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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 6758147, 9 pages
Research Article

Integrating Preventive Maintenance Planning and Production Scheduling under Reentrant Job Shop

1School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China
2Business School, Shanghai Dianji University, Shanghai 201306, China

Correspondence should be addressed to Huimin Ma; moc.361@18mham

Received 18 October 2016; Revised 2 February 2017; Accepted 7 February 2017; Published 19 March 2017

Academic Editor: Alberto Borboni

Copyright © 2017 Ruiqiu Li and Huimin Ma. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.