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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Lau, Lee Lyn
التنسيق: أطروحة
اللغة:eng
eng
منشور في: 2006
الموضوعات:
الوصول للمادة أونلاين: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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الوصف
الملخص: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.