Human-robot collaboration in disassembly for sustainable manufacturing

Sustainable manufacturing is a global front-burner issue oriented to the sustainable development of humanity and society. In this context, this paper takes the human-robot collaborative disassembly (HRCD) as the topic on its contribution to economic, environmental and social sustainability. In addit...

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Bibliographic Details
Published in:International journal of production research 2019-06, Vol.57 (12), p.4027-4044
Main Authors: Liu, Quan, Liu, Zhihao, Xu, Wenjun, Tang, Quan, Zhou, Zude, Pham, Duc Truong
Format: Article
Language:English
Subjects:
Artificial intelligence
Cognition
Collaboration
cyber-physical production system
Dismantling
human-robot collaboration
Machine learning
Perception
product disassembly
Robots
Sustainable development
sustainable manufacturing
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Summary:Sustainable manufacturing is a global front-burner issue oriented to the sustainable development of humanity and society. In this context, this paper takes the human-robot collaborative disassembly (HRCD) as the topic on its contribution to economic, environmental and social sustainability. In addition, a detailed enabling systematic implementation for HRCD is presented, combined with a set of advanced technologies such as cyber-physical production system (CPPS) and artificial intelligence (AI), and it involves five aspects which including perception, cognition, decision, execution and evolution aiming at the dynamics, uncertainties and complexities in disassembly. Deep reinforcement learning, incremental learning and transfer learning are also investigated in the systematic approaches for HRCD. The demonstration in the case study contains experiment results of multi-modal perception for robot system and human body in hybrid human-robot collaborative disassembly cell, sequence planning for an HRCD task, distance based safety strategy and motion driven control method, and it manifests high feasibility and effectiveness of the proposed approaches for HRCD and verifies the functionalities of the systematic framework.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2019.1578906