Cycle Time Analysis for Air Plane Part Production Based on Rough Clustering

Abstract

Abstract: Usually, production cycle time for air plane parts has a significant fluctuation. Thus, it is omportant to accurately estimate such a cycle time. To do so, an advanced k-means clustering algorithm based on rough set theory is proposed for cycle time analysis. With the proposed algorithm, the actual samples are clustered with respect to production cycle time by using upper approximation, lower approximation, and overlapping relationship between clusters. Simulation results for practical instances indicate that the cycle time obtaied by the proposed algorithm is useful for production scheduling and capacity planning.

Key words: production cycle time, Job-shop, rough set theory, k-means clustering

Tu Yuan-zhi, Sun Shu-dong, Li Qing-he, Wang Meng. Cycle Time Analysis for Air Plane Part Production Based on Rough Clustering[J]. Industrial Engineering Journal , 2012, 15(4): 119-124.

References

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