A human-cyber-physical system enabled sequential disassembly planning approach for a human-robot collaboration cell in Industry 5.0
Industry 5.0 characterized by human-centricity and sustainability has sparked a new wave of the industrial revolution. Human-cyber-physical system is the cornerstone of human-centric manufacturing while remanufacturing has gained considerable attention in fostering sustainability. Disassembly planni...
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| Main Authors: | , , , |
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| 其他作者: | |
| 格式: | Article |
| 語言: | English |
| 出版: |
2024
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/173151 |
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| 總結: | Industry 5.0 characterized by human-centricity and sustainability has sparked a new wave of the industrial revolution. Human-cyber-physical system is the cornerstone of human-centric manufacturing while remanufacturing has gained considerable attention in fostering sustainability. Disassembly planning is a vital but challenging task in remanufacturing. In order to accommodate the frequent changes resulting from mass personalization, a human-robot collaboration cell is valued for its ability to achieve flexible disassembly. However, recent studies treated disassembly sequence and task allocation as independent aspects. And tasks are allocated by predefined metrics and thresholds without considering the ergonomics of operators. This paper proposes a human-cyber-physical framework for the human-robot collaboration cell by illustrating human-in-the-loop and human-on-the-loop paradigms. A multi-objective sequential disassembly planning model is presented by simultaneously considering disassembly sequence and task allocation. The task complexity and operator ergonomics are evaluated based on cloud models to handle the fuzziness and randomness in human cognition. Moreover, an improved multi-objective hybrid grey wolf optimization algorithm is proposed to obtain Pareto optimal disassembly plans. A case study on the disassembly planning of a control box is presented to illustrate the feasibility and practicability of the proposed approach. The results underscore the superiority of the proposed approach in handling rigorous constraints inherent in the sequential disassembly planning model, which acquires more convergent, diverse, and uniform disassembly plans along the Pareto front. |
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