Machine learning based toolpath optimization for multi-stage incremental forming

The study aims to generate an optimal toolpath for Incremental Sheet Forming (ISF) of metal sheets in order to improve accuracy and enhance the process limits. Already gained experience with Single Point Incremental Forming (SPIF) will be used as a starting point in the approach, where the accuracy will be optimized by applying machine learning techniques. The toolpath optimization for multi staged ISF processes will be investigated to enhance the process window. The optimized toolpaths and the corresponding increase in accuracy and process window will lead to a promising sheet forming technique that will be applicable on larger scale.