The assembly line in question is a single-product line consisting of a set of workstations. In order to complete a product, various operations have to be processed, and technological precedence requirements exist among operations. Moreover, the processing time of a given operation differs largely among workers according to their work experience. Process planning for an assembly line includes not only operation assignment to line workstations (operation assignment sub-problem), but also worker allocation to the workstations (worker allocation sub-problem). The purpose of line process planning is to minimize the cycle time. In related research, we proved that a method where these subproblems are considered separately cannot obtain a good result. In this paper, an integrated method based on a genetic algorithm is proposed to simultaneously solve these sub-problems. In order to improve solution searching efficiency through crossover, we propose a method which focuses on the operations/workers that are assigned/allocated to the workstations with high or low workloads. At the same time, in order to obtain a good local optimum, we also propose two logics to avoid searching within a narrow solution area so that good solutions may be found. They are the gene similarity checking logic for parent chromosomes, and the gene correction logic for the defective child chromosomes. Compared to the separate method, the effects of our integrated proposal are confirmed for both shortening cycle time and decreasing line balance loss.
|Journal of Japan Industrial Management Association
|Published - 2007
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