Abstract

Actually, new applications of machine learning methods like variance-based sensitivity analysis take place for developing complex sheet metal forming and joining processes. The application of this methods will help to quickly start of production when the simple numerical designing of the processes becomes too complicated. Two investigated examples show the application of the method for complex planning situations. The first one uses variable functions of force and motion during deep drawing to extend the process limits. The second one describes the complex clamping of an assembly of different sheet metal parts. Field meta modelling approaches are shown to automate tasks, visualize results and support engineers to plan and run different complex processes regarding sheet metal parts.

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