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Introducción del factor humano al análisis de riesgo

  • Autores: José Roberto González Dan
  • Directores de la Tesis: Josep Arnaldos Viger (dir. tes.), Maria Rosa Darbra Roman (dir. tes.)
  • Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2015
  • Idioma: español
  • Tribunal Calificador de la Tesis: Joaquim Casal Fàbrega (presid.), Vicenç Martí (secret.), Micaela Demichela (voc.), Jesús Guardiola Soler (voc.), Christophe Bengoa (voc.)
  • Materias:
  • Enlaces
    • Tesis en acceso abierto en: TDX
  • Resumen
    • The frequency of occurrence of an accident is a key aspect in the risk assessment field. Variables such as the human factor, which is a major cause of undesired events in process industries, are usually not considered explicitly, mainly due to the uncertainty related to the lack of knowledge and the complexity associated to it. In this thesis, a frequency modifier has been developed in order to introduce the human factor in the failure frequency estimation. This modifier takes into account variables such as: the organizational factor, the job characteristic factor and the personal characteristic factor. The inclusion of the human factor was done through the application of two methodologies: the fuzzy logic and the Monte Carlo simulation. The first one is based on the operation of the human reason, because of that, the contribution of international experts on the subject area was taken into account through a questionnaire. In the second one, Monte Carlo, the variables are represented by probability functions through a probabilitic treatment. The modifiers were applied to four case studies of real chemical plants: two related to the storage of flammable products and another two dedicated to the toxic and flammable products storage. The new frequency values are considered more realistic and accurate since the human factor is now reflected. In addition, the models were validated with the comparison of the obtained results with a widely international recognized method: the Quantitative Risk Analysis (QRA). Consequently, the final evaluation of the risk is more conservative but in the same line as the results obtained through a QRA.


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