Siemens AI tools use the principle of “human-machine collaboration” to help workers solve maintenance problems.

• Siemens is using AI to solve industrial problems such as safety and labor shortages.

• Siemens says its artificial intelligence tools such as Senseye improve productivity and reduce costs for customers around the world.

• This article is part of “The C-suite’s Guide to Artificial Intelligenceis a candid conversation from business leaders about how they are testing and using AI.

Siemens is a German technology company operating in many sectors, including industry, infrastructure, transport and healthcare. The company employs approximately 320,000 employees worldwide.

Situation analysis: what problem was the company trying to solve?

The industrial sector is facing several problemsincluding safety regulations, environmental sustainability and shortages of qualified experts. Peter Koerte, chief technology officer and chief strategy officer at Siemens, said the company aims to solve many of these problems using artificial intelligence.

“What’s most important for AI is that in an industrial context it needs to be safe, reliable and trustworthy,” he told Business Insider. Siemens, which has been investing in artificial intelligence for about 50 years, offers several industrial artificial intelligence products that help manufacturers in industries such as automotive and aerospace predict maintenance problems and improve productivity using data.

“We believe that if we can take data from the real world, model it, understand it in the digital world, we can work much faster for our clients, and our clients can become more competitive, more resilient and more resilient,” Kerte said. .

Key Personnel and Stakeholders

Koerte said Siemens is working with a number of technology partners on its industrial AI products and services, including Google, Microsoft, Nvidia, Amazon Web Services and Meta. The company has approximately 1,500 employees with artificial intelligence expertise who work closely with these technology companies, as well as Siemens’ internal product development teams.

AI in action

Siemens’ work in industrial artificial intelligence focuses on predictive maintenance, worker assistance technologies and generative product design.

One product – Senseye Predictive Maintenancea tool that integrates with manufacturer data sources and uses artificial intelligence to analyze the information. The company said the platform provides insight into how well machines, tools and other infrastructure are performing. The technology can also help predict maintenance issues, which improves productivity and helps companies accelerate technology adoption across their businesses.

Siemens recently debuted. Industrial co-pilotAI-powered generative assistant for engineers working in industrial environments. The assistant can automatically generate code, quickly identify problems, and provide advice to support engineering tasks such as troubleshooting hardware maintenance issues. The company said the tool could encourage “human-machine collaboration” and allow companies to address labor shortages while remaining competitive.

Kerte said that when Industrial Copilot notifies an employee of a hardware or software problem, that employee can use verbal commands in any language to create a work order that is automatically sent to a team in another country to take action to resolve the issue. . “AI is breaking down barriers and democratizing a lot of technology because we are taking the complexity out of it,” he said.

Did it work and how did leaders find out about it?

Siemens found that companies using Senseye Predictive Maintenance reduced maintenance costs by 40%, increased operator productivity by 55% and reduced the time a machine is unavailable for service by 50%.

Australian steel company BlueScope implemented a predictive maintenance platform in 2021 to minimize downtime at its plants, increase uptime, increase product speed and reduce costs. Together, Senseye and BlueScope IoT sensors can detect abnormal vibrations in equipment early, preventing maintenance problems and saving companies money.

Schaeffler Group, a German supplier of automotive and industrial products, has equipped a production machine with an Industrial Copilot system. Its engineers can now more quickly generate code for programmable logic controllers, the devices that control machines in factories. Siemens said the technology helps the Schaeffler Group automate repetitive tasks, reduce errors and free up engineers for “higher value work.”

What’s next?

Kerte said Siemens continues to research and develop new use cases for AI.

The company is working on a project that feeds computer-aided design data, such as models and digital drawings, into large language models and encourages them to create products.

The project is still in the early stages of development, but Kerte said it could allow design engineers, particularly in the automotive sector, to create more product variations and produce higher quality products faster.

Read the original article at Business Insider