Human-robot collaboration in disassembly for sustainable manufacturing

Quan Liu, Zhihao Liu, Wenjun Xu, Quan Tang, Zude Zhou

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)
571 Downloads (Pure)


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.
Original languageEnglish
Article number10.1080/00207543.2019.1578906
Pages (from-to)4027-4044
Number of pages18
JournalInternational Journal of Production Research
Issue number12
Publication statusPublished - 14 Feb 2019
Externally publishedYes


  • artificial intelligence
  • cyber-physical production system
  • human-robot collaboration
  • product disassembly
  • sustainable manufacturing


Dive into the research topics of 'Human-robot collaboration in disassembly for sustainable manufacturing'. Together they form a unique fingerprint.

Cite this