help with fixture design, reachability validation, target sequencing, and robot task allocation. It can also be used to design the paths and interlocks for an entire manufacturing line from the start.

The post New robot path planning software cuts weeks of programming appeared first on Engineering.com.

This episode is brought to you by Parker.

Sustainability is no longer marketing hype, it’s a fundamental part of the way machines are engineered in the 21^st century.  The electric vehicle revolution is in full swing in the automotive industry, but internal combustion engines power a lot more than on-the-road vehicles.  Equipment in the mining, construction and agriculture sectors is big, powerful and emits both pollutants and CO₂ from internal combustion engines. 

It’s a segment that is ready for electrification, and Electrification Product Manager for Parker Hannifin, Jonah Leason, explains how in conversation with engineering.com’s Jim Anderton. 

Learn more about Parker’s offroad industry solutions.

***

Catch up on the latest engineering innovations with more Industry Insights & Trends videos and podcasts.

The post Electrification delivers sustainability to off-highway applications  appeared first on Engineering.com.

Total installations of industrial robots in the U.S. automotive sector increased by 10.7%, reaching 13,700 units in 2024, according to preliminary results reported by the International Federation of Robotics (IFR).

“The United States has one of the most automated car industries in the world. The ratio of robots to factory workers ranks fifth, tied with Japan and Germany and ahead of China,” says Takayuki Ito, President of the International Federation of Robotics. “This is a great achievement of modernization. However, in other key areas of manufacturing automation, the US lags behind its competitors.”

The majority of industrial robots deployed in the U.S. are imports from overseas, as there are few robot manufacturers producing there. Globally, 70% of robots are produced by four countries: Japan, China, Germany and South Korea.

Within this group, Chinese manufacturers are the most dynamic, with production for their huge domestic market more than tripling from 2019 to 2023. This puts them in second place after Japan and is driven by the country’s national robotics strategy. Its manufacturing industry installed about 280,000 units per year between 2021 and 2023, compared to a total of 34,300 installations in the United States in 2024.

In China, robotics and automation are penetrating all levels of production, resulting in a robot density of 470 robots per 10,000 employees in manufacturing—the third highest in the world, surpassing Germany and Japan in 2023.

China’s National Development and Reform Commission in March 2025 established a state-backed venture capital fund focused on robotics, AI and cutting-edge innovation. The long-term fund is expected to attract nearly 1 trillion yuan (US$138 billion) in capital from local governments and the private sector over the next 20 years. This initiative aims to continue China’s technology-driven manufacturing:

The U.S. ranks tenth among the world’s most automated manufacturing countries with a robot density of 295 robots per 10,000 employees. The country’s automation is heavily concentrated in the automotive sector with about 40% of all new industrial robot installations in 2024.

This is followed by the metal and machinery industry with 3,800 units, representing a market share of 11%. Installations in the US electrical and electronics industry has a market share of 9% with 2,900 units sold.

The post Robot deployment rises in automotive while other sectors lag appeared first on Engineering.com.

Additionally, physical prototypes require significant energy and resources to build, along with fuel, tires and transportation for testing, often involving international shipping, which adds to inefficiency and emissions. In contrast, simulators offer a more sustainable solution where virtual models can be tested locally, then shared digitally with teams around the world, dramatically reducing the carbon footprint, cost and time.

“The vision is to have a validation prototype be the first vehicle off the line,” said Dave Bogema, senior director of product management at VI-grade. “You want something that you can test, but that car should ideally be a saleable vehicle at that point. The aviation industry has gotten there to a large degree, so the idea for the auto industry is to get to the point where they can simulate virtually everything and then have a vehicle that’s right when they build it.”

Real-time, multi-attribute simulators create a realistic experience

VI-grade specializes in simulations that involve human interaction — areas where subjective human experience is essential to evaluation. This includes vehicle dynamics (how a car handles, rides and responds to road conditions), NVH (noise, vibration and harshness,) and the human-machine interface (HMI), which includes screens, buttons and other input systems in the vehicle. Although measurable in some objective ways, these elements ultimately depend on human perception to determine if the vehicle feels responsive, comfortable and engaging.

To support these evaluations, VI-grade develops a variety of specialized simulators. These range from large, room-sized simulators for vehicle dynamics (capable of simulating physical motion, such as lane changes or braking), to NVH simulators for accurate acoustic and vibration reproduction, to HMI simulators that replicate the vehicle’s interface. These tools allow engineers and decision-makers to immerse themselves in realistic scenarios, experiencing how a car performs and feels long before production.

One of VI-grade’s advancements is the development of multi-attribute simulation. Traditionally, automotive testing and simulation have been siloed — engineers would assess vehicle dynamics in one simulator, then move to another setup to evaluate NVH, and yet another for HMI. VI-grade’s integrated approach combines these aspects into a single, cohesive simulation experience. This integration is critical because these vehicle attributes often interact — for example, a vehicle’s vibration can affect how the HMI is perceived, or NVH might influence handling performance.

“For our vehicle dynamics models, we take what would be a traditional multibody model and simplify it as a real-time model,” said Bogema. “VI-grade’s sister company is Concurrent Real-Time, and their focus is on building real-time computers. So, the core of our simulators is this real-time computer that enables you to drive in real time as you would a real car.”

Simulating a vehicle involves integrating multiple specialized modeling techniques — such as multibody dynamics, finite element analysis and computational fluid dynamics (CFD). While many companies focus on individual components or specific simulation types, such as gearbox noise or wind acoustics, VI-grade’s strength lies in combining these diverse inputs into a unified environment that replicates the full complexity of a vehicle, enabling evaluation of interactions between systems such as road noise, wind and the entire powertrain without relying on physical prototypes.

“We stitch everything together and give you that realistic experience,” said Bogema.

The company has a global network of SimCenters, with its flagship location in Udine, Italy. These centers are used for product demonstrations and function as collaborative spaces where clients can undertake specific projects, conduct proof-of-concept work or simply gain hands-on experience with simulators. Staffed by technical experts, the SimCenters offer education and practical support, enabling customers to explore new ideas, test innovations and advance their development goals in a high-tech, guided environment.

Watch the 2025 Zero Prototypes Summit virtually

VI-grade will host its annual Zero Prototypes Summit, May 13–15, 2025, at its SimCenter in Udine, Italy, so that industry professionals can gather, discuss technology advancements and learn from each other. Registration remains open to attend the in-person event, and livestream options are available through LinkedIn.

“The Zero Prototypes Summit is unique in that it’s put on by Vi-grade but has turned into an industry event. It’s very similar to a conference where customers are giving presentations and learning from each other. It’s not all about VI-grade — it’s about the technology in the industry and how people are pushing forward this idea of zero prototypes,” said Bogema. 

The event fosters collaboration and knowledge sharing around the common goal of reducing physical prototypes and accelerating development through improved simulation methods. The first half of each day is dedicated to hands-on experiences with driving simulators, including the company’s newest HMI and full-spectrum simulators, which integrate motion, vibration and sound for multi-attribute testing. Virtual reality is also featured as a growing simulation tool. Alongside live software demos and interactive displays, a large exhibition area hosts VI-grade’s simulation and service partners, offering a comprehensive view of the simulation ecosystem. The event also typically includes product launches — this year showcasing a new motion simulator and new software solutions — for attendees to gain insights and a broader understanding of the field, with contributions from industry leaders and university researchers.

Online attendance is free of charge and includes the following high-level customer presentations that attendees can register for separately:

• Session 1, featuring Bridgestone EMIA, Ferrari, Porsche Engineering, Lamborghini and EDAG Group.
• Session 2, featuring TRE, Brembo, Horiba Mira & CATL, Honda R&D, as well as an engaging podium discussion on AI.
• Session 3, featuring Alpine, Pirelli & MegaRide, Aston Martin Lagonda, S&VL & Subaru, Applus+ IDIADA & Hyundai METC, HBK nCode and Volvo Cars.
• Session 4, featuring ASC-S, Multimatic, Stellantis & Meccanica 42, Ferrari, Hyundai METC and Ford Werke.

Those who register will receive an email with links to videos and a recap of the event.

Can’t make it to Udine? Let’s meet in Novi

For those in North America, particularly near Detroit, who cannot attend the 2025 Zero Prototypes Summit in person this year, VI-grade is hosting a 2025 North American Zero Prototypes Day on June 12, 2025, at the Multimatic SimCenter in Novi, Michigan. This regional event will mirror Udine’s vibes, knowledge-sharing and collaborative nature with live demonstrations, software stations, presentations and networking. 

Registration is open and free of charge, with more information to come.

To learn more about VI-grade, visit vi-grade.com.

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