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Exact formulation of stochastic EMQ model for an unreliable production system

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  • B C Giri

    (Hiroshima University)

  • T Dohi

    (Hiroshima University)

Abstract

The purpose of this paper is to present an exact formulation of stochastic EMQ model for an unreliable production system under a general framework in which the time to machine failure, corrective (emergency) and preventive (regular) repair times are assumed to be random variables. For exact financial implications of the lot-sizing decisions, the EMQ model is formulated based on the net present value (NPV) approach. Then, by taking limitation on the discount rate, the traditional long-run average cost model is obtained. The criteria for the existence and uniqueness of the optimal production time in both the models are derived under general failure and specific repair time distributions. Numerical examples are devoted to find the optimal production policies of the developed models and examine the sensitivity of the parameters involved. Computational results show that the optimal decision based on the NPV approach is superior to that based on the long-run average cost approach, though the performance level strongly depends on the pertinent failure and repair time distributions.

Suggested Citation

  • B C Giri & T Dohi, 2005. "Exact formulation of stochastic EMQ model for an unreliable production system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 563-575, May.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:5:d:10.1057_palgrave.jors.2601840
    DOI: 10.1057/palgrave.jors.2601840
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    References listed on IDEAS

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    Cited by:

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    3. Shaktipada Bhuniya & Biswajit Sarkar & Sarla Pareek, 2019. "Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand," Mathematics, MDPI, vol. 7(5), pages 1-20, May.
    4. Mitali Sarkar & Biswajit Sarkar, 2019. "Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management," Energies, MDPI, vol. 12(11), pages 1-16, May.
    5. Priyanka & Sarla Pareek, 2023. "A sustainable inventory model for stochastic demand using innovative multi-item production system with reduced failure rate," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(3), pages 844-864, June.
    6. Harun Öztürk, 2019. "Modeling an inventory problem with random supply, inspection and machine breakdown," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 497-527, June.
    7. 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.
    8. 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.
    9. Mitali Sarkar & Biswajit Sarkar & Muhammad Waqas Iqbal, 2018. "Effect of Energy and Failure Rate in a Multi-Item Smart Production System," Energies, MDPI, vol. 11(11), pages 1-21, October.
    10. Maddah, Bacel & Yassine, Ali A. & Salameh, Moueen K. & Chatila, Lama, 2014. "Reserve stock models: Deterioration and preventive replenishment," European Journal of Operational Research, Elsevier, vol. 232(1), pages 64-71.
    11. Chakraborty, Tulika & Giri, B.C. & Chaudhuri, K.S., 2008. "Production lot sizing with process deterioration and machine breakdown," European Journal of Operational Research, Elsevier, vol. 185(2), pages 606-618, March.

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