Asymmetric cycle time bounding in semiconductor manufacturing: an efficient and effective back-propagation-network-based method

Abstract

Estimating the cycle time of every job in a semiconductor manufacturing factory is essential. However, because cycle times are uncertain, determining the cycle time range is also crucial. Manufactures use the lower bound of a cycle time to promise an attractive due date to customers and the upper bound to indicate the latest possible time that fabrication will be completed. Thus, an interval estimate of cycle time is preferable to a point estimate. In several previous studies, a symmetric interval estimate has been derived from a probabilistic perspective. However, the managerial implications of the upper and lower bounds differ, and an asymmetric interval estimate is more useful. Therefore, this paper proposes a back-propagation-network-based approach to estimating the job cycle time and determining the cycle time range. A real case from a semiconductor manufacturing factory was used to illustrate the proposed method. According to the results, the estimates of the job cycle time obtained using the proposed method were precise and accurate. The established upper and lower bounds (especially the lower bound) were much tighter than those used in existing methods.