TLDR: Siemens has partnered with leading machine tool manufacturers and research institutions to create a data alliance. This collaboration aims to facilitate the systematic exchange of engineering, manufacturing, and machine data to develop generative AI applications for industrial environments, paving the way for the Siemens Industrial Foundation Model.
Hanover, September 23, 2025 – Siemens, in collaboration with several prominent machine tool manufacturers including Grob, Trumpf, Chiron, Renishaw, and Heller, as well as the Machine Tool Laboratory (WZL) of RWTH Aachen and the Voith Group, has announced a groundbreaking data alliance. This partnership is designed to enable a systematic exchange of critical engineering, manufacturing, and machine data, which will be instrumental in developing new generative AI applications tailored for industrial settings.
This strategic collaboration represents a significant leap towards realizing the Siemens Industrial Foundation Model, a vision first unveiled at Hannover Messe 2025. The alliance’s primary objective is to substantially boost efficiency and accelerate innovation cycles within the manufacturing sector through the targeted deployment of AI technologies.
Roland Busch, CEO of Siemens AG, emphasized the importance of this initiative, stating, “Along with our customers and partners, we are taking a significant step today to scale industrial AI. I see a great opportunity here for the European economy and its strong industrial base – from automotive, chemicals, and pharmaceuticals to mechanical engineering, energy, healthcare, infrastructure, and transport among others. By making our companies’ unique data treasure available to create generative AI models, we can achieve totally new levels of productivity – and this data alliance in the machine-building industry is leading the way.”
One of the immediate and tangible benefits envisioned for the machine tool industry is the automated creation of part programs. These programs, which serve as ‘work instructions’ for specialized manufacturing machines, could be generated much faster, drastically reducing error rates in code creation. This automation would also free programmers from routine tasks, allowing them to concentrate on more complex and innovative challenges.
Busch further elaborated on the critical role of data, explaining, “Access to high-quality machine data from different manufacturers is the key. With this alliance, we can develop AI systems that reflect the complexity entailed in development and manufacturing, and so it will become a powerful partner for skilled workers.”
The partnership is founded on the secure and compliant exchange of anonymized machine data, adhering to stringent data protection and security standards. This data will be utilized to develop and train AI models specifically designed to meet the rigorous demands of industrial manufacturing. Beyond automated NC program creation, other anticipated use cases include predictive maintenance with precise machine-specific forecasts, adaptive manufacturing processes that adjust in real-time to changing conditions, and optimizing energy efficiency through intelligent control of machine parameters.
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The long-term strategy of this alliance extends beyond the machine tool industry, aiming to onboard more companies from diverse sectors to broadly leverage industrial artificial intelligence.
