Most companies and systems that wish to implement the Six Sigma methodology seek to adapt their processes to their reality, facing abrupt changes to differentiate themselves from the rest and make the most of each process resource process. This research directed to the application of a fleet of trucks for the collection of urban solid waste, which is considered one of the most representative assets of the organization dedicated to this type of service. To analyze truck fleet availability and reliability, information on downtime for corrective maintenance was identified through a statistical distribution model to measure reliability and survivability. In addition, it was possible to establish the metrics of the behavior of truck stops for repairs. Three critical oil quality factors were studied: viscosity, TBN, and ppm of worn aluminum, obtained from the physicochemical analysis of engine oil changed every 250 h performed by ASTM-certified laboratories and other laboratories specialized in ASTM and the manufacturer’s laboratories. The results indicate that the most adequate reliability and survival model corresponds to the two-parameter Weibull model; statistical analysis and graphs with critical limits were established. Finally, it was determined that it is still possible to take advantage of the oils, maximize fleet availability, reduce maintenance costs, and contribute to reducing environmental impact.