The EVOLINE project aims to advance inline oil Condition Monitoring (CM), essential for improving the reliability, efficiency, and operational lifespan of lubricated machinery (such as gearboxes) in various industries. Targeting manufacturers of transmissions and heavy-duty equipment, the project addresses key industrial challenges: optimising maintenance schedules and costs, improving equipment uptime, and providing deeper insights into oil degradation mechanisms. Companies still face difficulties in oil data interpretation and correlating oil conditions with machinery health. This is primarily due to a lack of understanding of the underlying oil degradation mechanisms, the influence of oil contaminants (water ingress, air bubbles, wear debris from various system components) on oil condition, and the link to machinery degradation. Therefore, the EVOLINE project seeks to overcome these challenges by focusing on three main goals: (i) achieving detailed insights/correlations on how chemical oil degradation (oxidation, chain scission) and oil contaminants (wear debris, water, air) affect the oil’s basic properties of interest (viscosity, electrical conductivity, etc.) under typical operating conditions, (ii) developing a systematic approach to correlate oil degradation trends to detect physical wear damage of gear(boxe)s, and investigating the strength of complementing oil CM with other CM techniques (vibrations, vision), (iii) creating oil sensor uncertainty estimation models to make better decisions on oil replacement, as well as to guide the selection of the best sensor position. The EVOLINE insights and results will enable industry users to understand the effects of oil degradation and contamination on oil property trends, as well as to select the most suitable sensors for a particular use case. Reliably tracking the oil condition and/or wear contamination will allow for optimising oil change intervals, linking with component (e.g. gears, bearings) degradation, and contributing to improved machinery health.