Abstract
Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers have in shaping their own performance should be taken into account in order to understand the causal factors that may lead to errors while performing a task and identifying which human factors may prevent errors from occurring. In line with this purpose, the aim of this study is to present a new methodology for the assessment of human reliability. The proposed model relies on well-known HRA methodologies (such as SPAR-H and HEART) and integrates them in a unified framework in which human factors assume the role of safety barriers against human error. A test case of the new method was carried out in a logistics hub of an energy company. Our results indicate that human factors play a significant role in preventing workers from making errors while performing tasks by reducing human error probability. The limits and implications of the study are discussed.
Highlights
Once the generic task types (GTT) is chosen, the assessor identifies the nominal error probability (NEP) value associ ated with the specific category of GTT
The assessor may use task observation or interviews to attain all of the information required to estimate the impact of performance shaping factors on human reliability
Once the assessment is carried out, the method requires the identification of the multipliers associated with each performance shaping factors (PSF) and the estimation of the overall impact of PSFs on the probability of human failure through the calculation of the value of the PSF composite (PSFC) as the product of the multipliers of the PSFs: PSFC =
Summary
Human reliability analysis (HRA) is a systematic technique to assess human error probability and has been widely used in various industries for enhancing the safety and reliability of complex socio-technical systems. Several human reliability analysis (HRA) methods have been developed to predict human error associated with working performance. They estimate the probability of human error based on workers’. According to the study results, traditional HRA methods are not suitable for today’s working environments due to the transformation of tasks and systems. For this reason, the authors suggest focusing on the development of advanced HRA models that could overcome such limitations
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