Research Perspectives in Collaborative Assembly: A Review

Author:

Yonga Chuengwa Thierry1ORCID,Swanepoel Jan Adriaan1ORCID,Kurien Anish Matthew2ORCID,Kanakana-Katumba Mukondeleli Grace3,Djouani Karim24ORCID

Affiliation:

1. Department of Industrial Engineering, Tshwane University of Technology, Staatsartillerie Rd, Pretoria 0183, South Africa

2. F’SATI, Department of Electrical Engineering, Tshwane University of Technology, Staatsartillerie Rd, Pretoria 0183, South Africa

3. FEBE, Tshwane University of Technology, Staatsartillerie Rd, Pretoria 0183, South Africa

4. LISSI LAB, University Paris Est-Creteil, Avenue du General de Gaulle, 9400 Cretail, France

Abstract

In recent years, the emergence of Industry 4.0 technologies has introduced manufacturing disruptions that necessitate the development of accompanying socio-technical solutions. There is growing interest for manufacturing enterprises to embrace the drivers of the Smart Industry paradigm. Among these drivers, human–robot physical co-manipulation of objects has gained significant interest in the literature on assembly operations. Motivated by the requirement for human dyads between the human and the robot counterpart, this study investigates recent literature on the implementation methods of human–robot collaborative assembly scenarios. Using a combination of strings, the researchers performed a systematic review search, sourcing 451 publications from various databases (Science Direct (253), IEEE Xplore (49), Emerald (32), PudMed (21) and SpringerLink (96)). A coding assignment in Eppi-Reviewer helped screen the literature based on ‘exclude’ and ‘include’ criteria. The final number of full-text publications considered in this literature review is 118 peer-reviewed research articles published up until September 2022. The findings anticipate that research publications in the fields of human–robot collaborative assembly will continue to grow. Understanding and modeling the human interaction and behavior in robot co-assembly is crucial to the development of future sustainable smart factories. Machine vision and digital twins modeling begin to emerge as promising interfaces for the evaluation of tasks distribution strategies for mitigating the actual human ergonomic and safety risks in collaborative assembly solutions design.

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

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