A blended hazard identification methodology to support process diagnosis

Seligmann, Benjamin J., Németh, Erzsébet, Hangos, Katalin M., and Cameron, Ian T. (2012) A blended hazard identification methodology to support process diagnosis. Journal of Loss Prevention in the Process Industries, 25 (4). pp. 746-759.

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A novel hazard identification methodology applied to process systems is presented in this paper. This blended hazard identification (BLHAZID) methodology blends two different types of HAZID methods: the function-driven and component-driven approach. The BLHAZID method is based on a conceptual framework called the Functional Systems Framework, which describes structure–function–goal relationships in process systems.

The goals of the BLHAZID methodology are to generate outcomes that contain a high coverage of hazards, describe detailed failure causality in process systems and express this knowledge in a structured form for effective reused in subsequent applications, such as fault diagnosis, operator training, design reviews, fault and event tree construction and hazard updates to satisfy major hazard facility requirements.

Both the BLHAZID methodology and the Functional Systems Framework were developed with involvement and advice from two major industrial partners. An industrial case study of a benzene saturation unit is presented to illustrate how the BLHAZID methodology operates in practice.

Item ID: 49394
Item Type: Article (Research - C1)
ISSN: 0950-4230
Keywords: hazard identification; failure; function; blending; causality; knowledge management
Funders: Australian Research Council (ARC), Hungarian Research Funds (HRF), BlueScope Steel (BS), BP Refinery (BPR)
Projects and Grants: ARC Linkage Grant LP0776636, HRF Grant number 83440
Date Deposited: 15 Jun 2017 05:19
FoR Codes: 09 ENGINEERING > 0904 Chemical Engineering > 090499 Chemical Engineering not elsewhere classified @ 60%
09 ENGINEERING > 0915 Interdisciplinary Engineering > 091507 Risk Engineering (excl Earthquake Engineering) @ 30%
22 PHILOSOPHY AND RELIGIOUS STUDIES > 2203 Philosophy > 220304 Epistemology @ 10%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 100%
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