Journal
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Volume -, Issue -, Pages -Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00170-023-11197-4
Keywords
Human-robot collaboration; Industry 5; 0; User experience; Repetitive assembly; Mental workload; Human factors
Ask authors/readers for more resources
Human-Robot Collaboration (HRC) is able to improve the quality and adaptability of production processes. An experiment was conducted to investigate the effects of prolonged HRC on user experience and performance in a repetitive assembly process. The results showed that HRC reduced physical exertion, mental effort, stress, and process defects, indicating the contribution of collaborative robotics in improving ergonomics and process quality in repetitive tasks.
Human-Robot Collaboration (HRC) represents an innovative solution able to enhance quality and adaptability of production processes. However, to fully exploit the benefits of HRC, human factors must be also taken into account. A novel experimental setting involving a repetitive assembly process is presented to investigate the effects of prolonged HRC on user experience and performance. Each participant was involved in two 4-h shifts: a manual assembly setting and a HRC one. The response variables collected in the study included self-reported affective state, perceived body discomfort, perceived workload, physiological signals for stress (i.e., heart rate variability and electrodermal activity), process and product defectiveness. Experimental results showed less upper limb exertion in the HRC setting, emphasizing the contribution of cobots in improving physical ergonomics in repetitive processes. Furthermore, results showed reduced mental effort, stress, and fewer process defects in the HRC setting, highlighting how collaborative robotics can improve process quality by supporting operators from a cognitive point of view in repetitive processes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available