Improving the assessment of human barriers: an innovative methodology for the Energy industry
Guglielmi, Dina
Paolucci, Alessio
Fraboni, Federico
Mariani, Marco Giovanni
Pietrantoni, Luca
Casson Moreno, Valeria
Cozzani, Valerio
Mora, Cristina
Borzi, Marco
Soscia, Irene
Scataglini, Luciano
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How to Cite

Guglielmi D., Paolucci A., Fraboni F., Mariani M.G., Pietrantoni L., Casson Moreno V., Cozzani V., Mora C., Borzi M., Soscia I., Scataglini L., 2022, Improving the assessment of human barriers: an innovative methodology for the Energy industry, Chemical Engineering Transactions, 90, 715-720.
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Abstract

The present contribution aims at providing an innovative method for the assessment of human barriers, specifically addressing the framework of the energy industry, including offshore operations. Introducing a revised framework to analyse human errors, the methodology developed aims at extending the current Human Reliability Analysis (HRA) methods including psychosocial factors and barriers. The new methodology was developed extending and tailoring to the specific context the well-known framework set by two widely used HRA methodologies (SPAR-H and HEART). An innovative holistic framework, dedicated to the wide range of operations of the energy industry, was developed to assess human error probability (HEP). Human factors were considered safety barriers against human error: more specifically, workers were considered having an active role in shaping their own performance. The method developed introduced a revision of the Generic Task Types (GTT). Each GTT was then associated with a Nominal Error Probability (NEP). The NEP is then modified by the assessment of correction factors obtained from the assessment of conditions affecting task performance, in analogy with the Performance Shaping Factors (PSF) approach introduced by SPAR-H. The method proved to be easy to apply and the results obtained clearly show that human factors play a significant role in preventing workers from making errors while performing tasks by reducing human error probability.
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