ArticleScientific reports2026
An integrated hybrid HAZOP and fuzzy analytic hierarchy process framework for enhanced safety risk prioritization in process industries.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Safety risk assessment is crucial for managing hazards in chemical process industries. This study aimed to develop and validate a semi-quantitative risk assessment method, termed HAZOP+, tailored for these industries. The research was conducted in 2025 using a multi-phase approach. A two-stage Delphi survey involving 41 domain experts was carried out to identify and validate relevant risk factors. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was employed to establish hierarchical relationships among the factors and assign relative weights. The proposed HAZOP+ model was validated through a reality check, a field study in a large-scale chemical process industry, and an independent peer review. Severity factors (weight 0.602) influenced overall risk more than probability factors (0.337). Key severity sub-factors were human injury (0.199) and operational interruption (0.191); key probability sub-factors were reliability (0.190) and redundancy (0.179). The model showed strong content validity (CVR = 0.805, CVI = 0.927) and reliability (Cronbach's alpha = 0.88). In the case study, HAZOP+ provided more precise risk estimations than traditional HAZOP, especially for high-risk scenarios. The HAZOP+ method effectively enhances traditional HAZOP from a qualitative risk identification tool into a semi-quantitative risk assessment and ranking framework. By integrating expert consensus through the Delphi method, hierarchical weighting using fuzzy AHP, and practical validation, it addresses the subjectivity and qualitative limitations of conventional approaches. This technique enables safety professionals to more effectively identify, evaluate, and prioritize risks, ultimately enhancing operational safety and optimizing resource allocation.
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