Retrieval of process methods from task descriptions and generalized data representations

摘要

Intelligent machines are supposed to set process parameters automatically when faced with a task to be processed. The intelligence is often realized by databases linking the task with process parameters. This paper introduces a flexible and portable (to various processes) system to find (optimized) process parameters, which force the process outcome to predefined quality under given, variable conditions. The process knowledge is extracted from experiments and represented by a generalization in the form of so called goal-functions based on support vector methods. A level set method is proposed to find all process parameters which fulfill a given task. We also provide experimental results based on numerical simulations applied to Resistance Spot Welding to demonstrate the usability of the concept. Promising numerical results concerning the accuracy of process parameters and the process outcome approve the concept for the implementation on real process machines.