AI in machine tools: Revolution of industrial manufacturing

Contents of the article:

Page 1: EMO Hannover Demonstrates how AI Turns Machines into Partners
Page 2: AI reduces waste in injection molding, for example
Page 3: Autonomous Manufacturing Requires Learning Machines

Related Vendors

Datron AG

Verein Deutscher Werkzeug- maschinenfabriken e. V. (VDW)

tmts2026-ticec-banner-en-2000px (https://www.tmts.tw/en)

Taiwan Machine Tool & Accessory Builders' Association (TMBA)

Wuxi InfiMotion Technology Co., Ltd.

Autonomous Manufacturing Requires Learning Machines

Artificial intelligence also makes the dream of the self-learning machine tool a reality, it is stated further. The milling machine manufacturer and EMO exhibitor Datron, for instance, relies on the machine drawing on learned knowledge and adjusting the production process accordingly. The Datron milling machine is thus set to evolve into a learning manufacturing cell that can automatically adapt to part requirements and environmental conditions. "This not only reduces setup and machining times but also increases process stability—a crucial step toward autonomous manufacturing," comments Jonas Gillmann, CTO of Datron. AI shifts the focus away from rigid programming toward assisted, learning, and thus adaptive manufacturing. Machines essentially become partners in the manufacturing process, adapting to humans rather than the other way around. In mechanical engineering, this is emphasized, it is no longer a vision but increasingly a lived reality. According to Gillmann, AI in production promises significant efficiency gains, as setup times in CNC production with Datron machines can be reduced by up to 60 percent, rejects decrease, and tool life increases—all while achieving higher process reliability!

AI Turns Machine Operators into Process Designers

A particularly exciting advancement, according to Gillmann, is the integration with the Datron-Next control system. This system intuitively guides even inexperienced operators through the milling process and automatically detects workpieces. This means that even non-specialized employees can quickly become productive in milling. Additionally, as Gillmann explains further, the AI will enable predictive maintenance in the future, as previously mentioned, to prevent breakdowns before they occur. This makes the milling process more efficient, robust, and significantly more flexible in terms of personnel. Artificial intelligence in machine tools can also help meet the growing demand for customized products with small batch sizes. "In this respect, AI makes manufacturing simply more economical. And with the Next control system, workpieces are automatically recognized—without complex programming," says Gillmann. This eliminates long setup times, and individual parts can be manufactured quickly, efficiently, and with high quality. With the self-learning machine tool, the role of the user also changes entirely. Put simply, this means less programming and more process responsibility. Machine operators in the machining field become process designers who ensure quality and optimize workflows. At the same time, the barrier to entry for the job is lowered, and knowledge is supplemented by smart assistance, but, as is often feared, not replaced.

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Date: 08.12.2025

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