Next Level Manufacturing Technology: The thinking and technology behind General Motors’ MES 4.0
The future of automotive manufacturing is changing, becoming technologically smarter, more streamlined, and more sustainable. It’s both exciting and challenging in ways never seen before. At General Motors (GM), manufacturing is viewed as a core competitive advantage, one that will ensure we launch 30+ electric vehicles by 2025. We’ll be eliminating tailpipe emissions from new light-duty vehicles by 2035 and becoming carbon neutral in our global products and operations by 2040.
To meet these goals, our manufacturing technology is becoming more flexible—with concurrent production and engineering. We’re improving quality with better test automation and virtual design, development, and validation. And we’re taking advantage of the increase in data from industrial IOT devices, and artificial intelligence and machine learning at the edge.
As GM’s IT director for global manufacturing, my job is to explore how we can exploit concurrent engineering and operational technology (OT) and information technology (IT) subsystems, so we can achieve the speed, quality and flexibility needed to meet the challenges ahead.
How we are bridging the chasm between IT and OT
In a typical GM plant, we have about six thousand OT devices—anything from cameras and PCs to robots and various controllers. That plant can also have more than 50 manufacturing execution systems (MES) applications and because the ecosystem is connected, that means more than 100,000 connections between the OT and IT layers of the software stack.
But despite today’s technology-rich environment, this OT-IT boundary continues to be managed with manual and paper-based processes. At GM, we’re working with GE Digital to change that. We call the work to bridge the gap between OT and IT “MES 4.0.”
For example, consider a torque operation, which is common in an assembly plant. This operation needs to interact with several other systems—the auto management system that tracks parts, the SCADA system that monitors the assembly line, an IT system that tracks the vehicle’s genealogy, and more. It may need to store the torque value in a trace management system or store the torque curves into a telemetry system for detailed analytics and machine learning. And if the torque operation fails or is unsuccessful, for whatever reason, a defect needs to get logged into the quality management system.
Wouldn’t it be great to have a single system that manages and learns from these kinds of activities? We think so too. But the reality is that, like other manufacturers, we’ve struggled to stitch together disparate data and turn it into valuable, real-time insights.
So, we changed our approach.
Model-Based Systems Engineering
It’s common for manufacturers to take an application-centric approach to solving data management, but this approach can vary in how it is structured and deployed. Instead, at GM we’re now taking an operation-centric approach by formally modeling all the interfaces between operations. We built “catalogs” of operations—including IT interfaces, OT tools, equipment, and OT interfaces—which give us the context necessary to analyze data transmitted from IOT devices because the raw data alone is insufficient for drawing actionable insights.
This common understanding of context helps us stitch the data together across the various MES applications through to the entire manufacturing engineering process. From there, we can start to define the actual layout and the actual operations and the actual sequence of events, including creating the bill of process, bill of material and bill of equipment.
Virtual Design, Development & Validation
Traditional web applications have two sources of input—users (via UI) and other systems (via API). Manufacturing software has a third source—plant floor devices. That’s a lot of connection and communication. One of the key capabilities needed for the development of distributed systems is the ability to test and perform as much of the engineering work as possible in the virtual domain.
At GM, we developed a Virtual Factory Testbed to provide the tools and environment needed to test all manufacturing process variations that are necessary to support build-to-order manufacturing, as well as all permutations of outcomes that can result from each operation. We employ a process digital twin to mimic plant-floor behavior and test the integration of OT and IT systems—without requiring the physical lines to be deployed, and without requiring physical products flowing down the line. Not only does this help GM’s competitive advantage, but it brings us closer to our sustainability commitments.
While Model-Based Systems Engineering helps us eliminate paperwork, and our Virtual Design, Development and Validation system enables us to test OT and IT subsystems, MES Ops helps us eliminate the manual work needed to wire up these subsystems. MES Ops Is the term we are using to represent the tools and processes to automate the configuration of various IT applications and the 100,000+ connections between IT and OT endpoints, once the code (application/model) is deployed to production.
DevOps Is the set of tools and practices to automate the packaging and deployment of traditional code into production environments. ModelOps is the evolving set of tools and practices to automate the packaging and deployment of AI/ML models into production environments.
Working with GE Digital
GM has a longstanding relationship with GE Digital, with more than 30 years of leveraging their manufacturing software technology. We have several manufacturing IT applications based on GE Digital’s software platform, so as we started thinking about our MES 4.0 architecture, we naturally had discussions with GE Digital to get their perspective and advice.
From these discussions we realized that GE Digital’s HMI/SCADA platform, CIMPLICITY, and industrial data historian, Proficy Historian, could support our vision of MES 4.0 and become a key layer in our architecture.With it, we’ve created a library of reusable templates. These “device twins” are digital analogs of OT devices, and serve as communications proxies between OT and IT.
As we move closer to smart manufacturing in the automotive industry, the immediate need to redefine today’s manufacturing technology to meet our future customers’ needs is becoming more and more important. As software footprint in OT solutions continues to grow it is essential that we make the synergy between OT and IT as seamless and powerful as possible.
In the words of Gerald Johnson, GM’s EVP of Global Manufacturing and Sustainability: “Manufacturing is our strength and our competitive advantage.” For us that means faster, safer, cleaner manufacturing throughout our systems and operations. To dive into General Motors manufacturing technology journey, please check out my recent webinar: General Motors: Redefining today’s manufacturing technology for tomorrow’s customer.
General Motors: Redefining Today’s Manufacturing Technology for Tomorrow’s Customer
Automotive manufacturers continue to face extreme disruption on multiple fronts and time horizons. A global pandemic resulting in component shortages, demand for personalization, the shift to electrification and the resulting race for market share, as well as sustainability expectations, will shape which brands dominate the future and which fade into history.
Learn from General Motors and they embark on a path to secure their future, by redefining its manufacturing technology today. This shift involves designing a converged architecture spanning OT and IT systems, driving simplicity and better visibility across operations with a unified technology stack, and a focus on building a digital thread across operations.