A task scheduling model integrating micro-breaks for optimisation of job-cycle time in human-robot collaborative assembly cells

Abstract

Human-Robot Collaboration, whereby human worker and robot perform tasks jointly, is becoming the new frontier in industry production. Unlike robots, continuous work leads to an accumulation of human fatigue, which is the main cause of decreased efficiency and deterioration of health. Characteristic differences between human and robot bring challenges to collaboration task scheduling. In this paper, we studied the task scheduling of a human-robot collaboration assembly cell to achieve a trade-off between job cycle and human fatigue. A task scheduling model integrated with micro-breaks inside job cycles was proposed to avoid human fatigue accumulation by taking advantage of the human-robot collaboration characteristics. Furthermore, the optimisation of task scheduling by taking the job cycle as the objective function and maximum human fatigue as a constraint was solved. The developed method is studied on a cable assembly inspired by an industry case. The results of the case study are presented to indicate the validity and practicability of the proposed model. It suggests that compared with the model of placing rest breaks between job cycles, the proposed model outperforms in job-cycle performance in most cases. Finally, there are some insights on the HRCAC which are obtained from the results of the case study.

KEYWORDS:

• Human-robot collaboration
• task scheduling
• fatigue-recovery
• job-cycle minimisation
• micro-break

Disclosure statement

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

Additional information

Funding

]This work was supported by the National Natural Science Foundation of China [grant number 61661013]; College teacher research project of Guangxi [grant number 2019KY0252]; Natural Science Foundation of Guangxi Province [grant number 2018GXNSFAA281327].

Notes on contributors

Ming Zhang

Ming Zhang is a PhD candidate and an Assistant Professor of Guilin University of Electronic Technology. He received his S.M. (2006) in Signal Processing and B.S (2001) in Mechanical-electronic Engineering from Guilin University of Electronic Technology. He studies the collaboration of human and robot and is developing computational methods for real-time and collaborative planning optimisation.

Chunquan Li

Chunquan Li has been a Professor of Mechanical and Electrical Engineering at the Guilin University of Electronic Technology since 2011. He was a visiting scholar at North Carolina State University in 2011. He received his PhD in Mechanical Engineering from the Shanghai University in 2010. He has authored over 40 professional and scholarly publications in famous international journals or international conferences in the specialised field of the electronic manufacturing technology, and advanced manufacturing technology.

Yuling Shang

Yuling Shang has been a Professor of Electronic Engineering and Automation at the Guilin University of Electronic Technology since 2017. She received her PhD in Circuits and Systems from the Xi’an University of Electronic Science and Technology in 2010. She has authored over 30 professional and scholarly publications in famous international journals or international conferences. Her research interests focus on electronic manufacturing technology, fault diagnosis and testing technique.

Hongyan Huang

Hongyan Huang is PhD candidate and a teaching staff of Guilin University of Electronic Technology. He received his B.S (2000) in Machine Design and Manufacturing and Automation at School of Mechatronic Engineering from Changchun University of Science and Technology, and his S.M. (2003) in Machine Manufacturing and Automation at School of Mechanical and Electronic Engineering from Guilin University of Electronic Technology. His main research field is simulation and optimisation technology in automation manufacturing system.

Wangchun Zhu

Wangchun Zhu has been being a Professor of Electrical Engineering and Automation at Guilin University of Electronic Technology since 2016. He mainly researches automatic test bus, automatic test system and software, virtual instrument and interchangeable virtual instrument.

Yujia Liu

Yujia Liu is a master candidate of Guilin University of Electronic Science and Technology. She received her B.S. degree in mechanical engineering from Guizhou Institute of Technology in 2017. She studies microelectronics manufacturing technology.