Development of an Enhanced Risk Assessment Model for Human–Robot Collaboration and its Application

Background: Collaborative robots have emerged as a solution for complex and precision-driven tasks. However, there is no comprehensive risk assessment model for collaborative robotic work in the Republic of Korea. Thus, we aim to develop a risk assessment model tailored to the unique characteristics of human-robot collaboration. Methods: In this study, we examine the risk assessment factors in three key fields: worker, robotic systems, and work environment. The items adopted in the existing models of HFACS, USUS, and human–robot trust were initially selected to extract items for the risk assessment model. The analytic hierarchy process methodology was applied to refine and prioritize the evaluation items. Score scales were constructed for the six checklists. A five-level score ranging from one to five was given to each question in the checklist, and the average score was used to quantitatively evaluate each area. Results: The six evaluation checklists coalesced to constitute a comprehensive risk assessment model was adjusted for collaborative robot operations. Implementing the proposed model in six robot-operated workplaces yielded consistent results. Companies involved in previous robot-related accidents exhibited deficiencies in these risks than accident-free robot workplaces. Thus, comprehensive risk assessments encompassing the necessary factors are crucial to prevent accidents in robot-related work environments. Conclusion: The proposed risk assessment model can offer a robust foundation for guiding the future development of diverse risk assessment models for collaborative robot environments and facilitate the safe coexistence of humans and robots in the Industry 4.0 era.