Using a Clustering Approach with Evolutionary Optimized Attribute Weights to Form Product Families for Production Leveling

Abstract

Production leveling aims at balancing production volume as well as production mix. Conventional leveling approaches require limited product diversity and stable, predictable customer demands. They are well-suited only for large scale production. This paper presents a methodology that enables the leveling of low volume and high mix production. It is based on two fundamental steps. In the first step, which is focused on in this paper, product types are grouped into families according to their manufacturing similarity. In the second step, a family-oriented leveling pattern is generated. This paper presents an innovative clustering approach for product family formation regarding leveling. It employs evolutionary strategies to optimize the weights of the attributes which are used for clustering according to their impact on the grouping result. The paper refers to an industrial application and also shows how product families can be utilized for leveling.