Cellular bucket brigades on U-lines with discrete work stations

It is challenging to maximize and maintain productivity of a U-line with discrete stations under the impact of variability. This is because maximizing productivity requires assigning workers to suitable tasks and maintaining productivity requires sufficient flexibility in task assignment to absorb t...

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Main Authors: LIM, Yun Fong, WU, Yue
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/3512
https://ink.library.smu.edu.sg/context/lkcsb_research/article/4511/viewcontent/yflim_POM2013_CellularBucketBridages_afv.pdf
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spelling sg-smu-ink.lkcsb_research-45112020-01-14T07:44:40Z Cellular bucket brigades on U-lines with discrete work stations LIM, Yun Fong WU, Yue It is challenging to maximize and maintain productivity of a U-line with discrete stations under the impact of variability. This is because maximizing productivity requires assigning workers to suitable tasks and maintaining productivity requires sufficient flexibility in task assignment to absorb the impact of variability. To achieve this goal, we propose an operating protocol to coordinate workers on the U-line. Under the protocol the system can be configured such that its productivity is maximized. Workers are allowed to dynamically share work so that the system can effectively absorb the impact of variability. Analysis based on a deterministic model shows that the system always converges to a fixed point or a period-2 orbit. We identify a sufficient condition for the system to converge to the fixed point. Increasing the number of stations improves productivity only under certain circumstances. The improvement is most significant when the number of stations in each stage increases from one to two, but further dividing the U-line into more stations has diminishing return. Simulations based on random work velocities suggest that our approach significantly outperforms an optimized, static work-allocation policy if variability in velocity is large. 2014-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/3512 info:doi/10.1111/poms.12091 https://ink.library.smu.edu.sg/context/lkcsb_research/article/4511/viewcontent/yflim_POM2013_CellularBucketBridages_afv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University bucket brigades U-lines cross-training work-sharing self-organization Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic bucket brigades
U-lines
cross-training
work-sharing
self-organization
Operations and Supply Chain Management
spellingShingle bucket brigades
U-lines
cross-training
work-sharing
self-organization
Operations and Supply Chain Management
LIM, Yun Fong
WU, Yue
Cellular bucket brigades on U-lines with discrete work stations
description It is challenging to maximize and maintain productivity of a U-line with discrete stations under the impact of variability. This is because maximizing productivity requires assigning workers to suitable tasks and maintaining productivity requires sufficient flexibility in task assignment to absorb the impact of variability. To achieve this goal, we propose an operating protocol to coordinate workers on the U-line. Under the protocol the system can be configured such that its productivity is maximized. Workers are allowed to dynamically share work so that the system can effectively absorb the impact of variability. Analysis based on a deterministic model shows that the system always converges to a fixed point or a period-2 orbit. We identify a sufficient condition for the system to converge to the fixed point. Increasing the number of stations improves productivity only under certain circumstances. The improvement is most significant when the number of stations in each stage increases from one to two, but further dividing the U-line into more stations has diminishing return. Simulations based on random work velocities suggest that our approach significantly outperforms an optimized, static work-allocation policy if variability in velocity is large.
format text
author LIM, Yun Fong
WU, Yue
author_facet LIM, Yun Fong
WU, Yue
author_sort LIM, Yun Fong
title Cellular bucket brigades on U-lines with discrete work stations
title_short Cellular bucket brigades on U-lines with discrete work stations
title_full Cellular bucket brigades on U-lines with discrete work stations
title_fullStr Cellular bucket brigades on U-lines with discrete work stations
title_full_unstemmed Cellular bucket brigades on U-lines with discrete work stations
title_sort cellular bucket brigades on u-lines with discrete work stations
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/lkcsb_research/3512
https://ink.library.smu.edu.sg/context/lkcsb_research/article/4511/viewcontent/yflim_POM2013_CellularBucketBridages_afv.pdf
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