Queue time analysis for a production line with small variability
Much effort has been put into computing queue times for tandem queue networks as they form a paramount structure of the queuing network. However, it is highly challenging and time consuming to determine the exact queue times. Researchers have proposed several approximation methods for estimating the...
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sg-ntu-dr.10356-707772023-03-04T18:23:36Z Queue time analysis for a production line with small variability Wong, Lisa Ley Yien Wu Kan School of Mechanical and Aerospace Engineering DRNTU::Engineering::Aeronautical engineering Much effort has been put into computing queue times for tandem queue networks as they form a paramount structure of the queuing network. However, it is highly challenging and time consuming to determine the exact queue times. Researchers have proposed several approximation methods for estimating the mean queue times for single server tandem queues. Of which, one involved the exploitation of its Intrin- sic Ratio. This article proposes an approximation approach for homogeneous server two-staged tandem queues by incorporating this approximation method. Using the simulation results obtained for different cases, while varying number of servers in each stage, service time, sample size etc, behavior of the queue networks were stud- ied by observing its intrinsic ratio and intrinsic gap. This study aims to establish a homogeneous trend between intrinsic ratio and traffic intensity, by observing how the intrinsic ratio varies of traffic intensity for each queue setting. Wu and McGinnis (2012) determined that intrinsic ratios are relatively constant as utilization increases for single server tandem queues with squared coefficient of variance less than one. Therefore, this paper also aims to determine if such properties also apply to tandem queues with homogeneous servers. Using the trends identified, backed with mathe- matical formulas, an accurate approximation of queue time can be determined. Bachelor of Engineering (Aerospace Engineering) 2017-05-11T05:29:22Z 2017-05-11T05:29:22Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70777 en Nanyang Technological University 91 p. application/pdf |
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DRNTU::Engineering::Aeronautical engineering Wong, Lisa Ley Yien Queue time analysis for a production line with small variability |
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Much effort has been put into computing queue times for tandem queue networks as they form a paramount structure of the queuing network. However, it is highly challenging and time consuming to determine the exact queue times. Researchers have proposed several approximation methods for estimating the mean queue times for single server tandem queues. Of which, one involved the exploitation of its Intrin- sic Ratio. This article proposes an approximation approach for homogeneous server two-staged tandem queues by incorporating this approximation method. Using the simulation results obtained for different cases, while varying number of servers in each stage, service time, sample size etc, behavior of the queue networks were stud- ied by observing its intrinsic ratio and intrinsic gap. This study aims to establish a homogeneous trend between intrinsic ratio and traffic intensity, by observing how the intrinsic ratio varies of traffic intensity for each queue setting. Wu and McGinnis (2012) determined that intrinsic ratios are relatively constant as utilization increases for single server tandem queues with squared coefficient of variance less than one. Therefore, this paper also aims to determine if such properties also apply to tandem queues with homogeneous servers. Using the trends identified, backed with mathe- matical formulas, an accurate approximation of queue time can be determined. |
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Wu Kan |
author_facet |
Wu Kan Wong, Lisa Ley Yien |
format |
Final Year Project |
author |
Wong, Lisa Ley Yien |
author_sort |
Wong, Lisa Ley Yien |
title |
Queue time analysis for a production line with small variability |
title_short |
Queue time analysis for a production line with small variability |
title_full |
Queue time analysis for a production line with small variability |
title_fullStr |
Queue time analysis for a production line with small variability |
title_full_unstemmed |
Queue time analysis for a production line with small variability |
title_sort |
queue time analysis for a production line with small variability |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/70777 |
_version_ |
1759857475328147456 |