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Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell

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Listed author(s):
  • Berthaut, F.
  • Gharbi, A.
  • Dhouib, K.
Registered author(s):

    Abstract

    This paper considers a joint preventive maintenance (PM) and production/inventory control policy of an unreliable single machine, mono-product manufacturing cell with stochastic non-negligible corrective and preventive delays. The production/inventory control policy, which is based on the hedging point policy (HPP), consists in building and maintaining a safety stock of finished products in order to respond to demand and to avoid shortages during maintenance actions. Without considering the impact of preventive and corrective actions on the overall performance of the production system, most authors working in the reliability and maintainability domains confirm that the age-based preventive maintenance policy (ARP) outperforms the classical block-replacement policy (BRP). In order to reduce wastage incurred by the classical BRP, we consider a modified block replacement policy (MBRP), which consists in canceling a preventive maintenance action if the time elapsed since the last maintenance action exceeds a specified time threshold. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is composed of corrective and preventive maintenance costs as well as inventory holding and backlog costs. A simulation model mimicking the dynamic and stochastic behavior of the manufacturing cell, based on more realistic considerations of the real behavior of industrial manufacturing cells, is proposed. Based on simulation results, the joint optimal MBRP/HPP parameters are obtained through a numerical approach that combines design of experiment, analysis of variance and response surface methodologies. The joint optimal MBRP/HPP policy is compared to classical joint ARP/HPP and BRP/HPP optimal policies, and the results show that the proposed MBRP/HPP outperforms the latter. Sensitivity analyses are also carried out in order to confirm the superiority of the proposed MBRP/HPP, and it is observed that for practitioners, the proposed joint MBRP/HPP offers not only cost savings, but is also easy to manage, as compared to the ARP/HPP policy.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0305-0483(11)00009-0
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    Article provided by Elsevier in its journal Omega.

    Volume (Year): 39 (2011)
    Issue (Month): 6 (December)
    Pages: 642-654

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    Handle: RePEc:eee:jomega:v:39:y:2011:i:6:p:642-654
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    Keywords: Production/inventory control Block/age replacement policies Modified block replacement policy Simulation modeling Response surface methodology;

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    1. Salameh, M. K. & Ghattas, R. E., 2001. "Optimal just-in-time buffer inventory for regular preventive maintenance," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 157-161, December.
    2. Hipkin, I. B. & De Cock, C., 2000. "TQM and BPR: lessons for maintenance management," Omega, Elsevier, vol. 28(3), pages 277-292, June.
    3. Pentico, David W. & Drake, Matthew J. & Toews, Carl, 2009. "The deterministic EPQ with partial backordering: A new approach," Omega, Elsevier, vol. 37(3), pages 624-636, June.
    4. Yang, Suh-Jenq & Yang, Dar-Li, 2010. "Minimizing the makespan on single-machine scheduling with aging effect and variable maintenance activities," Omega, Elsevier, vol. 38(6), pages 528-533, December.
    5. Chelbi, Anis & Ait-Kadi, Daoud, 2004. "Analysis of a production/inventory system with randomly failing production unit submitted to regular preventive maintenance," European Journal of Operational Research, Elsevier, vol. 156(3), pages 712-718, August.
    6. Savsar, Mehmet, 2006. "Effects of maintenance policies on the productivity of flexible manufacturing cells," Omega, Elsevier, vol. 34(3), pages 274-282, June.
    7. Chelbi, Anis & Ait-Kadi, Daoud, 2000. "Generalized inspection strategy for randomly failing systems subjected to random shocks," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 379-384, March.
    8. Gharbi, A. & Kenne, J.-P. & Beit, M., 2007. "Optimal safety stocks and preventive maintenance periods in unreliable manufacturing systems," International Journal of Production Economics, Elsevier, vol. 107(2), pages 422-434, June.
    9. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    10. Gharbi, A. & Kenne, J. P., 2000. "Production and preventive maintenance rates control for a manufacturing system: An experimental design approach," International Journal of Production Economics, Elsevier, vol. 65(3), pages 275-287, May.
    11. Chakraborty, Tulika & Giri, B.C. & Chaudhuri, K.S., 2009. "Production lot sizing with process deterioration and machine breakdown under inspection schedule," Omega, Elsevier, vol. 37(2), pages 257-271, April.
    12. Chang, Hung-Chi & Ho, Chia-Huei, 2010. "Exact closed-form solutions for "optimal inventory model for items with imperfect quality and shortage backordering"," Omega, Elsevier, vol. 38(3-4), pages 233-237, June.
    13. Crespo Marquez, Adolfo & Gupta, Jatinder N.D., 2006. "Contemporary maintenance management: process, framework and supporting pillars," Omega, Elsevier, vol. 34(3), pages 313-326, June.
    14. Chen, Wen-Jinn, 2009. "Minimizing number of tardy jobs on a single machine subject to periodic maintenance," Omega, Elsevier, vol. 37(3), pages 591-599, June.
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    Cited by:

    1. Jeang, Angus, 2012. "Simultaneous determination of production lot size and process parameters under process deterioration and process breakdown," Omega, Elsevier, vol. 40(6), pages 774-781.
    2. Hauck, Zsuzsanna & Vörös, József, 2015. "Lot sizing in case of defective items with investments to increase the speed of quality control," Omega, Elsevier, vol. 52(C), pages 180-189.
    3. Wee, Hui Ming & Widyadana, Gede Agus, 2013. "A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule," Omega, Elsevier, vol. 41(6), pages 941-954.
    4. Bouslah, B. & Gharbi, A. & Pellerin, R., 2016. "Integrated production, sampling quality control and maintenance of deteriorating production systems with AOQL constraint," Omega, Elsevier, vol. 61(C), pages 110-126.
    5. Assid, M. & Gharbi, A. & Dhouib, K., 2015. "Joint production and subcontracting planning of unreliable multi-facility multi-product production systems," Omega, Elsevier, vol. 50(C), pages 54-69.
    6. Dhouib, K. & Gharbi, A. & Ben Aziza, M.N., 2012. "Joint optimal production control/preventive maintenance policy for imperfect process manufacturing cell," International Journal of Production Economics, Elsevier, vol. 137(1), pages 126-136.
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