Part family identification using a simple genetic algorithm

Past research in part family identification has focused mainly on the development of efficient procedures for manufacturing-oriented part family formation in which similarities among parts are established primarily on machine or operation requirements. While these part families are essential in cellular manufacturing, they are not well suited for other areas of production, in particular, part design and process planning. A new part family identification technique using a simple genetic algorithm is proposed in this paper to first determine a set of part family differentiating attributes and second to use these attributes to guide the formation of part families. Empirical analyses of the technique on both artificially generated data and a real application are performed and discussed.