Build Sequence Scheduling to Minimize Complexity in Mixed-Model Assembly Lines

Abstract

Build sequence scheduling is an important topic in mixed-model production. It is to determine the order of products being built in the assembly line. Significant research has been conducted to determine good sequences based on various criteria. For example, in Just-In-Time production systems, optimal sequences are searched to minimize the variation in the rate at which different parts were consumed. This paper discusses the selection of optimal build sequences based on complexity introduced by product variety in mixed-model assembly line. The complexity was defined as the information entropy that operator processes during assembly, which indirectly measures the human performance in making choices, such as selecting parts, tools, fixtures, and assembly procedures in a multi-product, multi-stage, manual assembly environment. In an earlier paper by the authors, a simple version of complexity measure has been developed for i.i.d. (independent identically distributed) sequences. This paper extends the concept and takes into account the sequential dependence of the choices and its impact on build sequence schedules. A model based on Hidden Markov Chain is proposed to model the sequence scheduling problem with the constraints by spacing rules. Methodologies developed in this paper enhance the previous work on modeling complexity, and provide solution strategies for build sequence scheduling to minimize complexity.