With its manufacturing clients and at its Smart Factory research facility in Wichita, Kansas, Deloitte is exploring applications for generative AI (Gen AI) across many industry sectors and a wide array of applications. Plant Services spoke with Tim Gaus, who is the principal and smart manufacturing lead for Deloitte, about current applications of Gen AI in manufacturing. He works with manufacturers on the use of technology in the transition to smart manufacturing, including artificial intelligence (AI) and Gen AI.
For any kind of artificial intelligence, an organization’s data foundation is the key to unlocking the potential, Gaus says. “We actually have spent a lot of time and energy helping customers get that data model in place and in the right structure for scale,” Gaus says.
AI is the key to the convergence of operational technology (OT) and informational technology (IT) and is making breaking down those siloes easier. Making equipment or processes “smart,” Gaus says, involves understanding how to take an asset in the physical world, bring it into the digital world to do something different or get a different outcome, and then bring that back to the physical world. “It’s creating that closed loop across the two different domains,” he adds.
AI in manufacturing: predictive analytics, smart vision systems and Gen AI
Deloitte is working with a manufacturing client to use vision systems and its security cameras with an AI neural network to detect and predict likely safety outcomes in operations. Gaus points to the very human impact of how this could change safety culture and the way it is thought about within the manufacturing environment.
Another client is using AI in its high-speed manufacturing facility to do predictive analytics for process control. The system requires very low latency, so it needs edge and cloud technology to bring the power of AI in real-time to the plant floor. “They are really pushing the edge of how an artificial intelligence, or at least the predictive nature and the machine learning elements, can intersect day-to-day operations,” Gaus says.
Manufacturing is uniquely positioned to harness the power of Gen AI in a very real way, Gaus says. “The ability to consume and contextualize different forms of information and bring that into a form where it’s accessible for a much more human interaction is the real unlock,” Gaus says. “How do we capture the intelligence of all the things that we do, that we have records for?”
Gen AI models allow businesses to do that with PowerPoint slides, email conversations, reports, meeting transcripts and more, and that becomes a base of knowledge accessible to everyone in a way it wasn’t available before. “You have this copilot to help access that knowledge of the people,” Gaus says.
Large language models, which power generative AI, are as useful for understanding and contextualizing different inputs and information and consolidating them, as much as they are for producing extra material from that data. Think of it as an infinite filing cabinet that can instantly answer questions about your business, processes, decisions, planning, you name it. It stores and contextualizes what the business feeds it. “You start to see the power [Gen AI] could have in a very knowledge-centric perspective,” Gaus says.
Deloitte has clients that have invested in private large language models for storing and contextualizing information like equipment manuals and maintenance records, making the information accessible to technicians in a conversational interface and democratizing information access.
Smart Factory for a brownfield world
Deloitte operates a fully functional production facility in Wichita, Kansas, for its clients and partners. “We created this because we know manufacturing was radically changing, and we needed to have a spot to help our clients get their heads around that,” Gaus says. Deloitte also sees the factory as a support for developing future engineers and the future of manufacturing.
The production facility has been fully functional since June 2022, and Deloitte has had hundreds of clients come through its door. Deloitte is not operating this project alone, and it has a large, curated ecosystem of partners, including Amazon Web Services, Siemens, SAP, HPE, Cisco, Verizon and more. They include very established players in technology and startups as well, Gaus says. “Our strong belief is that there is no single provider that can solve all the problems that manufacturers face today,” he adds.
Among some of the examples already mentioned, clients at the Smart Factory have explored process optimization using historical machine data and Gen AI to determine optimal setpoints and running conditions for maximizing process efficiency. Traditionally, factory layouts are created via experience, Gaus says, but Gen AI can create more optimized space with data.
Another client is using Gen AI to consume all its periodic conversations around planning decisions and why those decisions were made. “A classic SOP or integrated business planning process and then how that cascades to a scheduling process and the plant floor, that's all being loaded into a generative AI engine,” Gaus says.
The other thing that was done intentionally at the Smart Factory was to not make it pristine. “We could have created the lights out factory of the future, but quite frankly, none of our clients have that luxury. They live in a brownfield world,” Gaus says.
“The reason we built a truly functioning manufacturing line is we feel that innovation out of the lab doesn't have the same quality to it. We want to actually test it in the real world,” Gaus says.
