Structured analysis of industrial Hazard and Operability Study data: A case study of a gas handling system relevant to ammonia processes

Abstract

Hazard and Operability (HAZOP) studies are widely applied in process industries to identify deviations, causes, and consequences associated with operational hazards. However, HAZOP results are typically documented in tabulated form and are rarely analyzed beyond the study stage, limiting their value for identifying recurring patterns and supporting risk‐informed decision‐making. This study presents a structured and semi‐quantitative analysis of an industrial HAZOP dataset derived from a gas handling system. The dataset includes information on process nodes, deviations, causes, consequences, safeguards, and risk rankings. The records were systematically encoded into categorized variables and analyzed using frequency‐based ranking, weighted criticality assessment, and pathway analysis to identify dominant cause–deviation–consequence relationships. The results show that flow‐related deviations and valve‐related failures are the main contributors to system risk. High‐risk scenarios are primarily associated with gas compression systems, particularly under reverse flow, loss of containment, and control system interactions. The analysis also identifies recurring escalation pathways linking specific causes to critical outcomes such as compressor damage and ammonia release. The proposed approach enhances interpretation of HAZOP data and supports improved safety‐focused decision‐making in gas handling and ammonia process systems. Although this study is based on an Liquefied Natural Gas (LNG) boil‐off gas recovery system, the proposed methodology is applicable to other liquefied gas handling systems, including ammonia and liquefied petroleum gas. However, the resulting hazard rankings and dominant failure mechanisms should be derived from HAZOP data specific to the process, fluid properties, and operating conditions of the facility under evaluation.