Comparing capability of scenario hazard identification methods by the PIC (Plant-People-Procedure Interaction Contribution) network metric

Seligmann, Benjamin J., Zhao, Jiayi, Marmar, Sophia, Corbett, Tayla C., Small, Michael, Hassall, Maureen, and Boadle, Jesse T. (2019) Comparing capability of scenario hazard identification methods by the PIC (Plant-People-Procedure Interaction Contribution) network metric. Safety Science, 112. pp. 116-129.

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Abstract

Comparing the results of hazard identification (HAZID) methods is a complex task, but the question that drives this activity is vitally important: which HAZID method should be used to best identify an accident scenario? Despite many efforts to address this, effective metrics do not yet readily exist for clearly comparing HAZID results for a particular scenario. The complexity of socio-technical systems is often cited as a key factor that limits effective scenario identification, calling into question traditional HAZID efforts. Motivated by the observation that interactions between multiple component types, such as People, Plant and Procedures (P3), often significantly contribute to major process system accidents, being an expression of the complexity of the system, a novel, precise, network topology-based metric for calculating the contribution of P3 Interactions to accident scenarios is presented. This metric, called the P3 Interaction Contribution (PIC), is intended to be used for comparing the HAZID results. An illustrative example of using the PIC for HAZID comparison is included, whereby Failure Mode and Effects Analysis (FMEA), Blended Hazard Identification methodology (BLHAZID) and Systems Theoretic Process Analysis (STPA) were each applied to a heat exchanger start-up operation.

The results show initial promise that the PIC can be effective as a HAZID comparison tool. The main outputs of this paper are the presentation of the PIC calculation process and the method for applying the PIC to HAZID results. The paper concludes with recommendations for further experimental work to explore the validation and assess the true value of the PIC.

Item ID: 56653
Item Type: Article (Research - C1)
ISSN: 0925-7535
Keywords: Hazard identification, Network, Accident, Complexity, Socio-technical
Copyright Information: © 2018 Elsevier Ltd. All rights reserved.
Date Deposited: 19 Dec 2018 07:37
FoR Codes: 09 ENGINEERING > 0915 Interdisciplinary Engineering > 091507 Risk Engineering (excl Earthquake Engineering) @ 100%
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