A tool to evaluate industrial cobot safety readiness from a system-wide perspective: An empirical validation

可用性 知识管理 实证研究 过程管理 风险分析(工程) 灵活性(工程) 计算机科学 工程类 人机交互 业务 哲学 统计 数学 认识论
作者
Nicole Berx,Wilm Decré,Liliane Pintelon
出处
期刊:Safety Science [Elsevier BV]
卷期号:170: 106380-106380 被引量:1
标识
DOI:10.1016/j.ssci.2023.106380
摘要

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.
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