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Modeling sequence scrambling and related phenomena in mixed-model production lines

Rudolf, Gabor; Noyan, Nilay; Giard, Vincent (2014), Modeling sequence scrambling and related phenomena in mixed-model production lines, European Journal of Operational Research, 237, 1, p. 177-195. 10.1016/j.ejor.2014.02.041

Type
Article accepté pour publication ou publié
Date
2014
Journal name
European Journal of Operational Research
Volume
237
Number
1
Publisher
Elsevier
Pages
177-195
Publication identifier
10.1016/j.ejor.2014.02.041
Metadata
Show full item record
Author(s)
Rudolf, Gabor

Noyan, Nilay

Giard, Vincent
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
In this paper we examine the various effects that workstations and rework loops with identical parallel processors and stochastic processing times have on the performance of a mixed-model production line. Of particular interest are issues related to sequence scrambling. In many production systems (especially those operating on just-in-time or in-line vehicle sequencing principles), the sequence of orders is selected carefully to optimize line efficiency while taking into account various line balancing and product spacing constraints. However, this sequence is often altered due to stochastic factors during production. This leads to significant economic consequences, due to either the degraded performance of the production line, or the added cost of restoring the sequence (via the use of systems such as mix banks or automated storage and retrieval systems). We develop analytical formulas to quantify both the extent of sequence scrambling caused by a station of the production line, and the effects of this scrambling on downstream performance. We also develop a detailed Markov chain model to analyze related issues regarding line stoppages and throughput. We demonstrate the usefulness of our methods on a range of illustrative numerical examples, and discuss the implications from a managerial point of view.
Subjects / Keywords
Applied probability; Markov processes; Mixed-model production lines; Sequence scrambling; Stochastic processing times

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