Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study

Assembly line balancing type-e problem with resource constraint (ALBE-RC) is an attempt to assign the tasks to a minimal number of workstation with minimum cycle time by considering the resource constraint. Due to rapid growth in manufacturing and limited number of resources in industry, all the tas...

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Main Authors: Masitah, Jusop, M. F. F., Ab Rashid
Format: Article
Language:English
English
English
Published: Research India Publications 2016
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/1/Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource%20Constraint%20using%20NSGA-II-%20A%20Case%20Study.pdf
http://umpir.ump.edu.my/id/eprint/8243/7/c-f158.pdf
http://umpir.ump.edu.my/id/eprint/8243/13/fist-2017-mashitah-%20Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource.pdf
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spelling ump-82432017-05-02T03:23:54Z http://umpir.ump.edu.my/id/eprint/8243/ Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study Masitah, Jusop M. F. F., Ab Rashid TJ Mechanical engineering and machinery Assembly line balancing type-e problem with resource constraint (ALBE-RC) is an attempt to assign the tasks to a minimal number of workstation with minimum cycle time by considering the resource constraint. Due to rapid growth in manufacturing and limited number of resources in industry, all the tasks that used the same resources will be performed in the same workstation such that the precedence relations are not violated. In this work, an implementation of an elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to optimise ALBE-RC case study. An industrial case study was conducted in an electronic company and a product known as HM72A-10 series model has been selected for the case study. The results from the optimization shows that the number of workstations are extensively decreased as well as the number of resources used. The improvement of line efficiency, busy and idle time also indicates that the optimization results are better that the existing one. The validation from industrial expert provides evidence that the proposed method is applicable and can be implemented for line balancing. Research India Publications 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/8243/1/Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource%20Constraint%20using%20NSGA-II-%20A%20Case%20Study.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/8243/7/c-f158.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/8243/13/fist-2017-mashitah-%20Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource.pdf Masitah, Jusop and M. F. F., Ab Rashid (2016) Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study. International Journal of Applied Engineering Research (IJAER), 12 (7). pp. 1421-1426. ISSN 0973-4562 (print); 1087-1090 (online) (Unpublished) https://www.ripublication.com/ijaer17/ijaerv12n7_50.pdf DOI: 10.1007/978-3-662-45514-2_14
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Masitah, Jusop
M. F. F., Ab Rashid
Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
description Assembly line balancing type-e problem with resource constraint (ALBE-RC) is an attempt to assign the tasks to a minimal number of workstation with minimum cycle time by considering the resource constraint. Due to rapid growth in manufacturing and limited number of resources in industry, all the tasks that used the same resources will be performed in the same workstation such that the precedence relations are not violated. In this work, an implementation of an elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to optimise ALBE-RC case study. An industrial case study was conducted in an electronic company and a product known as HM72A-10 series model has been selected for the case study. The results from the optimization shows that the number of workstations are extensively decreased as well as the number of resources used. The improvement of line efficiency, busy and idle time also indicates that the optimization results are better that the existing one. The validation from industrial expert provides evidence that the proposed method is applicable and can be implemented for line balancing.
format Article
author Masitah, Jusop
M. F. F., Ab Rashid
author_facet Masitah, Jusop
M. F. F., Ab Rashid
author_sort Masitah, Jusop
title Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
title_short Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
title_full Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
title_fullStr Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
title_full_unstemmed Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study
title_sort optimization of assembly line balancing with resource constraint using nsga-ii: a case study
publisher Research India Publications
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/
http://umpir.ump.edu.my/id/eprint/8243/1/Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource%20Constraint%20using%20NSGA-II-%20A%20Case%20Study.pdf
http://umpir.ump.edu.my/id/eprint/8243/7/c-f158.pdf
http://umpir.ump.edu.my/id/eprint/8243/13/fist-2017-mashitah-%20Optimization%20of%20Assembly%20Line%20Balancing%20with%20Resource.pdf
first_indexed 2023-09-18T22:05:36Z
last_indexed 2023-09-18T22:05:36Z
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