Uncertainty under MRP-planned manufacture: Review and categorization

Abstract

Extensive 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. Bu ering and dampening (BAD) approaches are proposed and the experimental methods used are incorporated in the structure. A range of research gaps is identi®ed: the lack of a detailed structure to enable the signi®cant uncertainty to be diagnosed optimally, as most of the past research studied uncertainty discretely and only some in speci®c 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-e ect structure for diagnosing uncertainty, a holistic approach to deduce to the underlying causes of uncertainty, generalization of the cause-and-e ect structure, examination of the BAD approaches applied in industry and consideration of interactions between uncertainties by ®rst diagnosing the signi®cant 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 bu ering 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 identi®ed that a structured and systematic approach is required to cope with uncertainty holistically within MRP-planned manufacture.

Handling Unexpected Events in Production Activity Control Systems

“…However, the majority of research studies consider uncertainties independently [17], which is not the case in reality. This factor has been recognized by some recent empirical studies (see for example de Snoo et al [9]), showing the interdependencies, communication, and feedback process between planning and control levels during event handling process using an in-depth single case study.…”

“…There have also been some studies to characterize and categorize the uncertainty in manufacturing systems (see for example Koh et al [17]). Based on our discussions in the industrial cases, we think that it is also important to append the complexity aspect of the events into these categorizations.…”

Parameterization of MRP for Supply Planning Under Lead Time Uncertainties

“…Yücesan & De Groote (2000) did a survey on supply planning under uncertainties, but they focused on the impact of the production management under uncertainty on the lead times by observing the service level. Process uncertainties are considered in (Koh et al, 2002;Koh & Saad, 2003). The problem of MRP parameterization under lead time uncertainties has been often studied via simulation.…”

Safety stock or safety lead time: coping with unreliability in demand and supply

“…275-281). Koh et al distinguished four types of uncertainty in their review, and 21 out of 37 papers considered only one of these (Koh et al 2002, Figure 3&4 pp. 2403-2412.…”