Abstract
This study presents a hybrid genetic algorithm (GA) to optimize the periodic preventive maintenance model in a series-parallel system. The intrinsic properties of a repairable system, including the structure of reliability block diagrams, maintenance priority of components, and their maintenance periods, are considered in developing the proposed hybrid GA. The importance measure of components is employed to account for these properties, identify important components, and determine 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 using the GA search mechanism. An elitist conservation strategy is applied to retain superior chromosomes in the iterative breeding process to accelerate the approach toward the global optimum. Furthermore, the response surface methodology is utilized 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 hybrid GA in optimizing the periodic preventive maintenance model in a series-parallel system.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baker B. M., Ayechew M. A. (2003) A genetic algorithm for the vehicle routing problem. Computers & Operations Research 30: 787–800
Busacca P., Marseguerra M., Zio E. (2001) Multi-objective optimization by genetic algorithms: application to safety systems. Reliability Engineering & System Safety 72: 59–74
Bris R., Chatelet E., Yalaoui F. (2003) New method to minimize the preventive maintenance cost of series–parallel systems. Reliability Engineering & System Safety 82: 247–255
Chen J. S., Pan J., Chao H., Lin C. M. (2008) A hybrid genetic algorithm for re-entrant flow-shop scheduling problem. Experts System with Applications 34: 570–577
Duarte J. A. C., Craveiro J. C. T. A., Trigo T. P. (2006) Optimization of the preventive maintenance plan of a series components system. International Journal of Pressure Vessels and Piping 83: 244–248
Elsayed, E. A. (eds) (1996) Reliability engineering. Addison Wesley, Longman, MA
Gen M., Cheng R. (1997) Reliability optimization problems genetic algorithms and engineering design. Wiley, New York
Hsieh Y. C., Chen T. C., Bricker D. L. (1998) Genetic algorithms for reliability design problems. Microelectronics Reliability 38: 1599–1605
Iung B. (2003) From remote maintenance to MAS-based e-maintenance of an industrial process. Journal of Intelligent Manufacturing 14(1): 59–82
Jia H. Z., Nee A. Y. C., Fuh J. Y. H., Zhang Y. F. (2003) A modified genetic algorithm for distributed scheduling problems. Journal of Intelligent Manufacturing 14(3): 351–362
Lie C. H., Chun Y. H. (1986) An algorithm for preventive maintenance policy. IEEE Transactions on Reliability 35(1): 71–75
Leou R. C. (2006) A new method for unit maintenance scheduling considering reliability and operation expense. Electrical Power & Energy Systems 28: 471–481
Marseguerra M., Zio E. (2000) Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliability Engineering & System Safety 68(1): 69–83
Montgomery D. C. (2005) Design and analysis of experiments (6th ed.).Wiley, Massachusetts
Muller A., Marquez A. C., Iung B. (2008) On the concept of e-maintenance: Review and current research. Reliability Engineering & System Safety 93: 1165–1187
Pham H., Wang H. Z. (1996) Imperfect maintenance. European Journal of Operational Research 94: 425–438
Samrout M., Yalaoui F., Chatelet E., Chebbo N. (2005) New methods to minimize the preventive maintenance cost of series–parallel systems using ant colony optimization. Reliability Engineering & System Safety 89: 346–354
Samrout M., Kouta R., Yalaoui F., Châtelet E., Chebbo N. (2007) Parameter’s setting of the ant colony algorithm applied in preventive maintenance optimization. Journal of Intelligent Manufacturing 18(6): 663–677
Sheu D. D., Kuo J. Y. (2006) A model for preventive maintenance operations and forecasting. Journal of Intelligent Manufacturing 17(4): 441–451
Shieh H. M., May M. D. (2001) Solving the capacitated clustering problem with genetic algorithm. Journal of the Chinese Institute of Industrial Engineers 18: 1–12
Tavakkoli-Moghaddam R., Safari J., Sassani F. (2008) Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm. Reliability Engineering & System Safety 93: 550–556
Tsai Y. T., Wang K. S., Teng H. Y. (2001) Optimizing preventive maintenance for mechanical components using genetic algorithms. Reliability Engineering & System Safety 74: 89–97
Tsai Y. T., Wang K. S., Tsai L. C. (2004) A study of availability-centered preventive maintenance for multi-component systems. Reliability Engineering & System Safety 84: 261–270
Zimin Y., Dragan D., Jun N. (2008) Maintenance scheduling in manufacturing systems based on predicted machine degradation. Journal of Intelligent Manufacturing 19(1): 87–98
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lin, TW., Wang, CH. A hybrid genetic algorithm to minimize the periodic preventive maintenance cost in a series-parallel system. J Intell Manuf 23, 1225–1236 (2012). https://doi.org/10.1007/s10845-010-0406-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-010-0406-3