Oil changes in equipment is one of the most common preventative maintenance (PM) practices performed in fleet management. In addition to being a frequent cost item, the opportunity to optimize intervals could provide significant PM cost savings to an owner. This research investigated alternate variables for modeling oil degradation in an effort to improve oil change timing and potentially reduce PM cost. Throughout the course of the study, 952 samples were taken from North Carolina Department of Transportation (NCDOT) equipment. The samples were then analyzed using On-Site Analysis Inc. OSA4 TruckCheck oil analysis equipment. Additional data was acquired through the NCDOT’s on board diagnostic monitoring systems. Total base number (TBN), was chosen as the variable to track oil degradation. As such, the analysis data was then combined with the on board diagnostic data to create the following models: miles or hours on sample versus TBN, fuel usage versus TBN, run time versus TBN, idle time versus TBN, percent idle versus TBN, as well as a number of combine models. The models were tested at a 95% confidence level to determine that currently the ideal model remains the standard miles/hours on sample. Other models such as fuel usage showed promise as alternate models. However, due to the implementation effort required to convert current standards, the alternate methods do not pose a great enough increase in model accuracy to warrant the implementation and use of new models.
