Optimization of laser cut edges with AI: Trumpf's Cutting Assistant

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With the Cutting Assistant, Trumpf demonstrates at the Intech in-house exhibition a way to improve the quality of cut edges in laser cutting using artificial intelligence (AI) ...

To optimize the edge of laser-cut components with the help of artificial intelligence, the production worker first takes a picture of the component's cut edge with a handheld scanner, as Trumpf explains. The AI tool then assesses the edge quality based on objective criteria (such as burr formation). With this information, the Cutting Assistant's optimization algorithm suggests improved parameters for the cutting process. The machine then cuts the sheet again. If the edge quality still does not meet expectations, the process can simply be repeated. As the Ditzingen laser experts emphasize, no experience in laser cutting is required for this. Users not only overcome the skilled labor shortage but also save time and costs, leading to a productivity boost and better competitiveness. The new AI system is now available for all Trulaser series with a power of six kilowatts or more. Those who already have such a Trumpf laser cutting machine can usually retrofit the Cutting Assistant easily.

When laser cutting, users often have difficulty determining the right parameters for their material types. For materials not optimized for laser cutting, the quality of the cut edge often varies, and the production worker must adjust the processing parameters accordingly. However, this consumes time and requires experience because each individual parameter must be adjusted sequentially, as Trumpf notes. This presents challenges for many companies, especially when, as is often the case today, they employ inexperienced workers in production. However, the Cutting Assistant is integrated into the machine's software. Therefore, the optimized parameters can be seamlessly transferred to the software without programming. This not only saves time but also avoids errors.

The Trumpf experts have cut thousands of parts in advance and incorporated their in-depth expertise to develop the Cutting Assistant. This is how they trained the algorithm. However, the work is not yet finished! In the future, data from field applications will also be added to the system. This approach enables even faster and more reliable results as the self-learning system continuously improves. Trumpf ensures that the algorithm does not disseminate the user's expertise, as emphasized. Users will then regularly receive online updates that they can download to their machines.