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dc.contributor.authorKoh, S.C.L.
dc.contributor.authorSaad, S.M.
dc.contributor.authorJones, M.H.
dc.date.accessioned2010-01-19T11:34:00Z
dc.date.available2010-01-19T11:34:00Z
dc.date.issued2002
dc.identifier.citationKoh , S C L , Saad , S M & Jones , M H 2002 , ' Uncertainty under MRP-planned manufacture: review and categorization ' , International Journal of Production Research , vol. 40 , no. 10 , pp. 2399-2421 . https://doi.org/10.1080/00207540210136487
dc.identifier.issn0020-7543
dc.identifier.otherPURE: 80766
dc.identifier.otherPURE UUID: 94949af0-d8da-4fd8-afa2-d97c13cd2e29
dc.identifier.otherdspace: 2299/4163
dc.identifier.otherScopus: 0037054916
dc.identifier.urihttp://hdl.handle.net/2299/4163
dc.descriptionOriginal article can be found at: http://taylorandfrancis.metapress.com/link.asp?id=100666 Copyright Informa / Taylor & Francis Group. DOI: 10.1080/00207540210136487 [Full text of this article is not available in the UHRA]
dc.description.abstractExtensive research can be found in coping with uncertainty under Material Requirements Planning (MRP)-planned manufacture, but the under-performance of many manufacturing enterprises is still reported. To examine the reasons, a review of the literature on uncertainty under MRP-planned manufacture has been carried out. This paper presents a comprehensive review and categorisation of such research. It aims to provide a structure within which directions can be given for future research and the results of past research work are summarized to give an indication to practitioners of how to cope with uncertainty. An uncertainty categorization structure has been developed using systems theory to categorize uncertainty into input and process , and simultaneously to highlight the uncertainty that occurs in the supply and demand chain of the manufacturing process. Buffering and dampening (BAD) approaches are proposed and the experimental methods used are incorporated in the structure. A range of research gaps is identified: the lack of a detailed structure to enable the significant uncertainty to be diagnosed optimally, as most of the past research studied uncertainty discretely and only some in specific combinations; the sub-optimal approach in coping with uncertainty; and little research has examined the interactions between uncertainties. Several directions for future research are proposed: the development of a cause-and-effect structure for diagnosing uncertainty, a holistic approach to deduce to the underlying causes of uncertainty, generalization of the cause-and-effect structure, examination of the BAD approaches applied in industry and consideration of interactions between uncertainties by first diagnosing the significant uncertainty. It is found that safety stock, the use of appropriate lot-sizing rules and rescheduling are the most robust approaches to cope with uncertainty, while safety capacity is not used at all for buffering process uncertainty. Hedging/over-planning is useful for dampening process uncertainty. It can be concluded that input uncertainty has been maturely researched with external demand uncertainty dominating others, but with a range of suggested BAD approaches available. Scheduling heuristics, simulation modelling and mathematical modelling are the most applicable experimental methods in this research area. This review and categorization have identified that a structured and systematic approach is required to cope with uncertainty holistically within MRP-planned manufacture.en
dc.language.isoeng
dc.relation.ispartofInternational Journal of Production Research
dc.titleUncertainty under MRP-planned manufacture: review and categorizationen
dc.contributor.institutionHertfordshire Business School
dc.description.statusPeer reviewed
rioxxterms.versionofrecordhttps://doi.org/10.1080/00207540210136487
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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