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http://hdl.handle.net/11452/31670
Title: | A real-time methodology for minimizing mean flowtime in FMSs with machine breakdowns: threshold-based selective rerouting |
Authors: | Harmonosky, Catherine M. Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü. Özmutlu, Seda AAH-4480-2021 6603660605 |
Keywords: | Engineering Operations research and management science Flexible manufacturing systems Environment Algorithm Disruptions Algorithms Computer simulation Dynamic programming Heuristic methods Intelligent agents Machine components Regression analysis Flexible manufacturing system (FMS) Rerouting Thershold value Threshold-based selective rerouting (TSR) Real time systems |
Issue Date: | 1-Dec-2004 |
Publisher: | Taylor and Francis |
Citation: | Özmutlu, S. ve Harmonosky, C. M. (2004). “A real-time methodology for minimizing mean flowtime in FMSs with machine breakdowns: Threshold-based selective rerouting”. International Journal of Production Research, 42(23), 4975-4991. |
Abstract: | This paper presents the threshold-based selective rerouting (TSR) heuristic to minimize mean flowtime of parts in a flexible manufacturing system (FMS) with machine failures. Most of the available methodologies considering machine failures are either off-line methods or propose different versions of rerouting all the jobs to alternate machines. The objective of this methodology is to develop an efficient real-time rerouting strategy, which can be easily applicable in case of machine failures and is able to adapt to the dynamic features of an FMS. Parts in the queue of a failed machine are selectively rerouted to alternate machines when the benefit in terms of waiting time obtained from rerouting exceeds a specific pre-determined threshold value. The threshold concept and the performance of TSR in minimizing mean flowtime are tested with extensive simulation experiments. It has been shown that TSR provides significant improvements in system performance measures compared to other real-time rerouting methods and that the threshold value is dependent on system parameters. The relationship between the threshold value and system parameters has also been determined. |
URI: | https://doi.org/10.1080/00207540410001704005 https://www.tandfonline.com/doi/full/10.1080/00207540410001704005 http://hdl.handle.net/11452/31670 |
ISSN: | 0020-7543 |
Appears in Collections: | Scopus Web of Science |
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