A methodology for human reliability analysis of oil refinery and petrochemical operations: the hero (human error in refinery operations) hra methodology

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: RAMOS, Marilia Abílio
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de Pernambuco
UFPE
Brasil
Programa de Pos Graduacao em Engenharia Quimica
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufpe.br/handle/123456789/24864
Resumo: The oil industry has grown in recent decades in terms of quantity of facilities and process complexity. However, human and material losses still occur due to major accidents at the facility. The analysis of these accidents reveals that many involve human failures that, if prevented, could avoid such accidents. These failures, in turn, can be identified, modeled and quantified through Human Reliability Analysis (HRA), which forms a basis for prioritization and development of safeguards for preventing or reducing the frequency of accidents. The most advanced and reliable HRA methods have been developed and applied in nuclear power plant operations, while the petroleum industry has usually applied Quantitative Risk Analysis (QRA) focusing on process safety in terms of technical aspects of the operation and equipment. This thesis demonstrates that the use of HRA in oil refining and petrochemical operations allows the identification and analysis of factors that can influence the behavior of operators as well as the potential human errors that can contribute to the occurrence of an accident. Existing HRA methodologies, however, were mainly developed for the nuclear industry. Thus, they may not reflect the specificities of refining and petrochemical plants regarding the interaction of the operators with the plant, the failure modes of the operators and the factors that influence their actions. Thus, this thesis presents an HRA methodology developed specifically for use in this industry, HERO - Human Error in Refinery Operations HRA Methodology. The Phoenix HRA methodology was used as a basis, which has three layers i) a crew response tree (CRT), which models the interaction between the crew and the plant; ii) a human response model, modeled through fault trees, that identifies the possible crew failures modes (CFMs); and (iii) "contextual factors" known as performance influencing factors (PIFs), modeled through Bayesian networks. In addition to building on such a structure, HERO's development relied on interviews with HRA specialists, visitations to a refinery and its control room, and analysis of past oil refineries accidents - four accidents were analyzed in detail. The methodology developed maintains the three-layer structure and has a guideline flowchart for the construction of the CRT, in order to model the team-plant interactions in oil refining and petrochemical operations; it also features CFMs and PIFs developed specifically for this industry, with definitions that make them easily relatable by an analyst. Finally, the methodology was applied to three potential accidental scenarios of refinery operations. In one of these scenarios, it was combined with a QRA to illustrate how an HRA can be applied to a traditional QRA and to demonstrate the influence of PIFs and of human error probability on the final risk. The use of this methodology for HRA of refineries and petrochemical plants operations can enhance this industry safety and allow for solid riskbased decisions.