Manufacturers have had a long-standing goal of overcoming IT (information) and OT (operational) data siloes to gain end-to-end visibility of their entire business from the top floor to the shop floor and beyond. This is vital to drive down risk and costs while boosting sustainability and outputs. Until now, it’s proven easier said than done.

According to a report by The Manufacturer, just 23% of businesses have achieved more than a basic level of IT-OT convergence. In fact, 70% of manufacturers struggle to make operational data accessible for analysis and just 1% of generated data is currently being accessed and used to inform decisions, according to the Bureau of Labor Statistics. Within each production plant, there is a myriad of production lines, equipment and software systems each with their own unique purposes, protocols, and data formats. Due to entrenched interoperability and security challenges, using advanced AI at scale across manufacturers' entire ecosystem has proved difficult. But things are about to change.

Leverage the collective intelligence of your enterprise Developed with Accenture, our new solution – Avanade Manufacturing Copilot, powered by Manufacturing Data Solutions in Fabric – helps enterprises overcome this problem. It’s designed to democratize access to intelligence from a diversity of Manufacturing Execution System (MES), Computerized Maintenance Management Systems (CMMS), Quality Management Systems (QMS), Enterprise Resource Systems (ERP) and more. This is vital to supercharge the ask-an-expert capabilities of Microsoft Copilot and enable manufacturers to make higher-quality products faster with less waste.

What does it enable people to do? Frontline workers can ask questions about key performance metrics and troubleshoot manufacturing and supply chain problems using natural language rather than having to learn how to navigate a wide range of applications in their technology stack. There are many use cases:

Enhance quality control to reduce the risk of delays and product recalls Quality control is often a time-consuming and inefficient process in manufacturing. With Copilot, quality control managers no longer need to trawl through different manufacturing execution, materials management, and workforce scheduling systems to troubleshoot an issue. Instead, they can use one simple interface for an immediate answer.
Reduce energy usage for cost and carbon reduction co-benefits Many factors drive up energy usage. For example, machinery with worn-out parts that cause friction consumes more energy, as does unlubricated, overloaded, and idling equipment. Frontline workers are more easily able to benchmark machinery and plant performance and get to the root cause of a problem with copilot by their side.
Streaming report preparation for shift handover meetings Shift handover meetings take place several times a day. It is difficult and time-consuming for people to source data on production targets, quality control issues, equipment maintenance needs, safety concerns, personnel matters, and share progress on environmental topics like waste. With copilot, managers can easily access the data insights they need to summarize production output and issues from the last shift into an easy-to-use report.

For employees, this makes the difference between working overtime to solve complex problems and getting home promptly to see their family.

How does it work? By leveraging Microsoft’s graph-of-graph approach to knowledge management and the International Society for Automation’s open standard (ISA-95), we can help AI systems understand manufacturing data, processes, equipment, suppliers, and products from a diversity of knowledge graphs to overcome this challenge. Knowledge graphs help Large Language Models (LLMs) to find patterns, links and infer meaning, leading to very real business benefits. Our graph-of-graphs has a hierarchical structure to show how data insights in OT and IT systems and their data are interconnected. Accenture and Avanade also have a range of copilot accelerators for different use cases and are working with a number of private preview clients.

Who is using it? The solution is already being piloted by Schaeffler, Bridgestone, and others.

Schaeffler Schaeffler, a leading motion technology company, has embarked on a mission to democratize information access across their factory workforce. Employees can gain easy access to key metrics like scrap rates, yields (the proportion of usable or acceptable components), and energy usage over time using the chatbot. This will be vital to help drive cost and carbon reduction co-benefits.

“Artificial Intelligence, and in particular Generative AI, is already having an impact on the daily business at Schaeffler. Especially in the field of manufacturing and operations, the ongoing operationalization of AI solutions, combined with intensive training, enables us to optimize, rethink, and innovate the core of our company – our plants. As a leading motion technology company, Schaeffler has the ambition not only to participate but to proactively shape this ongoing transformation.”

Stefan Soutschek, Vice President Digitalization & Operations IT, Schaeffler

Bridgestone Bridgestone, the world’s largest tire and rubber company, is partnering with Accenture and Avanade to tackle disruptions and scheduling inefficiencies. A key focus is rate loss, which is a reduction in production efficiency or output caused by factors like machine breakdowns, setup time, material shortages, and defects. Their goal is to implement a natural language query system that enables contextualized analysis and information retrieval, catering to users with diverse levels of expertise.

It is establishing a centralized system that efficiently gathers and presents critical information from various sources and facilitates informed decision-making to enhance operational agility.

"We are excited to accelerate our industrial transformation with AI in partnership with Accenture, Avanade and Microsoft Cloud for Manufacturing, particularly we recognize the disruptive potential of generative AI, and true to our values, we want to be at the forefront of innovation equipping our front-line workers with powerful tools, like copilots, to optimize our operations."

Bart Kerhofs, VP IT for Bridgestone EMEA

Why does this matter? Manufacturing relies on complex, globally distributed supply and production processes. Every movement and handover between the links in this value chain is a chance for something to go wrong, yet it all needs to happen at breathtaking speed. Manufacturers need a total systems view of what is happening at each step to create customer satisfaction at the end point of delivery.

This revolutionary new technology can help manufacturers move toward a world of more autonomous operations in which production processes can take place with minimal human intervention. This is vital in an era of labor and skills shortages, rising production targets, and the need to cut costs and carbon emissions. An estimated 2.6 million Baby Boomers will retire from manufacturing jobs over the next decade according to the Society for Human Resource Management. A survey by Microsoft indicated that tech ranks as one of the top three factors that frontline manufacturing workers say could help relieve workplace stress.

We truly believe that generative AI will enable manufacturers to reinvent their design-make-and-use value chain, be a great employer, drive down costs and boost sustainability on a global basis.

Want to learn more?

Unlock IT-OT intelligence with copilot in manufacturing

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