Heuristic classification for automated CAPP

Abstract

In order to create a process plan from a workpiece description, a human expert thinks in a special terminology with respect to the given workpiece. The steps of human thinking during the generation process of a process plan are following the principles of heuristic classification: First using feature recognition an abstraction process isrealized yielding a high level (qualitative) description of the current workpiece in terms of features. To these features certain (more or less) abstract (partial) process plans--the so-called skeletal plans--are associated. In the refinement step these skeletal plans are merged together to one complete process plan. In this paper we present a set of domain-oriented higher level representation formalisms for features and skeletal plans suitable for the modeling of this approach. When an expert's (process planner's) knowledge has been represented using these formalisms, the generation of a process plan can be achieved by heuristic classification. This is demonstrated in the CAPP-system PIM, which is currently implemented as a prototype.