The development of job intermediation and the increasing use of the Internet allow companies to carry out ever quicker capacity changes. In many cases, capacity can be adapted rapidly to the actual workload, which is especially important in production-to-order systems, where inventory cannot be used as a buffer for demand variation. We introduce a set of Markov chain models to represent workload-dependent capacity control policies. We present two analytical approaches to evaluate the policies’ due-date performance based on stationary analysis. One provides an explicit expression of throughput time distribution, the other is a fixed-point iteration method that calculates the moments of the throughput time. We compare due-date performance, capacity, capacity switching, and lost sales costs to select optimal policies. We also give insight into which situations a workload-dependent policy is beneficial to introduce. Our results can be used by
manufacturing and service industries when establishing a static policy for dynamic capacity planning.
Original language | English |
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Place of Publication | Eindhoven |
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Publisher | Eurandom |
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Number of pages | 24 |
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Publication status | Published - 2009 |
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Name | Report Eurandom |
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Volume | 2009054 |
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ISSN (Print) | 1389-2355 |
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