An efficient assembly line balancing in automobile manufacturing

The process time in Assembly Line balancing (ALB) is one for the most part important stage in production line at automobile manufacturing. It is a fundamental problem in continuous production line, and it is one of the difficult optimization problems. ALB contains many stations concerned with the al...

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Main Authors: Razman, Mat Tahar, Adham, Ali A. J.
Format: Conference or Workshop Item
Language:English
Published: IEEE 2011
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/26116/1/An%20efficient%20assembly%20line%20balancing%20in%20automobile%20manufacturing.pdf
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author Razman, Mat Tahar
Adham, Ali A. J.
author_facet Razman, Mat Tahar
Adham, Ali A. J.
author_sort Razman, Mat Tahar
collection UMP
description The process time in Assembly Line balancing (ALB) is one for the most part important stage in production line at automobile manufacturing. It is a fundamental problem in continuous production line, and it is one of the difficult optimization problems. ALB contains many stations concerned with the allocation of tasks to work, where each station includes a number of operations that assist to achieve the task work. The main ALB problem is the queuing among stations during task achievement that is an obstacle to the efficient assembly line. This paper, will be process minimize the queuing problem by applying Multi-Objectives Model and Genetic Algorithm. The outcome of the mixed models helps to reduce the queuing through harmonizing the tasks in each workstation. Moreover, to get the optimal solution as well balancing the redistribution tasks to the stations.
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spelling UMPir261162019-10-16T07:45:41Z http://umpir.ump.edu.my/id/eprint/26116/ An efficient assembly line balancing in automobile manufacturing Razman, Mat Tahar Adham, Ali A. J. HD28 Management. Industrial Management T Technology (General) The process time in Assembly Line balancing (ALB) is one for the most part important stage in production line at automobile manufacturing. It is a fundamental problem in continuous production line, and it is one of the difficult optimization problems. ALB contains many stations concerned with the allocation of tasks to work, where each station includes a number of operations that assist to achieve the task work. The main ALB problem is the queuing among stations during task achievement that is an obstacle to the efficient assembly line. This paper, will be process minimize the queuing problem by applying Multi-Objectives Model and Genetic Algorithm. The outcome of the mixed models helps to reduce the queuing through harmonizing the tasks in each workstation. Moreover, to get the optimal solution as well balancing the redistribution tasks to the stations. IEEE 2011 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26116/1/An%20efficient%20assembly%20line%20balancing%20in%20automobile%20manufacturing.pdf Razman, Mat Tahar and Adham, Ali A. J. (2011) An efficient assembly line balancing in automobile manufacturing. In: International Summer Conference of Asia Pacific Business Innovation and Technology Management (APBITM 2011) , 10-12 July 2011 , Dalian, China. pp. 37-39.. https://doi.org/10.1109/APBITM.2011.5996287
spellingShingle HD28 Management. Industrial Management
T Technology (General)
Razman, Mat Tahar
Adham, Ali A. J.
An efficient assembly line balancing in automobile manufacturing
title An efficient assembly line balancing in automobile manufacturing
title_full An efficient assembly line balancing in automobile manufacturing
title_fullStr An efficient assembly line balancing in automobile manufacturing
title_full_unstemmed An efficient assembly line balancing in automobile manufacturing
title_short An efficient assembly line balancing in automobile manufacturing
title_sort efficient assembly line balancing in automobile manufacturing
topic HD28 Management. Industrial Management
T Technology (General)
url http://umpir.ump.edu.my/id/eprint/26116/1/An%20efficient%20assembly%20line%20balancing%20in%20automobile%20manufacturing.pdf
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