A state-of-the-art literature survey on artificial intelligence techniques for disassembly sequence planning

被引:3
|
作者
Chand, Mirothali [1 ]
Ravi, Chandrasekar [1 ]
机构
[1] Natl Inst Technol Puducherry, Dept Comp Sci & Engn, Karaikal, India
关键词
E-waste; Disassembly sequence planning; Artificial intelligence; Optimization; LEARNING-BASED OPTIMIZATION; DISCRETE BEES ALGORITHM; ELECTRONIC EQUIPMENT; GENETIC ALGORITHM; MAINTENANCE; GENERATION; PRODUCTS; DESIGN; INFORMATION; SEARCH;
D O I
10.1016/j.cirpj.2022.11.017
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In recent years, the utilization of artificial intelligence-based approaches has rapidly grown in the manu-facturing sectors. Disassembly sequence planning is an important combinatorial optimization problem that is gaining importance because of its significant role in the re-manufacturing sector and its ability to build a circular economy. An efficient disassembly process can reduce a product's ecological and economic impacts in the re-manufacturing industry. In this work, the state-of-the-art disassembly sequence planning methods are analyzed and explained in the point of disassembly objectives, disassembly attributes, and optimization techniques. This presentation also provides comparative inference of the functionality and limitation of various techniques used in disassembly sequence planning. A clear perspective on different optimization techniques is given which will be helpful for researchers to carry out their research in DSP for planning optimal disassembly sequences while satisfying various disassembly objectives and conditions.(c) 2022 CIRP.
引用
收藏
页码:292 / 310
页数:19
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