Abstract
This paper focuses on a preventive maintenance plan and production scheduling problem under reentrant Job Shop in semiconductor production. Previous researches discussed production scheduling and preventive maintenance plan independently, especially on reentrant Job Shop. Due to reentrancy, reentrant Job Shop scheduling is more complex than the standard Job Shop which belongs to NP-hard problems. Reentrancy is a typical characteristic of semiconductor production. What is more, the equipment of semiconductor production is very expensive. Equipment failure will affect the normal production plan. It is necessary to maintain it regularly. So, we establish an integrated and optimal mathematical model. In this paper, we use the hybrid particle swarm optimization algorithm to solve the problem for it is highly nonlinear and discrete. The proposed model is evaluated through some simple simulation experiments and the results show that the model works better than the independent decision-making model in terms of minimizing maximum completion time.
Highlights
IntroductionIn 1993, Kumar [1] proposed the third mode of production, reentrant production, which was different from common Job Shop or Flow Shop when he studied the semiconductor manufacturing process
This paper focuses on a preventive maintenance plan and production scheduling problem under reentrant Job Shop in semiconductor production
In 1993, Kumar [1] proposed the third mode of production, reentrant production, which was different from common Job Shop or Flow Shop when he studied the semiconductor manufacturing process
Summary
In 1993, Kumar [1] proposed the third mode of production, reentrant production, which was different from common Job Shop or Flow Shop when he studied the semiconductor manufacturing process. Reentrancy means that the same job, at various processing stages, may wait for processing before the same device or the workpiece, at different stages of processing, visits the same device repeatedly. This feature makes the process even more intense when different jobs are processed in the same machine, which will undoubtedly make scheduling more difficult. With the rapid development of semiconductor industry, the reentrant Job Shop scheduling problem (RJSP) has gotten more and more attention recently. The proposed model is evaluated through simulation experiments and the results show that the model works better than the independent decision-making model in terms of minimizing maximum completion time
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