Setayesh Azin, Di Pasquale Valentina, Neumann W Patrick
Mechanical and Industrial Engineering, Ryerson University, Ryerson University, Toronto, ON, M5B 2K3, Canada.
Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132- 84040, Fisciano, SA, Italy.
Appl Ergon. 2022 Jul;102:103750. doi: 10.1016/j.apergo.2022.103750. Epub 2022 Apr 6.
This paper presents a comparison of four common Human Reliability Assessment (HRA) models through a scoping literature review and sensitivity analysis. The scoping literature review identified 72 relevant studies which formed the basis of the comparison. Studies reported the four selected models have similarities in terms of the sector of origin, applied sectors, output calculation, and a lack of clear guidelines on Performance Influencing Factors (PIFs) selection and risk level allocation. The studied models have differences in the number and type of PIF inputs and Human Error Probability (HEP) calculation procedures. The One Factor At a Time (OFAT) and "combined" sensitivity analysis were conducted to examine the HRA models' responses to systematic risk level changes when each of 8 matching PIFs were systematically set to "high" and then "low" levels individually and simultaneously. The OFAT analysis showed coefficients of variation (CV) in HEP varying from 9% for skills/training up to 94% for work procedure when the PIFs are assigned to a "low" risk level individually. The combined analysis showed the median HEP value close to 97% and 1% when PIFs are assigned to" high" and "low" risk levels respectively. Although the selected HRA models were reported to be validated in high-risk domains there was no study found that validated these models in low-risk domains such as manual order picking, or manual assembly lines. The HRA models examined here are disconnected from specific system design elements which can inhibit design improvement efforts. The study outcome suggests the need for clear guidelines for PIFs selection and risk level allocation. Future research should address both the connection of error assessment to the design of the system and the features of new HRA models that affect its reliability and validity in a variety of industrial contexts.
本文通过范围界定文献综述和敏感性分析,对四种常见的人因可靠性评估(HRA)模型进行了比较。范围界定文献综述确定了72项相关研究,这些研究构成了比较的基础。研究报告称,所选的四种模型在起源领域、应用领域、输出计算方面存在相似之处,并且在性能影响因素(PIFs)选择和风险水平分配方面缺乏明确的指导方针。所研究的模型在PIF输入的数量和类型以及人因失误概率(HEP)计算程序方面存在差异。进行了一次一因素(OFAT)和“组合”敏感性分析,以检验当8个匹配的PIF分别系统地设置为“高”水平然后再设置为“低”水平时,HRA模型对系统风险水平变化的响应。OFAT分析表明,当PIF单独分配为“低”风险水平时,HEP的变异系数(CV)从技能/培训的9%到工作程序的94%不等。组合分析表明,当PIF分别分配为“高”和“低”风险水平时,HEP的中位数分别接近97%和1%。尽管所选的HRA模型据报道在高风险领域得到了验证,但未发现有研究在诸如人工订单拣选或手动装配线等低风险领域对这些模型进行验证。这里所研究的HRA模型与特定的系统设计元素脱节,这可能会阻碍设计改进工作。研究结果表明需要明确PIF选择和风险水平分配的指导方针。未来的研究应解决错误评估与系统设计的联系,以及新HRA模型在各种工业环境中影响其可靠性和有效性的特征。