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

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  • Berthaut, F.
  • Gharbi, A.
  • Dhouib, K.

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.

Suggested Citation

  • Berthaut, F. & Gharbi, A. & Dhouib, K., 2011. "Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell," Omega, Elsevier, vol. 39(6), pages 642-654, December.
    • Handle: RePEc:eee:jomega:v:39:y:2011:i:6:p:642-654
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    References listed on IDEAS

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    Citations

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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. Om Prakash & A.R. Roy & A. Goswami, 2014. "Stochastic manufacturing system with process deterioration and machine breakdown," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 2539-2551, December.
    3. 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.
    4. Ke, Hua & Yao, Kai, 2016. "Block replacement policy with uncertain lifetimes," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 119-124.
    5. 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.
    6. 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.
    7. 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.
    8. S. Priyan & P. Manivannan, 2017. "Optimal inventory modeling of supply chain system involving quality inspection errors and fuzzy defective rate," OPSEARCH, Springer;Operational Research Society of India, vol. 54(1), pages 21-43, March.
    9. 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.

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