• Siemens is using artificial intelligence to address industrial challenges such as safety and labor shortages.

• Siemens says its AI tools, such as Senseye, increase productivity and reduce costs for global customers.

• This article is part of “CXO AI Playbook“ — direct discussions from business leaders on how they are testing and using AI.

Siemens is a German technology company that operates in many sectors, including industry, infrastructure, transportation and healthcare. It has approximately 320,000 employees worldwide.

Situation Analysis: What problem was the company trying to solve?

The industrial sector is facing more challengesincluding safety and security regulations, environmental sustainability and lack of qualified experts. Peter Koerte, Siemens’ Chief Technology Officer and Chief Strategy Officer, said the company aims to solve many of these problems with artificial intelligence.

“What’s most important for AI is that, in an industrial context, it has to be safe, it has to be reliable, and it has to be trusted,” he told Business Insider. Siemens, which has been investing in AI for around 50 years, offers more AI industrial products that helps manufacturers in various industries, such as automotive and aerospace, predict maintenance issues and improve worker productivity using data.

“We believe that if we can take data from the real world, simulate it, understand it in the digital world, we can be much faster for our customers, and our customers can be more competitive, more resilient and more sustainable,” Koerte said. .

Key personnel and stakeholders

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

AI in action

Siemens’ industrial AI work focuses on predictive maintenance, technology to assist workers and generative product design.

A product is Senseye Predictive Maintenancea tool that integrates with a manufacturer’s data sources and uses AI to analyze the information. The company said the platform provides information on how well machinery, tools and other infrastructure are performing. Technology can also help predict maintenance issues, which increases productivity and helps companies accelerate technology adoption within their businesses.

Recently, Siemens debuted Industrial pilotan AI-powered generative assistant for engineers in industrial environments. The assistant can automatically generate code, quickly identify problems, and provide advice to support engineering tasks such as troubleshooting equipment maintenance. The company said the tool can boost “human-machine collaboration” and enable companies to address labor shortages while remaining competitive.

Koerte said that when Industrial Copilot notifies a worker of a problem with equipment or software, that employee can use verbal commands in any language to create a work order, which is automatically sent to a team in another country to take action to solve the problem. . “AI is breaking down barriers and democratizing a lot of technology because we’re taking the complexity out of it,” he said.

Did it work and how did the leaders know?

Siemens has found that companies using Senseye Predictive Maintenance have low maintenance costs by 40%, increased the productivity of maintenance staff by 55% and decreased the time a machine is unavailable for maintenance by 50%.

Australian steel company BlueScope implemented the predictive maintenance platform in 2021 to minimize downtime at its plants, increase uptime, improve the rate at which it can produce products and reduce costs. Together, Senseye and BlueScope IoT sensors can detect abnormal vibrations in equipment early, preventing maintenance issues and saving the company money.

Schaeffler Group, a German automotive and industrial supplier, scaled up a production machine with Industrial Copilot. Its engineers are now able to generate faster code for programmable logic controllers, the devices that control machines in factories. Siemens said the technology helps Schaeffler Group automate repetitive tasks, reduce errors and free up engineers for “higher-value work.”

What’s next?

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

The company is working on a project that provides computer-aided design data, such as models and digital drawings, in large language models and leads it to create products.

The project is still in the early stages of development, but Koerte said it could allow design engineers, particularly in the automotive sector, to create more product variants and produce higher-quality items more quickly.

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