Queue time approximation for a production line with large variability
Queuing networks are surprisingly common in a wide range of real-life scenarios. They can be found in service systems like commercial, transportation, internal and even social service systems. It is important to understand these queuing systems and to ensure that the systems developed are e ectiv...
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sg-ntu-dr.10356-708302023-03-04T18:26:23Z Queue time approximation for a production line with large variability Chua, Kurtz Yuan Feng School of Mechanical and Aerospace Engineering Wu Kan DRNTU::Engineering::Aeronautical engineering Queuing networks are surprisingly common in a wide range of real-life scenarios. They can be found in service systems like commercial, transportation, internal and even social service systems. It is important to understand these queuing systems and to ensure that the systems developed are e ective and e cient by reducing queue times (waiting time). It is however di cult to obtain the exact queue times in tan- dem queues. Many approaches have been used to approximate the exact mean queue time in a tandem queue and this article will be focusing on one of the approximation approach by Wu and McGinnis (2012). In Wu and McGinnis (2012), they showed that by exploiting the Intrinsic Ratio, the queue time can be more accurately ap- proximated in single server tandem queues. This paper aims to determine if the use of the Intrinsic Ratio will also be applicable in approximating the queue times for a tandem queue with homogeneous servers. This paper will present ndings based on the simulation of a high variability production line. The almost linear properties of the intrinsic ratio provided in this paper, will provide insights to the approximation of queue times that will be applicable to real-life manufacturing processes. Bachelor of Engineering (Aerospace Engineering) 2017-05-11T08:10:04Z 2017-05-11T08:10:04Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70830 en Nanyang Technological University 67 p. application/pdf |
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DRNTU::Engineering::Aeronautical engineering Chua, Kurtz Yuan Feng Queue time approximation for a production line with large variability |
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Queuing networks are surprisingly common in a wide range of real-life scenarios.
They can be found in service systems like commercial, transportation, internal and
even social service systems. It is important to understand these queuing systems and
to ensure that the systems developed are e ective and e cient by reducing queue
times (waiting time). It is however di cult to obtain the exact queue times in tan-
dem queues. Many approaches have been used to approximate the exact mean queue
time in a tandem queue and this article will be focusing on one of the approximation
approach by Wu and McGinnis (2012). In Wu and McGinnis (2012), they showed
that by exploiting the Intrinsic Ratio, the queue time can be more accurately ap-
proximated in single server tandem queues. This paper aims to determine if the use
of the Intrinsic Ratio will also be applicable in approximating the queue times for a
tandem queue with homogeneous servers. This paper will present ndings based on
the simulation of a high variability production line. The almost linear properties of
the intrinsic ratio provided in this paper, will provide insights to the approximation
of queue times that will be applicable to real-life manufacturing processes. |
author2 |
School of Mechanical and Aerospace Engineering |
author_facet |
School of Mechanical and Aerospace Engineering Chua, Kurtz Yuan Feng |
format |
Final Year Project |
author |
Chua, Kurtz Yuan Feng |
author_sort |
Chua, Kurtz Yuan Feng |
title |
Queue time approximation for a production line with large variability |
title_short |
Queue time approximation for a production line with large variability |
title_full |
Queue time approximation for a production line with large variability |
title_fullStr |
Queue time approximation for a production line with large variability |
title_full_unstemmed |
Queue time approximation for a production line with large variability |
title_sort |
queue time approximation for a production line with large variability |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/70830 |
_version_ |
1759857637074141184 |