Desenvolvimento de ferramentas de sistemas inteligentes na análise de confiabilidade humana em sistemas industriais.

Detalhes bibliográficos
Ano de defesa: 2012
Autor(a) principal: Murari, Mariana Lima Acioli
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Alagoas
Brasil
Programa de Pós-Graduação em Engenharia Química
UFAL
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: http://www.repositorio.ufal.br/handle/riufal/1199
Resumo: The human reliability analysis has been researched and developed for decades in different branches of industry: civil, chemical, petroleum, petrochemical, energy, among others. The increasingly strict legislation and the current public opinion factor due to accidents are even more crucial than the material losses and may order a company to bankruptcy. On the other hand beyond the corporate investment in risk prevention automation systems has been widely used both to reduce the exposure of people at risk and for financial gain with stabilizing and balancing processes, avoiding loss of raw materials and supplies , energy costs among others. However, this automation does not exempt people in their control arise some questions about the adequacy of the needs of operators, which factors most influence on your performance and what is the probability of human error during an emergency situation. To address these questions is necessary to use subjective variables without rigid boundaries that carry large uncertainties from the human knowledge and that in classical programming languages are not represented effectively. So Fuzzy logic has shown interesting results in the representation of these systems. In this work it was found that fuzzy logic is a powerful tool in determining factors that influence human performance and error probability based on experience of experts.