期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 146, 期 -, 页码 68-78出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2015.10.013
关键词
Preventive maintenance; Scheduling; Random keys; Genetic algorithms
资金
- National Natural Science Foundation of China [51035008]
- Fundamental Research Funds for the State Key Laboratory of Mechanical Transmission, Chongqing University [SKLMT-ZZKT-2012 MS 02]
Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. (C) 2015 Published by Elsevier Ltd.
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