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The purpose of this study is to obtain more empirical data and develop rules to quantify the benefits of QRM. However, this literature tends to be anecdotal and descriptive, and the link that ties and quantifies actual cost benefits achieved with specific lead time reduction targets has not been formally established yet. ![]() Currently, there is detailed literature on QRM principles, how to implement QRM, and also its potential benefits. Quick Response Manufacturing (QRM) is a company-wide approach to lead time reduction that has been shown to be successful at many manufacturing enterprises. When compared with other OR techniques such as LP or Simulation, we see that there is also a scarcity of commercially supported software packages enabling the use of queueing models for manufacturing. There has actually been a lot of progress in the research on queueing models in manufacturing3, but queueing models are seldom used in industry for real manufacturing decision-making. Despite the fact that the analysis of queueing systems was formalized with Erlang’s work at the beginning of this century2, the use of queueing models in manufacturing and operations management (OM) remains limited. We agree wholeheartedly with those comments, and in the present paper we will address this issue from the point of view of manufacturing applications of queueing models. ![]() A recent paper in Interfaces laments that1 “the mathematical and often abstract nature of many articles on queueing suggests that queueing theory is just that: only theory and difficult to apply in practice.” It goes on to document the “limited use of queueing theory” in practice.
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