A self-evolving system for robotic disassembly sequence planning under uncertain interference conditions

Fei Ye; James Perrett; Lin Zhang; Yuanjun Laili; Yongjing Wang

doi:10.1016/j.rcim.2022.102392

A self-evolving system for robotic disassembly sequence planning under uncertain interference conditions

Fei Ye, James Perrett, Lin Zhang, Yuanjun Laili, Yongjing Wang

Mechanical Engineering

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Abstract

Robotic disassembly sequence planning (DSP) is a research area that looks at the sequence of actions in the disassembly intending to achieve autonomous disassembly with high efficiency and low cost in remanufacturing and recycling applications. A piece of key input information being factored in DSP is the interference condition of a product, i.e., a mathematical representation of the spatial location of components in an assembly, usually in the form of a matrix. An observed challenge in the area is that the interference condition can be uncertain due to variations in the end-of-life conditions, and there is a lack of tools available in DSP under uncertain interference. To address this challenge, this paper proposes a new DSP method that can cope with uncertain interference conditions enabled by the fuzzification of DSP (FDSP). This new approach in the core is a fuzzy and dynamic modeling method in combination with an iterative re-planning strategy, and FDSP offers the capability for DSP to adapt to failures and self-evolve online. Three products are given to demonstrate FDSP.

Original language	English
Article number	102392
Number of pages	14
Journal	Robotics and Computer-Integrated Manufacturing
Volume	78
Early online date	3 Jun 2022
DOIs	https://doi.org/10.1016/j.rcim.2022.102392
Publication status	Published - Dec 2022

Bibliographical note

Funding Information:
This work is supported by the National Key Research and Development Program of China (Grant No. 2018YFB1700603 ), the National Natural Science Foundation of China (NSFC) (Grant No. 62173017 ), the Royal Society ( IEC\NSFC\181018 ), and by the Engineering and Physical Sciences Research Council (EPSRC) under the funded projects AUTOREMAN ( EP/N018524/1 ) and ATARI ( EP/W00206X/1 ).

Publisher Copyright:
© 2022

Keywords

Dual-loop self-evolving
Fuzzification
Robotic disassembly
Sequence planning
Uncertain interference

ASJC Scopus subject areas

Control and Systems Engineering
Software
General Mathematics
Computer Science Applications
Industrial and Manufacturing Engineering

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Cite this

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abstract = "Robotic disassembly sequence planning (DSP) is a research area that looks at the sequence of actions in the disassembly intending to achieve autonomous disassembly with high efficiency and low cost in remanufacturing and recycling applications. A piece of key input information being factored in DSP is the interference condition of a product, i.e., a mathematical representation of the spatial location of components in an assembly, usually in the form of a matrix. An observed challenge in the area is that the interference condition can be uncertain due to variations in the end-of-life conditions, and there is a lack of tools available in DSP under uncertain interference. To address this challenge, this paper proposes a new DSP method that can cope with uncertain interference conditions enabled by the fuzzification of DSP (FDSP). This new approach in the core is a fuzzy and dynamic modeling method in combination with an iterative re-planning strategy, and FDSP offers the capability for DSP to adapt to failures and self-evolve online. Three products are given to demonstrate FDSP.",

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N2 - Robotic disassembly sequence planning (DSP) is a research area that looks at the sequence of actions in the disassembly intending to achieve autonomous disassembly with high efficiency and low cost in remanufacturing and recycling applications. A piece of key input information being factored in DSP is the interference condition of a product, i.e., a mathematical representation of the spatial location of components in an assembly, usually in the form of a matrix. An observed challenge in the area is that the interference condition can be uncertain due to variations in the end-of-life conditions, and there is a lack of tools available in DSP under uncertain interference. To address this challenge, this paper proposes a new DSP method that can cope with uncertain interference conditions enabled by the fuzzification of DSP (FDSP). This new approach in the core is a fuzzy and dynamic modeling method in combination with an iterative re-planning strategy, and FDSP offers the capability for DSP to adapt to failures and self-evolve online. Three products are given to demonstrate FDSP.

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A self-evolving system for robotic disassembly sequence planning under uncertain interference conditions

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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