How Can An Organisation Position Itself With An Industrial AI Grade? A Siemens Case Study

As Generative AI takes over the world of business and technology, one concept is critical for companies and organisations, Industrial AI Grade. With Digital Industries software and Siemens Accelerator Business Program, Siemens is at the vanguard of this transformation, pioneering advancements in Industrial AI that set the benchmark for innovation and operational excellence worldwide. How does Siemens drive this innovation, particularly in the realm of Industrial AI

Siemens leads AI innovation in Europe and the global advancement of Industrial AI. With its worldwide AI research centres anchored in Germany, the company spearheads the global development in Industrial Grade AI.

What is Industrial AI? Industrial AI refers to the application of AI in an industrial context designed to meet the rigorous requirements and standards of the most demanding industrial environments. With the ability to handle big data from machines and to detect complex patterns, Industrial AI is helping to supercharge digital and sustainability transformation with speed and scale.

The industrial sector needs digital transformation toward greater sustainability and resilience. Value creation and actions for the planet must be brought into balance. Companies need to do more with fewer resources.

I spoke recently with Michael May, Head of Data Analytics & Artificial Intelligence, about Industrial AI and how Siemens builds advanced technology products and software using the power of AI and what it can bring to Industries in general and digital twins - the Industrial Metaverse. He also highlights the need to up-skilling artificial intelligence:

“Developing and operating industrial-grade AI is an urgent team effort that starts with a set of required skills that rarely exist within one company. Automation expertise combined with IT/OT integration skills is essential. Business domain expertise, that is, access to ground truth, is a prerequisite for a robust AI model that will be performing in an industrial environment. And, finally, solid AI expertise is required.”

Collaboration: A Siemens’ strategy for Industrial AI

With as fast moving an industry as AI is, it is often startups that are best able to quickly realise and bring to market a concept powered by the latest AI advancements. However, when it comes to bringing those solutions into production, many companies would prefer the long track record and proven reliability brought by larger, more established partners. This is why, when it comes to building industrial-grade AI, partnership is key - between startups and established companies as well as between developers and clients.

“Together with our partners, we will be showcasing how innovations like AI, digital twins, and software-defined automation can help customers address multiple challenges. From increasing competitiveness, reducing costs, overcoming labour shortages, or increasing sustainability, Siemens has the technologies that industries need right now,” said Roland Busch, President and CEO of Siemens AG.

With key partnerships with tech giants like Microsoft, Siemens focuses on integrating AI with operational technologies to enhance efficiency and foster digital transformation. These collaborations have been pivotal in advancing projects such as the Siemens Industrial Copilot and digital twin technologies, providing practical, AI-driven solutions to real-world challenges. 

I spoke with Boris Scharinger, AI Strategist at Siemens Digital Industries, about the importance of Industrial AI:

“Let's make AI industrial great together, because the autonomous car cannot be built by a car maker alone. The autonomous car is something that requires that insurance companies buy in, politicians change the law, certification bodies understand what they need to do, and car builders need to improve the technology. With industrial AI, it's the same thing. We need to solve several challenges together to make it a lot more ubiquitous than it is today.”

How can a business create up-skilling an artificial intelligence – and how does that work?

Siemens Digital Industries Software helps organisations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimise their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.

“Simulation and digital twins are essential”, says Boris. “By simulating designs and processes before implementing them, we can optimise resource consumption and improve efficiency on a component, machine, line, and plant level. This holistic approach helps us reduce our resource footprint.”

Michael May, Head of Company Core Technology Data Analytics & AI, Siemens, says:

“The artificial neural networks – the technology behind ChatGPT – consist of a large stack of specifically designed neuronal layers that follow a so-called “transformer”-architecture. Although this is extremely powerful and broad, for many cases the AI lacks the very detailed domain knowledge needed in industrial applications.

Similar to a human who is not born as an engineer, we need to educate or fine-tune the AI models and sometimes even re-train the upper layers of the network with more technological and domain data, so that the AI can really give substantial factual answers and support to engineers. If we don’t do this, the models at a certain point will start to invent their answers, or “hallucinate”.

In order to solve this, we are collaborating with Microsoft to train ChatGPT. One goal is to enable engineering teams to reduce time and errors by generating code through natural language inputs. This will also help maintenance teams identify errors and generate step-by-step solutions more quickly. These capabilities have the potential to transform how industries approach their processes and workflows.”

Building a robust future with Industrial AI Grade

Artificial intelligence as a technology is changing the foundations of businesses but getting it ready for deployment in the rigours of industry will be no simple matter. Industrial grade AI, built to a high standard of reliability and with the support of partners, will be a key part in the digital transformation journey of many companies and industries going forward. While it won’t be an easy task, the benefits that industry stands to reap from it more than make up the cost as AI positions itself as a key technology for the world of tomorrow.

To finish, I want to highlight some more material of my interview with Boris Scharinger, AI Strategist at Siemens Digital Industries:

“Generative AI can really support high-cost labor tasks. It's a democratisation of AI that allows people to try out new things but going from 80% to 100% maturity in use cases is challenging. At Siemens, we're proud of our engineering culture that helps us navigate these challenges and create industrial-grade AI solutions.

In Hamburg, we have a factory that has maintained the same number of employees and floor space over 20 years but has increased output by a factor of 19 through digital initiatives. Automating processes doesn't eliminate jobs; it creates new opportunities for roles in our international factory network.”