Translating overall production goals into distributed flow control parameters for semiconductor manufacturing

Abstract

As manufacturing systems are often operated under distributed control, translating overall production goals, such as system output rate and cycle time, into local flow control targets for internal operations, such as work-in-process (WIP) levels and part release intervals, has been a significant and challenging research topic. This paper studies the problem for semiconductor wafer fabrication plants, where there are multiple part types, failure-prone machines, and deterministic reentrant process flows. Such a system is first modeled as a failure-free and reentrant open queuing network with an aggregated part type. By exploiting a decomposition-based approximation, a backward queuing network analysis (BQNA) is designed to derive flow control parameters in terms of means and variations of input processes for each machine group. These derived control parameters can be utilized to obtain managerially tangible requirements for cycle times and WIP levels and to create guidelines for distributed flow control leading to the desired overall production goals. Comparisons with simulation results for two example wafer fabrication models demonstrate the accuracy and computational efficiency of BQNA and its potential for real applications.