This 25+ page white paper explores practical ways to simplify operations, accelerate throughput, and maintain quality in today’s most demanding production environments. It shows how modern execution strategies can close the gap between as-designed and as-built products while reducing costly delays.

Inside, you’ll learn about:

• Streamlining production flows and enforcing consistency across operations
• Advanced tracking, tracing, and defect management for full visibility
• Digital instructions and data capture that eliminate paper-based inefficiencies
• Scalable approaches for multi-plant execution and collaboration
• Integration across planning, quality, and execution for better outcomes

Your download is sponsored by Siemens.

The post Your Guide to Managing Complexity with Confidence appeared first on Engineering.com.

Planned annual shutdowns are a routine part of facility operations. Usually timed around slower seasons, they offer a chance to complete maintenance tasks that can’t be done while equipment is running. However, the opportunity is often underutilized.

“People will do very minimal planning, or sometimes even no planning,” says Bill Brown, chief engineer at Schneider Electric. “Without really taking a hard look at what needs to be done, inevitably some things get left out.”

In some cases, improvements to existing infrastructure take a backseat to more urgent tasks, such as construction projects. With the right support, however, shutdown periods can help facilities boost their operations uptime. Consulting services like Schneider Electric’s EcoConsult are giving teams the tools to plan smarter and make better use of their shutdown window.

Missed opportunities during planned downtime

Even when shutdowns are scheduled well in advance, teams often go in with limited visibility into actual system conditions. Maintenance tasks are typically guided by standard checklists—and while these may keep operations running in the short term, they also increase the risk of reactive maintenance. Opportunities to uncover deeper issues or improve equipment performance often go unnoticed.

“Without visibility to data, you end up doing too much guesswork,” says Brown. “When you do that and follow a set checklist, you’re not necessarily on the lookout for things that aren’t on the checklist but could very well make or break the reliability of the equipment if they’re not looked at and fixed.”

One common blind spot is equipment loading. If teams don’t have a clear understanding of whether components have been operating within their limits, they may miss signs of wear that can reduce equipment lifespan and lead to unplanned downtime later.

How EcoConsult helps teams prioritize and plan work

EcoConsult offers a more structured, data-driven approach to shutdown planning, starting with assessments of both safety risks and de-energization activities at the beginning of the process. In scenarios where facility teams don’t have an electrical maintenance plan in place, Schneider Electric works with them to build one from the ground up.

“We can use our expertise with these types of equipment and systems to make sure that the program is robust enough to keep things running reliably, that the right things are looked at during maintenance, and that things don’t get missed,” says Brown.

EcoConsult also helps facilities meet NFPA 70B requirements, including producing or updating one-line diagrams and completing studies such as short-circuit, protection coordination and arc flash analysis. These tools not only support compliance but also assist in determining which equipment needs attention during the shutdown.

“Let’s say, for example, we’re going through a facility, trying to find what the particular issues could be,” explains Brown. “If we find a piece of equipment that is overloaded, or a piece of equipment that doesn’t have a clear maintenance record, or we find a system where there’s some safety issue—some modification needed to make sure things stay safe—those types of findings can be pointed out in the report. With a report that outlines those issues, they become much easier to prioritize. They also become much more visible when presenting to the facility’s management.”

By looking at the state of the electrical system and identifying conditions that could otherwise be overlooked, EcoConsult helps teams further plan for modernization. “Depending on the make and model of the equipment, we know what can be done, how difficult it is, and all of that comes together to help plan a modernization project,” says Brown.

For example, if a facility has switchgear with obsolete circuit breakers but the overall structure is still in good condition, EcoConsult may recommend targeted replacements rather than full system overhauls. “Ultimately, we can make sure the proper budgeting support is put in place,” says Brown. “We know what kinds of upgrades provide a good bang for the buck and which ones don’t.”

Conclusion

With the right preparation and visibility, teams can use annual shutdown time to uncover risks, prioritize upgrades, and extend uptime. To make that possible, work needs to begin early—typically two to three months ahead of the scheduled outage. Time spent upfront ultimately allows more to be accomplished during the shutdown and ensures that teams are targeting the right priorities.

“The biggest reason companies aren’t as effective as they could be with their maintenance shutdowns is they simply lack resources,” says Brown. “They don’t have the time or the people to plan adequately—in which case, choosing the right partner becomes critical. We at Schneider Electric have got decades of experience doing this sort of thing. We have a lot of in-house experts. Because we know the equipment, and know it well, we can be a very effective partner to help make the most of a maintenance shutdown.”

To learn more, visit Schneider Electric.

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ABB will invest $110 million through the remainder of 2025 to expand its R&D and manufacturing of advanced electrification solutions.

The company says the cash will create nearly 200 new jobs and support expected future growth in key industries, including data centers and the power grid. Rapid expansion of data centers in the US is expected to keep annual electricity demand growth above 2% in both 2025 and 2026, more than double the average growth rate over the past decade, according to the IEA.

“This $110 million investment in the US is part of our long-term strategy to support future growth in our biggest global market,” said Morten Wierod, ABB’s Chief Executive Officer. “Demand is being driven by key trends, from the surging power needs of AI in data centers, to grid modernization and customers improving energy efficiency and uptime to reduce their costs.”

ABB will invest $15 million to create a new production line for Emax 3 in its Senatobia, Mississippi site. The Emax 3 air circuit breaker improves the energy security and resilience of power systems in large facilities with high power demands, including data centers, advanced manufacturing sites, and airports. The new line is expected to open in 2026.

A $30 million project will double the footprint of ABB’s Richmond, Virginia facility adding a new test center, warehouse and new assembly lines. The new facility, opening in Q4 2025, will create around 100 new production and engineering roles.

In Arecibo, Puerto Rico, an investment of more than $30 million will increase the size of the facility to accommodate three new production lines. Technologies produced in Arecibo include smart circuit breakers and switching devices, essential power components that help distribute electricity, protect equipment and monitor energy usage. The expansion will create 90 new jobs by the end of 2026.

A $35 million investment will increase the capacity of ABB’s manufacturing facility in Pinetops, North Carolina. This will support expected demand for advanced low and medium voltage grid components from the utilities, and for data centers and industrial facilities. The upgraded facility will come online in 2026.

All of this comes on the heels of a4100 million investment in ABB’s Canadian facilities announced in August 2025. That investment in Montreal, Quebec will combine ABB’s existing Iberville and Saint-Jean-sur-Richelieu facilities at a new greenfield location. This will enable ABB to meet increasing demand in key growth industries, including utilities, renewables, transportation, and residential and infrastructure projects across Canada.

The new site is expected to open in mid-2027 and will be located in the South Shore region of Montreal, Quebec. The new building will integrate clean, energy-efficient electrical equipment and heating systems to reduce energy consumption and cut carbon emissions by over 95 percent, compared with the two existing facilities.

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The partnership addresses a critical challenge in modern manufacturing: the disconnect between information technology (IT) and operational technology (OT) systems that has historically hindered production efficiency and innovation. Using Siemens’ Xcelerator portfolio and TRUMPF’s manufacturing expertise, the collaboration will focus on developing open and interoperable IT interfaces to support AI readiness for motion control applications.

Overcoming complexity with seamless system integration

Software is increasingly central to manufacturing, moving beyond its traditional role as an addition to hardware. Integrated hardware and software can improve flexibility, efficiency, and overall performance. For Siemens and TRUMPF, this shift brings both opportunities and challenges. Their collaboration aims to support faster innovation, improve hardware–software integration, and provide a scalable approach to delivering solutions through standardized interfaces.

The collaboration will also deliver tangible customer benefits through modular system architecture and unified system solutions. Standardized interfaces will allow for seamless connectivity between shop floor equipment and enterprise-level systems. Customers will benefit from increased operational efficiency, reduced engineering costs, and future-proof scalability by using open, modular automation solutions. These are critical to ensure future-proof AI readiness, that will permit customers to achieve faster time-to-market, improved production flexibility, and competitive manufacturing operations.

The partnership builds on regular exchanges between Siemens and TRUMPF development teams and reflects the role of collaboration in addressing industry challenges.

For more information, visit siemens.com.

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Most electrical equipment failures stem from inadequate maintenance. That’s exactly what the National Fire Protection Association (NFPA) 70B was established to prevent. It provides an electrical equipment maintenance framework to reduce the risk of equipment failure, costly downtime, and energy inefficiency. 

But despite its importance, many facilities, from office buildings and industrial plants to commercial sites, remain unprepared to meet the NFPA 70B requirements introduced in the 2023 update. That’s a growing concern, especially now that NFPA 70B, previously a recommended practice, has become a formal standard with mandatory language.

There are two main reasons for this gap. A study from Schneider Electric found nearly 89 percent of facilities lack a documented electrical single-line diagram, which is the most fundamental requirement for compliance. Approximately 84 percent of sites in the United States report that they lack the time and resources to implement the new standard.

Experts at Schneider Electric have simplified compliance for electrical equipment owners by structuring an eight-step Electrical Maintenance Program (EMP) framework.

8 steps to compliance

With the shift from “Recommended Practice” to a “Standard” with mandatory requirements, organizations must take a structured approach to achieve compliance. Schneider Electric outlines an eight-step process to help streamline the process.

1. Assign an Electrical Maintenance Program Coordinator

The first step is to designate an individual to monitor the implementation and operation of the maintenance program. This coordinator serves as the central hub for the facility, ensuring that the maintenance plan includes all the necessary components and pieces of infrastructure.

2. Conduct a condition assessment of electrical infrastructure

Before establishing a maintenance plan, perform a comprehensive assessment of the current condition of all electrical equipment and infrastructure on site. “If there is no existing maintenance program, this can be an invasive inspection to see what condition everything is in and what the starting point should be for your maintenance plan,” Brown explains.

3. Update documentation (SLDs, studies, records)

This step involves updating all electrical documentation, including single-line diagrams, electrical drawings, arc flash analyses, short-circuit studies, and other relevant system studies. As outlined in NFPA 70B Chapter 6, once the existing documents are assessed, they must be updated at least every five years.

4. Perform remediation

In this step, the facility operator must execute remediation measures to address any issues or deficiencies found during the assessment. This step involves implementing the needed repairs, replacements, and improvements to the electrical equipment.

5. Define maintenance intervals

It is essential to define the scope of maintenance tasks and determine the maintenance intervals depending on the post-remediation conditions of each piece of equipment. In contrast to traditional maintenance schedules that occur every 2-3 years, NFPA 70B Chapter 9 provides guidelines for determining condition-based intervals.

6. Keep detailed EMP records

Maintaining detailed records is important for tracking compliance. Documentation will involve details on the maintenance activities, inspection findings, equipment conditions, and the schedule for each asset in the electrical infrastructure. “The EMP Coordinator will make sure everything stays up to date,” Brown notes. “The records are key because they tell us what must be maintained and when.

7. Audit EMP every 5 years or less

The coordinator must set up a regular audit to review the entire electrical maintenance program at intervals not more than five years. This step involves continuous improvement, comparing the current EMP records against NFPA 70B requirements and industry best practices.

8. Embrace digitalization

Digital tools enhance every step of the compliance process. By digitizing records, monitoring equipment health in real-time, and integrating analytics, facilities can shift from reactive to proactive maintenance. “Going forward, digitalization is going to be a huge part—or at least a highly recommended part—of efficiently maintaining a system,” Brown emphasizes.

Digital tools to support compliance

To support compliance with NFPA 70B, Schneider Electric offers a suite of digital tools and services to help facilities implement their Electrical Maintenance Program.

EcoCare is a membership-based service plan that gives facility owners access to Schneider Electric’s expert and emergency support. “Depending on the subscription level, EcoCare can offer everything from prioritized services and spare parts access to performance dashboards showing what’s covered under the plan,” Brown adds.

In today’s fast-paced industrial landscape, downtime isn’t just inconvenient—it’s costly. That’s where EcoCare steps in, a next-generation service plan designed to keep operations running smoothly through a powerful blend of expert support, AI-driven analytics, and condition-based maintenance.

Members gain exclusive access and fast-track emergency support, a dedicated Customer Success Manager, and preferential rates on training, spare parts, and on-site interventions. “EcoCare isn’t just a service plan—it’s peace of mind, powered by innovation,” Brown explains.

Conclusion

The 2023 update of NFPA 70B has made electrical maintenance a key aspect for ensuring reliable operation and safety.

By following the eight-step outline above, from assigning a maintenance coordinator and assessing equipment conditions, to maintaining up-to-date records and leveraging digital tools, facilities can build an Electrical Maintenance Program that meets the standard.  

To learn more about Schneider Electric’s compliance solutions, visit their website.

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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.

By Alan Petrillo

History teaches that the Industrial Revolution began in England in the mid-18^th century. While that era of sooty foundries and mills is long past, manufacturing remains essential — and challenging. One promising way to meet modern industrial challenges is by using additive manufacturing (AM) processes, such as powder bed fusion and other emerging techniques. To fulfill its promise of rapid, precise, and customizable production, AM demands more than just a retooling of factory equipment; it also calls for new approaches to factory operation and management.

Figure 1. An 1873 illustration of coal mines and iron works in England’s West Midlands. As one of the world’s first industrialized regions, part of this area became known as “the Black Country” for its soot-covered landscape. Image in the public domain via Wikimedia Commons.

That is why Britain’s Manufacturing Technology Centre (MTC) has enhanced its in-house metal powder bed fusion AM facility with a simulation model and app to help factory staff make informed decisions about its operation. The app, built using the Application Builder in the COMSOL Multiphysics^® software, shows the potential for pairing a full-scale AM factory with a so-called “digital twin” of itself.

“The model helps predict how heat and humidity inside a powder bed fusion factory may affect product quality and worker safety,” says Adam Holloway, a technology manager within the MTC’s modeling team. “When combined with data feeds from our facility, the app helps us integrate predictive modeling into day-to-day decision-making.” The MTC project demonstrates the benefits of placing simulation directly into the hands of today’s industrial workforce and shows how simulation could help shape the future of manufacturing.

Additive Manufacturing for Aerospace with DRAMA

To help modern British factories keep pace with the world, the MTC promotes high-value manufacturing throughout the United Kingdom. The MTC is based in the historic English industrial city of Coventry (Figure 2), but its focus is solely on the future. That is why the team has committed significant human and technical resources to its National Centre for Additive Manufacturing (NCAM).

Figure 2. The headquarters of the Manufacturing Technology Centre in Coventry, England.

“Adopting AM is not just about installing new equipment. Our clients are also seeking help with implementing the digital infrastructure that supports AM factory operations,” says Holloway. “Along with enterprise software and data connectivity, we’re exploring how to embed simulation within their systems as well.”

The NCAM’s Digital Reconfigurable Additive Manufacturing for Aerospace (DRAMA) project provides a valuable venue for this exploration. Developed in concert with numerous manufacturers, the DRAMA initiative includes the new powder bed fusion AM facility mentioned previously. With that mini factory as DRAMA’s stage, Holloway and his fellow simulation specialists play important roles in making its production of AM aerospace components a success.

Making Soft Material Add Up to Solid Objects

What makes a manufacturing process “additive”, and why are so many industries exploring AM methods? In the broadest sense, an additive process is one where objects are created by adding material layer by layer, rather than removing it or molding it. A reductive or subtractive process for producing a part may, for example, begin with a solid block of metal that is then cut, drilled, and ground into shape. An additive method for making the same part, by contrast, begins with empty space! Loose or soft material is then added to that space (under carefully controlled conditions) until it forms the desired shape. That pliable material must then be solidified into a durable finished part.

Figure 3. An example of a part produced through the metal powder bed fusion process.

Different materials demand different methods for generating and solidifying additive forms. For example, common 3D printers sold to consumers produce objects by unspooling warm plastic filament, which bonds to itself and becomes harder as it cools. By contrast, the metal powder bed fusion process (Ref. 1) begins with, as its name suggests, a powdered metal which is then melted by applied heat and re-solidified when it cools. A part produced via the metal powder bed fusion process can be seen in Figure 3.

How Heat and Humidity Affect Metal Powder Bed Fusion

“The market opportunities for AM methods have been understood for a long time, but there have been many obstacles to large-scale adoption,” Holloway says. “Some of these obstacles can be overcome during the design phase of products and AM facilities. Other issues, such as the impact of environmental conditions on AM production, must be addressed while the facility is operating.” For instance, maintaining careful control of heat and humidity is an essential task for the DRAMA team. “The metal powder used for the powder bed fusion process (Figure 4) is highly sensitive to external conditions,” says Holloway. “This means it can begin to oxidize and pick up ambient moisture even while it sits in storage, and those processes will continue as it moves through the facility. Exposure to heat and moisture will change how it flows, how it melts, how it picks up an electric charge, and how it solidifies,” he says. “All of these factors can affect the resulting quality of the parts you’re producing.”

Figure 4. A microscopic close-up of powdered metal grains, as used for powder bed fusion.

Careless handling of powdered metal is not just a threat to product quality. It can threaten the health and safety of workers as well. “The metal powder used for AM processes is flammable and toxic, and as it dries out, it becomes even more flammable,” Holloway says. “We need to continuously measure and manage humidity levels, as well as how loose powder propagates throughout the facility.”

To maintain proper atmospheric conditions, a manufacturer could augment its factory’s ventilation with a full climate control system, but that could be prohibitively expensive. The NCAM estimated that it would cost nearly half a million English pounds to add climate control to its relatively modest facility. But what if they could adequately manage heat and humidity without adding such a complicated system?

Responsive Process Management with Multiphysics Modeling

Perhaps using multiphysics simulation for careful process management could provide a cost-effective alternative. “As part of the DRAMA program, we created a model of our facility using the computational fluid dynamics (CFD) capabilities of the COMSOL^® software. Our model (Figure 5–7) uses the finite element method to solve partial differential equations describing heat transfer and fluid flow across the air domain in our facility,” says Holloway. “This enabled us to study how environmental conditions would be affected by multiple variables, from the weather outside, to the number of machines operating, to the way machines were positioned inside the shop. A model that accounts for those variables helps factory staff adjust ventilation and production schedules to optimize conditions,” he explains.

Figure 5. An isosurface plot showing temperature variations in the Drama facility with seven machines operating.

Figure 6. A plot of the distribution of humidity variations in the Drama facility.

Figure 7. A slice plot showing airflow velocity throughout the facility.

A Simulation App that Empowers Factory Staff

The DRAMA team made their model more accessible by building a simulation app of it with the Application Builder in COMSOL Multiphysics^® (Figure 8). “We’re trying to present the findings of some very complex calculations in a simple-to-understand way,” Holloway explains. “By creating an app from our model, we can empower staff to run predictive simulations on laptops during their daily shifts.”

Figure 8. A simulation app of the DRAMA powder bed fusion facility, showing the machines it contains and the locations of the air vents. Users can specify the initial temperature and humidity throughout the space, along with settings for the air handling system, lights, and metal powder storage room. In this case, some doors (highlighted in pink) have been left open.

Figure 9. The user can add an AM machine to the facility model by choosing it from a drop-down menu, and then specify its position and other relevant settings.

Figure 10. The simulation can capture variations in the thermal and fluid output of the machines over time. These isothermal surface plots show changes in temperature at 30 seconds (left) and 60 seconds (right) after opening the build chambers of every AM machine in the facility.

The app user can define relevant boundary conditions for the beginning of a factory shift and then make ongoing adjustments. Over the course of a shift, heat and humidity levels will inevitably fluctuate. Perhaps factory staff should alter the production schedule to maintain part quality, or maybe they just need to open doors and windows to improve ventilation. Users can change settings in the app to test the possible effects of actions like these. For example, Figure 10 presents isothermal surface plots that show the effect that opening the AM machines’ build chambers has on air temperature, while Figure 11 shows how airflow is affected by opening the facility doors.

Figure 11. A slice plot showing the effect that opening a door has on airflow. Air velocity toward an outlet duct is significantly weakened when the door directly beneath it is opened.

A Step Toward a “Factory-Level Digital Twin”

While the current app is an important step forward, it does still require workers to manually input relevant data. Looking ahead, the DRAMA team envisions something more integral, and therefore, more powerful: a “digital twin” for its AM facility. A digital twin, as described by Ed Fontes in a 2019 post on the COMSOL Blog (Ref. 2), is “a dynamic, continuously updated representation of a real physical product, device, or process.” It is important to note that even the most detailed model of a system is not necessarily its digital twin.

“To make our factory environment model a digital twin, we’d first provide it with ongoing live data from the actual factory,” Holloway explains. “Once our factory model was running in the background, it could adjust its forecasts in response to its data feeds and suggest specific actions based on those forecasts.”

Figure 12. The integrated feedback loop of a digital twin-equipped manufacturing operation, as defined by NCAM.

“We want to integrate our predictive model into a feedback loop that includes the actual factory and its staff. The goal is to have a holistic system that responds to current factory conditions, uses simulation to make predictions about future conditions, and seamlessly makes self-optimizing adjustments based on those predictions,” Holloway says. “Then we could truly say we’ve built a digital twin for our factory.”

Simulation at Work on the Factory Floor

As an intermediate step toward building a full factory-level digital twin, the DRAMA simulation app has already proven its worth. “Our manufacturing partners may already see how modeling can help with planning an AM facility, but not really understand how it can help with operation,” Holloway says. “We’re showing the value of enabling a line worker to open up the app, enter in a few readings or import sensor data, and then quickly get a meaningful forecast of how a batch of powder will behave that day.” Beyond its practical insights for manufacturers, the overall project may offer a broader lesson as well: By pairing its production line with a dynamic simulation model, the DRAMA project has made the entire operation safer, more productive, and more efficient. The DRAMA team has achieved this by deploying the model where it can do the most good — into the hands of the people working on the factory floor.

Figure 13. Workers inside the NCAM metal powder bed facility at MTC.

References

E. Fontes, “Digital Twins: Not Just Hype,” Feb. 2019; https://www.comsol.com/blogs/digital-twins-not-just-hype/

S. Hendrixson, “AM 101: Powder Bed Fusion,” Jun. 2021; https://www.additivemanufacturing.media/articles/am-101-powder-bed-fusion-pbf

Sponsored Content by Comsol

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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.

GE Aerospace and South Burlington, Vermont-based Beta Technologies Inc. have struck a strategic partnership to accelerate the development of a hybrid electric turbogenerator for advanced air mobility (AAM).

Applications include long-range Vertical Takeoff and Landing (VTOL) aircraft and future Beta aircraft and will combine Beta’s permanent magnet electric generators with GE Aerospace’s turbine, certification and safety expertise for large-scale manufacturing. This hybrid solution will leverage existing infrastructure and capabilities, such as GE Aerospace’s CT7 and T700 engines.

As part of the deal, GE Aerospace will make an equity investment of $300 million in Beta. GE Aerospace will have the right to designate a director to join Beta’s Board.

“Partnering with Beta will expand and accelerate hybrid electric technology development, meeting our customers’ needs for differentiated capabilities that provide more range, payload, and optimized engine and aircraft performance,” said GE Aerospace Chairman and CEO H. Lawrence Culp.

The deal is part of GE Aerospace’s pursuit of a suite of technologies for the future of flight, including integrated hybrid electric propulsion systems and advanced new engine architectures.

“We believe the industry is on the precipice of a real step change, and we’re humbled that GE Aerospace has the confidence in our team, technology, and iterative approach to innovation to partner with us. We look forward to partnering to co-develop products that will unlock the potential of hybrid electric flight, and to do it with the rigor, reliability, and safety that aviation demands,” said Kyle Clark, Beta Technologies’ Founder and CEO.

Beta’s “Alia” five-passenger VTOL and conventional electric aircraft charge in less than an hour, according to Beta’s website. They are engineered for all-weather performance and have been tested to operate reliably in a wide range of environmental conditions across the U.S. and Europe. ALIA’s electric propulsion and battery systems — which are developed in-house — offers reliable, high-tempo performance, as well as a quieter sound profile than conventional aircraft.

GE Aerospace and Beta also announced the two companies will collaborate to develop an additional offering for the AAM industry but offered no additional details.

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Last month Nvidia launched it’s powerful new AI and robotics developer kit Nvidia Jetson AGX Thor. The chipmaker says it delivers supercomputer-level AI performance in a compact, power-efficient module that enables robots and machines to run advanced “physical AI” tasks—like perception, decision-making, and control—in real time, directly on the device without relying on the cloud.

It’s powered by the full-stack Nvidia Jetson software platform, which supports any popular AI framework and generative AI model. It is also fully compatible with Nvidia’s software stack from cloud to edge, including Nvidia Isaac for robotics simulation and development, Nvidia Metropolis for vision AI and Holoscan for real-time sensor processing.

Nvidia says it’s a big deal because it solves one of the most significant challenges in robotics: running multi-AI workflows to enable robots to have real-time, intelligent interactions with people and the physical world. Jetson Thor unlocks real-time inference, critical for highly performant physical AI applications spanning humanoid robotics, agriculture and surgical assistance.

Jetson AGX Thor delivers up to 2,070 FP4 TFLOPS of AI compute, includes 128 GB memory, and runs within a 40–130 W power envelope. Built on the Blackwell GPU architecture, the Jetson Thor incorporates 2,560 CUDA cores and 96 fifth-gen Tensor Cores, enabled with technologies like Multi-Instance GPU. The system includes a 14-core Arm Neoverse-V3AE CPU (1 MB L2 cache per core, 16 MB shared L3 cache), paired with 128 GB LPDDR5X memory offering ~273 GB/s bandwidth.

There’s a lot of hype around this particular piece of kit, but Jetson Thor isn’t the only game in town. Other players like Intel’s Habana Gaudi, Qualcomm RB5 platform, or AMD/Xilinx adaptive SoCs also target edge AI, robotics, and autonomous systems.

Here’s a comparison of what’s available currently and where it shines:

Edge AI robotics platform shootout

Nvidia Jetson AGX Thor

Specs & Strengths: Built on Nvidia Blackwell GPU, delivers up to 2,070 FP4 TFLOPS and includes 128 GB LPDDR5X memory—all within a 130 W envelope. That’s a 7.5 times AI compute leap and 3 times better efficiency compared to the previous Jetson Orin line. Equipped with 2,560 CUDA cores, 96 Tensor cores, and a 14-core Arm Neoverse CPU. Features 1 TB onboard NVMe, robust I/O including 100 GbE, and optimized for real-time robotics workloads with support for LLMs and generative physical AI.

Use Cases & Reception: Early pilots and evaluations are taking place at several companies, including Amazon Robotics, Boston Dynamics, Meta, Caterpillar, with pilots from John Deere and OpenAI.

Qualcomm Robotics RB5 Platform

Specs & Strengths: Powered by the QRB5165 SoC, combines Octa-core Kryo 585 CPU, Adreno 650 GPU, Hexagon Tensor Accelerator delivering 15 TOPS, along with multiple DSPs and an advanced Spectra 480 ISP capable of handling up to seven concurrent cameras and 8K video. Connectivity is a standout—integrated 5G, Wi-Fi 6, and Bluetooth 5.1 for remote, low-latency operations. Built for security with Secure Processing Unit, cryptographic support, secure boot, and FIPS certification.

Use Cases & Development Support: Ideal for robotics use cases like SLAM, autonomy, and AI inferencing in robotics and drones. Supports Linux, Ubuntu, and ROS 2.0 with rich SDKs for vision, AI, and robotics development.

(Read more about the Qualcom Robotics RB5 platform on Robot Report)

AMD Adaptive SoCs and FPGA Accelerators

Key Capabilities: AMD’s AI Engine ML (AIE-ML) architecture provides significantly higher TOPS per watt by optimizing for INT8 and bfloat16 workloads.

Innovation Highlight: Academic projects like EdgeLLM showcase CPU–FPGA architectures (using AMD/Xilinx VCU128) outperforming GPUs in LLM tasks—achieving 1.7 times higher throughput and 7.4 times better energy efficiency than NVIDIA’s A100.

Drawbacks: Powerful but requires specialized development and lacks an integrated robotics platform and ecosystem.

The Intel Habana Gaudi is more common in data centers for training and is less prevalent in embedded robotics due to form factor limitations.

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