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MRP-controlled batch-manufacturing environment under uncertainty

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  • S C L Koh

    (Management School, University of Sheffield)

Abstract

The overall aim of this research is to model the effects of uncertainty on delivery performance in an MRP-controlled batch-manufacturing environment with multi-product and multi-level dependent demand. To this end, MRP planning and batch-manufacturing system control architectures were modelled using simulation to implement the MRP release logic. Simulation and experimental design were carried out based on a real case enterprise. ANOVA showed that four uncertainty factors—namely late delivery from suppliers, machine breakdowns, process batch size increments and customer design changes—have significant effects on delivery performance. This ANOVA further showed that uncertainties create knock-on and compound effects; the latter are difficult to predict in practice. Significant two-way and three-way interactions among some uncertainty factors were also found, making it more difficult to characterise the precise factor effects. It was found that the more uncertain the environment is, the later the deliveries are. It can be concluded that MRP-controlled batch-manufacturing enterprises should diagnose uncertainties that are significantly affecting delivery performance, and tackle these uncertainties most urgently to prevent diffusion of knock-on and compound effects and improve delivery performance. This conclusion was validated through the case enterprise, for which significant delivery improvement has been achieved.

Suggested Citation

  • S C L Koh, 2004. "MRP-controlled batch-manufacturing environment under uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 219-232, March.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:3:d:10.1057_palgrave.jors.2601710
    DOI: 10.1057/palgrave.jors.2601710
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    References listed on IDEAS

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    1. Matsuura, Haruki & Tsubone, Hitoshi & Kataoka, Kiyoshi, 1995. "Comparison between simple infinite loading and loading considering a workload status under uncertainty in job operation times," International Journal of Production Economics, Elsevier, vol. 40(1), pages 45-55, June.
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    Cited by:

    1. Koh, S.C.L. & Gunasekaran, A. & Tseng, C.S., 2012. "Cross-tier ripple and indirect effects of directives WEEE and RoHS on greening a supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 305-317.
    2. Ketikidis, P.H. & Koh, S.C.L. & Dimitriadis, N. & Gunasekaran, A. & Kehajova, M., 2008. "The use of information systems for logistics and supply chain management in South East Europe: Current status and future direction," Omega, Elsevier, vol. 36(4), pages 592-599, August.
    3. Sivadasan, Suja & Smart, Janet & Huaccho Huatuco, Luisa & Calinescu, Anisoara, 2013. "Reducing schedule instability by identifying and omitting complexity-adding information flows at the supplier–customer interface," International Journal of Production Economics, Elsevier, vol. 145(1), pages 253-262.
    4. D Worthington, 2006. "Beware multiple hypothesis testing—the curse of type I errors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 612-612, May.
    5. Shpend IMERI, 2012. "Logistics Information Systems In Macedonian Firms: Current Situation And Future Prospects," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 2(3), pages 43-52, September.
    6. Bayraktar, Erkan & Demirbag, Mehmet & Koh, S.C. Lenny & Tatoglu, Ekrem & Zaim, Halil, 2009. "A causal analysis of the impact of information systems and supply chain management practices on operational performance: Evidence from manufacturing SMEs in Turkey," International Journal of Production Economics, Elsevier, vol. 122(1), pages 133-149, November.
    7. Jahangirian, Mohsen & Eldabi, Tillal & Naseer, Aisha & Stergioulas, Lampros K. & Young, Terry, 2010. "Simulation in manufacturing and business: A review," European Journal of Operational Research, Elsevier, vol. 203(1), pages 1-13, May.

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