Planning and scheduling in semiconductor manufacturing

Semiconductor manufacturing is one of the most complex existing manufacturing systems. It requires constant improvement to meet demands and expectations. This dissertation studies semiconductor manufacturing under three main topics, preventive maintenance scheduling, lot size management and AMHS scheduling. We first provide an optimization based decomposition algorithm and a heuristic algorithm to solve preventive maintenance scheduling problem along with direct optimization. Then, we develop an analytic tool to investigate and find optimal lot sizes to run in a manufacturing environment to minimize cycle time. Finally, we propose an optimization based AMHS scheduling algorithm and compare its performance to a myopic algorithm.