Aframework fora goal-drivenapproachto grouptechnology applications using conceptual clustering

Abstract

This paper presents a goal-driven approach for group technology applications using conceptual clustering techniques to induce useful part families for GT applications. GT applications differ along the following lines: the part information to be represented, the technique for generating part groups and the evaluation of the part groups. The goals of a GT application should be considered at each stage for the results to be meaningful for that application. A framework for such a goaldriven approach is presented in this paper. The feasibility of the framework is demonstrated for two popular GT applications: design retrieval and part family formation for cellular manufacturing. A symbolic representation scheme is employed instead of traditional coding systems. Conceptual clustering, an inductive learning technique is used for generating part groups from the symbolic representation. The results from two case studies show that the proposed framework can effectively satisfy the goals of GT applications.