Citation

Berx N, Decré W, Pintelon L. Safety Sci. 2024; 170: e106380.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.ssci.2023.106380

PMID

unavailable

Abstract

The emergence of collaborative robots (cobots) has transformed the interaction between humans and robots in industrial workspaces. While cobots offer significant advantages in productivity and flexibility, their unique interaction model with humans introduces additional safety considerations. Moreover, the adoption of cobots remains limited, partly due to a lack of awareness and knowledge about their safety. To address these challenges, the Cobot Safety Readiness Assessment Tool (CSRAT) evaluates cobot safety readiness, the combination of awareness and knowledge, from a system-wide perspective. The CSRAT is grounded in maturity grid models evaluating the readiness of technological and other safety risk factors such as operator trust, privacy, and training. It allows practitioners to self-assess their cobot safety readiness and perceived importance of risk factors. Additionally, the tool aims to facilitate alignment among internal stakeholders on cobot safety. The CSRAT prototype underwent iterative development and validation by experts from academia and industry. Empirical validation results highlight the tool's usefulness, effectiveness, and usability. It successfully enhances users' awareness and knowledge of safety risk factors and serves as a conversation starter among internal stakeholders. For industry practitioners, the CSRAT offers practical relevance in enhancing safety readiness, guiding decision-making, and addressing overlooked risk factors. Academically, this research contributes to the fields of human-robot interaction, safety evaluation, usability research, and cobot adoption. In conclusion, this research provides a comprehensive approach to evaluating cobot safety readiness and promoting informed decision-making for safer human-robot collaborations. While acknowledging CSRAT's value and limitations, the paper also points towards potential future research directions.

Language: en