Robotic Disassembly Sequence Planning With Backup Actions

A key step in remanufacturing is disassembly of the ``core'' or the returned product to be remanufactured. Disassembly sequence planning is challenging due to uncertainties in the conditions of the cores. Rust, corrosion, deformation, and missing parts may require disassembly plans to be c...

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Bibliographic Details
Published in:IEEE transactions on automation science and engineering 2022-07, Vol.19 (3), p.1-13
Main Authors: Laili, Yuanjun, Li, Xiang, Wang, Yongjing, Ren, Lei, Wang, Xiaokang
Format: Article
Language:English
Subjects:
Automation
Backup actions
Disassembly sequences
Dismantling
Evolutionary algorithms
Interference
multiobjective evolutionary algorithm
Multiple objective analysis
Optimization models
Planning
Recovery
Remanufacturing
robotic disassembly
Robotics
Robustness
sequence planning
Service robots
Uncertainty
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Summary:A key step in remanufacturing is disassembly of the ``core'' or the returned product to be remanufactured. Disassembly sequence planning is challenging due to uncertainties in the conditions of the cores. Rust, corrosion, deformation, and missing parts may require disassembly plans to be changed and adapted frequently. Conventional industrial automation that usually serves in repetitive and structured activities may fail when it is applied to disassembly. This research investigates the flexible sequencing of robotic disassembly in the presence of failed automation operations and develops online recovery by incorporating backup actions. It starts with modeling the time and success rate of a backup action. The expected disassembly time and completion rate of a disassembly plan are deduced according to the failure probability of both the operations and their backup actions. A biobjective optimization model for robotic disassembly sequence planning is established using a dual-selection multiobjective evolutionary algorithm. Two solution selection criteria are combined to produce potential offspring candidates in each evolutionary generation. Experimental results show that the backup actions allow efficient recovery from automation and can potentially improve the robustness of robotic disassembly.
ISSN:1545-5955
1558-3783
DOI:10.1109/TASE.2021.3072663