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A production-inventory model with imperfect production process and partial backlogging under learning considerations in fuzzy random environments

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  • Gour Chandra Mahata

    (Sitananda College)

Abstract

In this paper, we investigates the learning effect of the unit production time on optimal lot size for the imperfect production process with partial backlogging of shortage quantity in fuzzy random environments. It is assumed that the setup cost, the average holding cost, the backorder cost, the raw material cost and the labour cost are characterized as fuzzy variables and the elapsed time until the machine shifts from “in-control” state to “out-of-control” state is characterized as a fuzzy random variable. As a function of these parameters, the average total cost is also a random fuzzy variable. Based on the credibility measure of fuzzy event, the fuzzy random total cost function is transformed into an equivalent crisp function. We propose an algorithm to determine the optimal solution. Furthermore, the model is illustrated with the help of numerical example. Finally, sensitivity analysis of the optimal solution with respect to major parameters is carried out.

Suggested Citation

  • Gour Chandra Mahata, 2017. "A production-inventory model with imperfect production process and partial backlogging under learning considerations in fuzzy random environments," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 883-897, April.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:4:d:10.1007_s10845-014-1024-2
    DOI: 10.1007/s10845-014-1024-2
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    References listed on IDEAS

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    1. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2008. "Learning curves for imperfect production processes with reworks and process restoration interruptions," European Journal of Operational Research, Elsevier, vol. 189(1), pages 93-104, August.
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    9. 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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    Cited by:

    1. Dharamender Singh & Anurag Jayswal & Majed G. Alharbi & Ali Akbar Shaikh, 2021. "An Investigation of a Supply Chain Model for Co-Ordination of Finished Products and Raw Materials in a Production System under Different Situations," Sustainability, MDPI, vol. 13(22), pages 1-25, November.
    2. Falguni Mahato & Chandan Mahato & Gour Chandra Mahata, 2023. "Sustainable optimal production policies for an imperfect production system with trade credit under different carbon emission regulations," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10073-10099, September.
    3. Kaifang Fu & Zhixiang Chen & Guolin Zhou, 2022. "The Effects of Cognitive and Skill Learning on the Joint Vendor–Buyer Model with Imperfect Quality and Fuzzy Random Demand," Mathematics, MDPI, vol. 10(14), pages 1-24, July.
    4. Bikash Koli Dey & Hyesung Seok, 2024. "Intelligent inventory management with autonomation and service strategy," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 307-330, January.

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