Computation of Manufacturing Complexity in a Mixed Model Assembly

Abstract

Manufacturing systems have evolved to adopt a mixed-model assembly systems in order to enable the production of high product variety. Mixed-model assembly systems offers a wide range of advantages, however, as variety increases, the system becomes very complex, thus worsening the system performance. This paper proposes a novel method for complexity quantification in a mixed model assembly line. The model uses the information entropy and considers both the options count as well as the relationship among options. The resulting measure not only serves an input in the assessment of the impact of the complexity on the system performance, specifically on human error; but also provides an insight on how the complexity can be mitigated without affecting the overall manufacturing throughput.