Managing stochastic bucket brigades on discrete work stations

Bucket brigades are notably used to coordinate workers in production systems. We study a J-station, I-worker bucket brigade system. The time duration for each worker to serve a job at a station is exponentially distributed with a rate that depends on the station's expected work content and the...

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Main Authors: WANG, Peng, PAN, Kai, YAN, Zhenzhen, LIM, Yun Fong
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Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6911
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7910/viewcontent/yflim_POM2021b.pdf
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spelling sg-smu-ink.lkcsb_research-79102022-05-20T02:38:59Z Managing stochastic bucket brigades on discrete work stations WANG, Peng PAN, Kai YAN, Zhenzhen LIM, Yun Fong Bucket brigades are notably used to coordinate workers in production systems. We study a J-station, I-worker bucket brigade system. The time duration for each worker to serve a job at a station is exponentially distributed with a rate that depends on the station's expected work content and the worker's work speed. Our goal is to maximize the system's productivity or to minimize its inter-completion time variability. We analytically derive the throughput and the coefficient of variation (CV) of the inter-completion time. We study the system under two cases. (i) If the work speeds depend only on the workers, the throughput gap between the stochastic and the deterministic systems can be up to 47% when the number of stations is small. Either maximizing the throughput or minimizing the CV of the inter-completion time, the slowest-to-fastest worker sequence always outperforms the reverse sequence for the stochastic bucket brigade. To maximize the throughput, more work content should be assigned to the stations near the faster workers. In contrast, tominimize the CV of the inter-completion time, more work content should be allocated to the stations near the slower workers. (ii) If the work speeds depend on the workers and the stations such that the workers may not dominate each other at every station, the asymptotic throughput can be expressed as a function of the average work speeds and the asymptotic expected blocked times of the workers, and can be interpreted as the sum of the effective production rates of all the workers. 2022-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6911 info:doi/10.1111/poms.13539 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7910/viewcontent/yflim_POM2021b.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 brigade Stochastic service time Productivity Variability Operations and Supply Chain Management Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Bucket brigade
Stochastic service time
Productivity
Variability
Operations and Supply Chain Management
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Bucket brigade
Stochastic service time
Productivity
Variability
Operations and Supply Chain Management
Operations Research, Systems Engineering and Industrial Engineering
WANG, Peng
PAN, Kai
YAN, Zhenzhen
LIM, Yun Fong
Managing stochastic bucket brigades on discrete work stations
description Bucket brigades are notably used to coordinate workers in production systems. We study a J-station, I-worker bucket brigade system. The time duration for each worker to serve a job at a station is exponentially distributed with a rate that depends on the station's expected work content and the worker's work speed. Our goal is to maximize the system's productivity or to minimize its inter-completion time variability. We analytically derive the throughput and the coefficient of variation (CV) of the inter-completion time. We study the system under two cases. (i) If the work speeds depend only on the workers, the throughput gap between the stochastic and the deterministic systems can be up to 47% when the number of stations is small. Either maximizing the throughput or minimizing the CV of the inter-completion time, the slowest-to-fastest worker sequence always outperforms the reverse sequence for the stochastic bucket brigade. To maximize the throughput, more work content should be assigned to the stations near the faster workers. In contrast, tominimize the CV of the inter-completion time, more work content should be allocated to the stations near the slower workers. (ii) If the work speeds depend on the workers and the stations such that the workers may not dominate each other at every station, the asymptotic throughput can be expressed as a function of the average work speeds and the asymptotic expected blocked times of the workers, and can be interpreted as the sum of the effective production rates of all the workers.
format text
author WANG, Peng
PAN, Kai
YAN, Zhenzhen
LIM, Yun Fong
author_facet WANG, Peng
PAN, Kai
YAN, Zhenzhen
LIM, Yun Fong
author_sort WANG, Peng
title Managing stochastic bucket brigades on discrete work stations
title_short Managing stochastic bucket brigades on discrete work stations
title_full Managing stochastic bucket brigades on discrete work stations
title_fullStr Managing stochastic bucket brigades on discrete work stations
title_full_unstemmed Managing stochastic bucket brigades on discrete work stations
title_sort managing stochastic bucket brigades on discrete work stations
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/lkcsb_research/6911
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7910/viewcontent/yflim_POM2021b.pdf
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