Modelagem bayesiana da influência do risco de falha em equipamentos nos custos, interferências operacionais e impactos socioeconômicos de uma operação metroferroviária

Abstract

The growing demands for the provision of services with high quality and fewer operational interruptions leads the rail and subway transport operators to seek different methods to improve the performance of equipment, with a focus on the availability and improvement of classic maintenance performance indicators, such as the MKBF (Mean Kilometer Between Failures) for example. However, the available methodologies rarely relate the reliability of the systems with the risk of interruption in the provision of service, as consequence the classic maintenance indicators have little or no use in the scope of the management of the system's operation. This work proposes a reliability evaluation model, considering its impact on the quality of the transport system operation, using Bayesian Networks to estimate the reliability of a critical equipment for the operation of the transport system. The model was elaborated from failure data analysis and experts opinion; component reliability data and probabilities of events responsible for operational impacts feeds the proposed Bayesian Network. Maintenance costs and socioeconomic benefits generated by the transport system operation data are used to assess the economic impacts of interruptions. The proposed model provides a forecast of maintenance costs, operational interferences, and impacts on the socioeconomic benefits generated, from the reliability of the equipment components under analysis. The study main proposal is to provide a model to evaluate the equipment reliability impact in the subway system performance, additionally is provided a framework to apply the model in other types of systems. The proposed model can be applied in management decision making, provide service operation improvement, and even guide new investments on systems performance.