AI-based path planning optimization for laser welding pro-cesses (T10#)

• Subject Area: Primary Shaping and Reshaping Technology, Additive Manufacturing
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 236616214

The project “AI-based path planning optimization for laser welding processes” aims to optimize the Directed Energy Deposition (DED) process by developing and integrating an adaptive track width control. The focus is on the dynamic adaptation of process parameters to improve dimensional accuracy, shape accuracy and material consumption. An essential component is the application of heuristics to predict and adapt process parameters, supported by modern models. This includes comparing classic statistical methods with innova-tive AI-based approaches, such as an artificial neural network (ANN), to precisely record the melt pool geometry and dynamically adapt the path planning. The collaboration with ModuleWorks enables the integration of these models into the existing software environment, which promotes the industrial implementation of adaptive path planning and process optimization. The solutions developed improve production quality, shorten process times, and reduce material consumption.

• DFG Programme: Collaborative Research Centres (Transfer Project)
• Subproject of: SFB 1120: Precision manufacturing by controlling melt dynamics and solidification in production processes
• Applicant Institution: Rheinisch-Westfälische Technische Hochschule Aachen
• Business and Industry: ModuleWorks GmbH
• Project Head: Professor Dr.-Ing. Johannes Henrich Schleifenbaum