Uma abordagem GIS para cálculo de desgaste em programas de manutenção

Abstract

The population growth, mainly in urban areas, implies the corresponding growth in the needs of the infrastructure. The transport sector is one of the areas within this infrastructure which need improvements. For companies that have heavy machinery, such as trucks, tractors, excavators, and others, the maintenance of such equipment is a relevant part of the machines’ administration. Predictive maintenance is a subfield of maintenance that is concerned about using data to predict variables of interest. It is composed of the following steps: data processing, diagnosis, prognosis and decision making. This work plays a part in the first two steps, namely data processing and diagnosis. Geographical data is used to propose a vehicle wear index that can be used for such diagnosis tasks. As an example scenario, the “Inter II”bus line data of Curitiba was analysed. As result, the wear index for the vehicles that are assigned to that line were computed, and the data in the Central 156 database for that line was also analysed in conjunction with the proposed index.