Abstract
Disassembly of end-of-life products is a common step in remanufacturing and recycling. Disassembly sequence planning is the process that automatically finds the optimal sequence of components being removed. A key element of disassembly sequence planning is a suitable mathematical representation that describes the interference of any two components in a product. Previous studies on disassembly sequence planning have tended to focused on the interference that is fixed and known. However, the interference may be uncertain due to complex end-of-life conditions such as deformation, corrosion and rust. To deal with uncertain interference, this paper proposes an interference probability matrix as a new mathematical representation that uses probability to indicate uncertainty in the interference, and establishes a multi-threshold planning scheme to generate the optimal disassembly sequence plans. Three case studies are given to demonstrate the use of the proposed approach. It is also tested the performance of four multi-objective optimization algorithms that can be adopted in the proposed multi-threshold planning scheme.
Original language | English |
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Pages (from-to) | 214-225 |
Number of pages | 12 |
Journal | Journal of Manufacturing Systems |
Volume | 60 |
Early online date | 3 Jun 2021 |
DOIs | |
Publication status | Published - Jul 2021 |
Bibliographical note
Funding Information:This work is supported by the National Key Research and Development Program of China under Grant (Grant No. 2018YFB1701601 ), National Natural Science Foundation of China (NSFC) (Grant No. 61911530217 ), the Royal Society ( IEC/NSFC/181018 ) and in part by the Engineering and Physical Sciences Research Council (EPSRC Grant No. EP/N018524/1 ).
Publisher Copyright:
© 2021 The Society of Manufacturing Engineers
Keywords
- Automated disassembly
- Deformation probability
- Interference probability
- Multi-threshold scheme
- Sequence planning
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Hardware and Architecture
- Industrial and Manufacturing Engineering