Thyssenkrupp bridges manufacturing skill gap with AI-powered copilots
Thyssenkrupp, a global manufacturing company, collaborated with Siemens and Microsoft to address a pressing shortage of skilled labor in their industrial engineering and operational processes. Through the adoption of Siemens Industrial Copilot, powered by Microsoft Azure OpenAI Service, thyssenkrupp enables both engineers and machine operators to interact with complex manufacturing machinery using natural language input—via text and, soon, voice. By integrating this copilot into their production workflow, they have accelerated programming, troubleshooting, and knowledge transfer. The solution allows even less experienced engineers to program machines, diagnose problems, and understand legacy code, significantly increasing efficiency and bridging generational knowledge gaps. The copilot securely leverages company-specific data in a private Azure cloud. With over 100 other manufacturers also piloting the copilot, the initiative is poised for global rollout.
- Organization
- thyssenkrupp Automation Engineering
- Industry
- Manufacturing
- Location
- Germany
- Published
- June 2025
Reported outcomes
Strategic outcomes
Primary read
Use case focus
Showing 3 of 3
- 1Natural Language Machine Programming for Engineers
- 2AI-assisted Troubleshooting and Code Explanation in Industrial Automation
- 3Voice-enabled Operator Support in Manufacturing
- Shortage of skilled labor in manufacturing engineering and machine operation.
- Traditional machine programming is slow, complex, and dependent on highly experienced staff.
- Lost productivity due to long learning curves for new engineers.
- Retiring workforce creates knowledge gaps in manufacturing processes.
- Legacy machine code is hard to interpret and update by new staff.
- Deployed Siemens Industrial Copilot powered by Azure OpenAI Service (GPT-4).
- Integrated natural language processing for programming, troubleshooting, and code explanation.
- Enabled voice and text communication with machines for operational support.
- Leveraged a private Azure cloud for data privacy and company-specific knowledge integration.
- Collaborated with Siemens to tailor the copilot to thyssenkrupp’s proprietary machines and workflows.
- Engineers with less experience can program machines quickly and solve problems autonomously.
- Accelerated troubleshooting and onboarding for both engineers and operators.
- Knowledge transfer from retiring experts is facilitated through AI explanations and code translation.
- Global deployment planned for 2025 within thyssenkrupp plants.
- Demonstrated strong adoption, with 100+ other manufacturers testing similar solutions.
Architecture
The Siemens Industrial Copilot runs in thyssenkrupp’s private Azure cloud. Engineers and operators interact with machine PLCs via Copilot, using natural language (English or German) for programming, code explanation, and troubleshooting. The solution combines Azure OpenAI Service (GPT-4) for language and reasoning, interfaces with proprietary manufacturing databases, and connects to machine sensors and cameras for real-time operation.
Implementation partners1
Sources & evidence3
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