Failure rate neural analysis in the transport sector

In order to obtain a correct failure diagnosis and to prepare more effective maintenance programmes, it is essential to have reliable forecasts about the trend of equipment and machinery failure rate. In this work attention is focused on the transport sector. First the strong points of the “intelligent” techniques of forecasting are analysed compared to the more traditionally used statistical methodologies, and then a forecasting neural model of the failure rate of the equipment installed on buses and trains is proposed. Finally an application of the model is presented.