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Research Article

A systematic investigation of the barriers to effective implementation of human-robot assembly line: an integrated multi-criteria decision-making approach

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Pages 198-223 | Received 13 Jul 2022, Accepted 16 Oct 2023, Published online: 24 Nov 2023
 

ABSTRACT

Human-robot collaboration (HRC) is putting humans back at the centre of manufacturing via tech-empowered workers. On human-robot assembly line (HRAL), humans and collaborative robots (cobots) can perform tasks collaboratively to improve flexibility and reconfigurability. Most previous work focuses on the production optimization of HRAL yet lacks systematic analysis of the implementation of HRAL. This study investigates factors influencing HRAL implementation: drivers, benefits and barriers, aiming to help practitioners realise suitable application scenarios and overcome implementation challenges. This study defines the features of three important resources on HRAL (humans, robots and cobots) via skillsets and discusses the contribution of these features to the benefits and limitations of HRAL. Furthermore, a novel Triple-I framework is proposed to summarise the implementation barriers of HRAL. The relative importance of these barriers is analysed by Best-Worst Method (BWM), and the impact on various HRAL configurations is assessed using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show that critical barriers revolve around the limitations in productivity and accuracy, resulting in safety-rated monitored stop-based HRAL configurations being the most appropriate choice for the automotive industry. Finally, this study offers practitioners with a barrier elimination plan to aid successful HRAL implementation.

Acknowledgments

The authors wish to thank the experts for providing their valuable opinions during the project. The authors would also like to express their appreciation to anonymous referees for their constructive comments. This work is supported in part by China Scholarship Council (CSC) under Grant No. 202106060016.

Disclosure statement

No potential conflict of interest was reported by the author(s).