Processing FT-IR data for facilitated oil condition monitoring

Abstract

The physical and chemical condition of a lubricant plays a vital role in the long-term operability of engineering systems. Hence, oil condition monitoring of high-value and heavy-duty equipment is a common practice across numerous industries. However, this practice is not utilized on a regular basis for passenger cars, and car fleets. For general automotive purposes, a simpler time and mileage-based approach is favored. This approach employs fixed oil change intervals, that are based on average usage, with more recently produced vehicles only slightly modifying these intervals by monitoring oil temperatures over time. With rising environmental concerns and increasing focus on systemic approaches, reducing waste production is gaining importance. Being aware of lubricant condition opens up the opportunity to optimized, condition-based oil changes, that can help reduce waste by elongating the service life of engine oils. This study presents a methodology of processing FT-IR data that allows for a simplified decision making regarding the prolonged applicability of used engine oil. The presented method can be implemented as a step of planned maintenance during scheduled service at a repair shop, as well as a regular investigation by fleet operators.