Abstract
This work presents an improved genetic algorithm (IGA) for minimizing periodic preventive maintenance costs in series-parallel systems. The intrinsic properties of a repairable system, including the structure of reliability block diagrams and component maintenance priorities are considered by the proposed IGA. The proposed component importance measure considers these properties, identifies key components, and determines their maintenance priorities. The optimal maintenance periods of these important components are then determined to minimize total maintenance cost given the allowable worst reliability of a repairable system. An adjustment mechanism is established to solve the problem of chromosomes falling into infeasible areas. A response surface methodology is further used to systematically determine crossover probability and mutation probability in the GA instead of using the conventional trial-and-error process. A case study demonstrates the effectiveness and practicality of the proposed IGA for optimizing the periodic preventive maintenance model in series-parallel systems.
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References
Birnbaum, Z.: On the importance of different components in a multicomponent system: Multivariate Analysis 11. In: Krishnaiah, P.R. (ed.), Academic Press, London (1969)
Bris, R., Chatelet, E., Yalaoui, F.: New method to minimize the preventive maintenance cost of series–parallel systems. Reliability Engineering and system safety 82, 247–255 (2003)
Busacca, P., Marseguerra, M., Zio, E.: Multiobjective optimization by genetic algorithms: application to safety systems. Reliability Engineering and system safety 72, 59–74 (2001)
Fussell, J.: How to calculate system reliability and safety characteristics. IEEE Transactions on Reliability 24, 169–174 (1975)
Goldberg, D.: Genetic Algorithms in Search and Optimization. Addison-Wesley, Reading (1989)
Holland, J.: Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor (1975)
Leou, R.: A new method for unit maintenance scheduling considering reliability and operation expense. International Journal of Electrical Power and Energy Systems 28, 471–481 (2006)
Lie, C., Chun, Y.: An algorithm for preventive maintenance policy. IEEE Transactions on Reliability 35, 71–75 (1986)
Marseguerra, M., Zio, E.: Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliability Engineering and system safety 68, 69–83 (2000)
Montgomery, D.: Design and analysis of experiments. Wiley, Hoboken (2005)
Muller, A., Crespo Marquez, A., Iung, B.: On the concept of e-maintenance: review and current research. Reliability Engineering and system safety 93, 1165–1187 (2008)
Samrout, M., Yalaoui, F., Chatelet, E., Chebbo, N.: New methods to minimize the preventive maintenance cost of series–parallel systems using ant colony optimization. Reliability Engineering and system safety 89, 346–354 (2005)
Shieh, H., May, M.: Solving the capacitated clustering problem with genetic algorithms. Journal-Chinese Institute of Industrial Engineers 18, 1–12 (2001)
Tsai, Y., Wang, K., Teng, H.: Optimizing preventive maintenance for mechanical components using genetic algorithms. Reliability Engineering and system safety 74, 89–97 (2001)
Tsai, Y., Wang, K., Tsai, L.: A study of availability-centered preventive maintenance for multi-component systems. Reliability Engineering and system safety 84, 261–270 (2004)
Wang, H.: A survey of maintenance policies of deteriorating systems. European Journal of Operational Research 139, 469–489 (2002)
Rausand, M., Hoyland, A.: System reliability theory: models, statistical methods, and applications. Wiley-IEEE (2004)
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Wang, CH., Lin, TW. (2010). Improved Genetic Algorithm for Minimizing Periodic Preventive Maintenance Costs in Series-Parallel Systems. In: Hsu, CH., Yang, L.T., Park, J.H., Yeo, SS. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2010. Lecture Notes in Computer Science, vol 6081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13119-6_8
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DOI: https://doi.org/10.1007/978-3-642-13119-6_8
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