Using systems thinking-based risk assessment methods to assess hazardous manual tasks: a comparison of Net-HARMS, EAST-BL, FRAM and STPA. Issue 5 (4th May 2023)

• Record Type: Journal Article
• Authors: McCormack, Peter; Read, Gemma J. M.; Hulme, Adam; Lane, Ben R.; McLean, Scott; Salmon, Paul M.
• Is Part Of: Ergonomics. Volume 66:Issue 5(2023)
• Page Start: 609
• Page End: 626
• Publication Date: 2023-05-04
• Subjects: Systems thinking -- hazardous manual tasks -- risk assessment -- signal detection theory; Human engineering -- Periodicals; Cybernetics -- Periodicals; Industrial management -- Periodicals; Ergonomie -- Périodiques; Cybernétique -- Périodiques; Gestion d'entreprise -- Périodiques; 620.8205
• DOI: 10.1080/00140139.2022.2105959
• Languages: English
• ISSNs: 0014-0139

Abstract

Abstract: Formal risk assessment is a component of safety management relating to hazardous manual tasks (HMT). Systems thinking approaches are currently gaining interest for supporting safety management. Existing HMT risk assessment methods have been found to be limited in their ability to identify risks across the whole work system; however, systems thinking-based risk assessment (STBRA) methods were not designed for the HMT context and have not been tested in this area. The aim of this study was to compare the performance of four state-of-the-art STBRA methods: Net-HARMS, EAST-BL, FRAM and STPA to determine which would be most useful for identifying HMT risks. Each method was independently applied by one of four analysts to assess the risks associated with a hypothetical HMT system. The outcomes were assessed for alignment with a benchmark analysis. Using signal detection theory (SDT), overall STPA was found to be the best performing method having the highest hit rate, second lowest false alarm rate and highest Matthews Correlation Coefficient of the four methods. Practitioner summary: A comparison of four systems thinking risk assessment methods found that STPA had the highest level of agreement with the benchmark analysis and is the most suitable for practitioners to use to identify the risks associated with HMT systems.