Exploring the Effects of Perceived Complexity Criteria on Performance Measures of Human–Robot Collaborative Assembly

SEE OUR PUBLICATION: Verna E., Puttero S., Genta G., Galetto M., Exploring the Effects of Perceived Complexity Criteria on Performance Measures of Human–Robot Collaborative Assembly (778.69 kB), Journal of Manufacturing Science and Engineering (2023) 145(10): 101014. DOI:10.1115/1.4063232.

The use of Human-Robot Collaboration (HRC) in assembly tasks has gained increasing attention in recent years as it allows for the combination of the flexibility and dexterity of human operators with the repeatability of robots, thus meeting the demands of the current market. However, the performance of these collaborative systems is known to be influenced by various factors, including the complexity perceived by operators. This study aimed to investigate the effects of perceived complexity on the performance measures of HRC assembly. An experimental campaign was conducted in which a sample of skilled operators was instructed to perform six different variants of electronic boards and express a complexity assessment based on a set of assembly complexity criteria. Performance measures such as assembly time, in-process defects, quality control times, offline defects, total defects, and human stress response were monitored. The results of the study showed that the perceived complexity had a significant effect on assembly time, in-process and total defects, and human stress response, while no significant effect was found for offline defects and quality control times. Specifically, product variants perceived as more complex resulted in lower performance measures compared to products perceived as less complex. These findings hold important implications for the design and implementation of HRC assembly systems and suggest that perceived complexity should be taken into consideration to increase HRC performance.