Remanufacturing disassembly service line and balancing optimization method

被引：0
|
作者：
Xia X. [1 ]
Zhou M. [1 ]
Wang L. [1 ,2 ]
Cao J. [1 ]
机构：
[1] Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan
[2] Center for Service Science and Engineering, Wuhan University of Science and Technology, Wuhan
来源：
Wang, Lei (wanglei1987@wust.edu.cn) | 2018年 / CIMS卷 / 24期
基金：
中国国家自然科学基金;
关键词：
Disassembly line balancing; Disassembly service; Multi-objective optimization; Remanufacturing; Teaching-learning-based optimization;
D O I：
10.13196/j.cims.2018.10.011
中图分类号：
学科分类号：
摘要：
To improve the resource utilization and entire efficiency of remanufacturing disassembly, according to the concept of remanufacturing service, a model of remanufacture disassembly service was put forward. The layout and characteristics of three types of disassembly lines namely single product disassembly, multi product mixed disassembly and robot based flexible disassembly were analyzed in this model. Aiming at the line balancing problem of remanufacture disassembly service, the single product-dual objectives model for disassembly line balancing(DLBP) model was formulated with the optimization goals of maximizing load balancing rate of disassembly line and giving priority to disassembling high-value parts. To simplify the parameter setting and improve the computational efficiency, an Improved Teaching-Learning-Based Optimization (ITLBO) algorithm was developed. On the basis of the traditional TLBO and random key initialization, the algorithm was endowed with capability of "self-learning" to improve its partial searching ability. Through the comparison analysis for two group benchmark cases of ITLBO and genetic algorithm, the effectiveness and feasibility were verified. An application example of reducer disassembly was given to verify the practicability of the model and algorithm. © 2018, Editorial Department of CIMS. All right reserved.
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页码：2492 / 2501
页数：9
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