Abstract
Cycle times are of order of ten weeks in most semiconductor wafer fabrication facilities (wafer fabs). They have to be explicitly considered in production planning. A nonlinear relation between resource workload and cycle time can be observed. In this paper, we study data-driven (DD) production planning formulations. These formulations are based on a set of system states representing the congestion behavior of the wafer fab with work in process (WIP) and resulting output levels. The effects of different WIP-output relations and additional capacity constraints in the DD models are investigated. Moreover, several methods are proposed to obtain representative sets of system states. The performance of the DD variants is compared with the performance of the allocated clearing function (ACF) model using a scaled-down simulation model of a wafer fab. Simulation results demonstrate that under certain experimental conditions, the DD models lead to similar profit and cost values as the ACF model.
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