Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm

This paper introduces the use of an Artificial-Intelligence (AI) based technique, Genetic Algorithm (GA), to solve single model product disassembly sequence problems. The generation of disassembly sequence is modeled using Design for Assembly (DfA) working principles. In this paper, the performances...

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Main Author:	Lau, Lee Lyn
Format:	Thesis
Language:	eng eng
Published:	2006
Subjects:	TS Manufactures
Online Access:	https://etd.uum.edu.my/23/1/lau_lee_lyn.pdf https://etd.uum.edu.my/23/2/lau_lee_lyn.pdf
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id	my-uum-etd.23
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	TS Manufactures
spellingShingle	TS Manufactures Lau, Lee Lyn Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
description	This paper introduces the use of an Artificial-Intelligence (AI) based technique, Genetic Algorithm (GA), to solve single model product disassembly sequence problems. The generation of disassembly sequence is modeled using Design for Assembly (DfA) working principles. In this paper, the performances of Design for Disassembly (DfD) and GA in selecting optimum disassembly sequence were tested. The problem is involves minimizing the total disassembly time by proper feeder allocation and component sequencing. The objective is to find out the optimum disassembly sequence with minimum disassembly time. The study started by manual disassembly using DfD which involves manual handling and manual insertion guideline in estimating time to search for optimum sequence. Finally, GA technique is applied to search for the optimum sequence. The results were compared between DfD and GA to show the efficiency of the proposed GA approach.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Lau, Lee Lyn
author_facet	Lau, Lee Lyn
author_sort	Lau, Lee Lyn
title	Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
title_short	Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
title_full	Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
title_fullStr	Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
title_full_unstemmed	Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm
title_sort	product disassembly planning using design for disassembly and genetic algorithm
granting_institution	Universiti Utara Malaysia
granting_department	Sekolah Siswazah
publishDate	2006
url	https://etd.uum.edu.my/23/1/lau_lee_lyn.pdf https://etd.uum.edu.my/23/2/lau_lee_lyn.pdf
_version_	1747826828559515648
spelling	my-uum-etd.232013-07-24T12:05:20Z Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm 2006 Lau, Lee Lyn Sekolah Siswazah Graduate School TS Manufactures This paper introduces the use of an Artificial-Intelligence (AI) based technique, Genetic Algorithm (GA), to solve single model product disassembly sequence problems. The generation of disassembly sequence is modeled using Design for Assembly (DfA) working principles. In this paper, the performances of Design for Disassembly (DfD) and GA in selecting optimum disassembly sequence were tested. The problem is involves minimizing the total disassembly time by proper feeder allocation and component sequencing. The objective is to find out the optimum disassembly sequence with minimum disassembly time. The study started by manual disassembly using DfD which involves manual handling and manual insertion guideline in estimating time to search for optimum sequence. Finally, GA technique is applied to search for the optimum sequence. The results were compared between DfD and GA to show the efficiency of the proposed GA approach. 2006 Thesis https://etd.uum.edu.my/23/ https://etd.uum.edu.my/23/1/lau_lee_lyn.pdf application/pdf eng validuser https://etd.uum.edu.my/23/2/lau_lee_lyn.pdf application/pdf eng public masters masters Universiti Utara Malaysia Boothroyd, G. (1992). Assembly Automation And Product Design. New York: Marcel Dekker. Daabub, A.M., & Abdalla, H.S. (1999). A Computer-based Intelligent System for Design for Assembly. Computers & Industrial Engineering, 37: 111 - 115. Deo, S., & Javadpour, R., & Knapp, G.M. (2002). Multiple Setup PCB Assembly Planning Using Genetic Algorithm. Computers & Industrial Engineering, 42: 1 - 16. Chan, V., & Salustri, F.A. (2003). Design for Assembly. Retrieved October 10, 2003, from http://deed.ryerson.ca/-fil/t/dfmdfa.htm Chapman, C.D., & Saitou, K., & Jakiela, M.J. (1994). 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(1999). A Framework For The Flexible Grouping Of Products For Disassembly. Journal of Electronics Manufacturing, 9(1): 53-66. Viswanathan, S., & Allada, V. (2004). Product Configuration Optimization for Disassembly Planning: A Differential Approach. The International Journal of Management Science, 01 : 01 1. Zussman, E., & Zhou, M. (2000). Design and implementation of a adaptive process planner for disassembly processes. IEEE Transactions on Robotics and Automation, 16(2): 171-9.

Product Disassembly Planning Using Design For Disassembly and Genetic Algorithm

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