The use of probabilistic risk analysis in the jet engines manufacturing process is essential to prevent failure. It has been observed in the literature about risk management that the standard risk assessment is normally inadequate to address the risks in this process. To remedy this problem, the methodology presented in this paper covers the construction of a probabilistic risk analysis model, based on Bayesian Belief Network coupled to a bow-tie diagram. It considers the effects of human, software and calibration reliability to identify critical risk factors in this process. The application of this methodology to a particular jet engine manufacturing process is presented to demonstrate the viability of the proposed approach.
The use of probabilistic risk analysis in jet engines manufacturing process is essential to prevent failure. The objective of this study is to present a probabilistic risk analysis model to analyze the safety of this process. The standard risk assessment normally conducted is inadequate to address the risks. To remedy this problem, the model presented in this paper considers the effects of human, software and calibration reliability in the process. Bayesian Belief Network coupled to a Bow Tie diagram is used to identify potential engine failure scenarios. In this context and to meet this objective, an in depth literature research was conducted to identify the most appropriate modeling techniques and an interview were conducted with experts. As a result of this study, this paper presents a model that combines fault tree analysis, event tree analysis and a Bayesian Belief Networks into a single model that can be used by decision makers to identify critical risk factors in order to allocate resources to improve the safety of the system. The model is delivered in the form of a computer assisted decision tool supported by subject expert estimates.
Resumo A água é reconhecida mundialmente como um recurso limitado ao qual deve ser dada atenção particular. O Fórum Econômico Mundial no ano de 2017 classificou o risco denominado "Crise Hídrica" em termos de impacto em terceiro lugar, perdendo apenas para armas de destruição em massa e mudanças de clima. No Brasil, observa-se redução de pluviosidade a partir de 2012 para a região Nordeste e 2013 para a região Sudeste, sendo que, nesta última, a criticidade é atribuída à alta demanda e a poluição hídrica. O principal instrumento de gestão para este recurso é a legislação, que estabelece usos prioritários, ao qual a indústria não é inserida. O presente trabalho tem como objetivo criar um modelo e análise de riscos combinados com a utilização das ferramentas AHP e BBN para análise dos riscos advindos do cenário de crise hídrica para as indústrias siderúrgicas a fim de garantir a disponibilidade dos recursos hídricos necessários para garantir a operação segura deste tipo de indústria. A metodologia utilizada foi a de pesquisa exploratória, quando da aplicação das ferramentas probabilísticas AHP e BBN. Como resultado obtém-se uma matriz global de riscos hídricos para os processos siderúrgicos das empresas de um grupo siderúrgico no Brasil.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.