When making decisions that revolve around oil health, it is very important to have a complete and representative understanding of the health of the oil in your asset so that you can make the best decisions and implement a preventative maintenance schedule and optimize your operations. Decision-making between oil changes, bleed and feed, top offs, etc., is often difficult because trending of the oil’s critical properties and remaining useful life (RUL) estimation are not available.

This disparity between the information needed to make decisions and the lack of information available by traditional oil condition monitoring methods can lead to severe consequences in the form of unnecessary O&M costs for wasteful oil changes, or arguably worse, extensive and costly damage to the equipment being monitored. For example, on a fleet of 5,000 locomotives, extending just 25% of each oil change an additional 6 months equates to a savings of $10 million a year, on average.

This shows why companies might want to wait to change the oil in their asset; it can have a great cost savings. However, if companies miss an event or the oil’s RUL depletes faster than expected and is not changed when it needs to be, this can damage the equipment and lead to extremely expensive repairs and increased downtime. For example, a wind turbine gearbox replacement can cost more than $350,000, including on-site crane rental, downtime lost revenue, installation and testing, and startup costs, and this same idea is applicable to other industries as well.

This dilemma between wanting to minimize cost without damaging the asset shows the value online oil condition monitoring can provide to businesses in order to optimize their operations and reduce unnecessary costs. Online oil condition monitoring allows for oil change optimization based on actual measurements, as compared to traditional time-based changes. With traditional time-based changes, oil is almost always exchanged too early too or too late due to the nature of oil condition and wear debris generation. An example of how more data can help extend life and minimize oil changes and costs can be seen in the graph below:


Many of the key properties and contaminant levels used to measure RUL and identify preventative and life-extending actions such as oxidation, TBN, total acid number (TAN), additive packages, viscosity, water, fuel, soot, etc… are event driven. This means that events such as water and fuel contamination can happen within minutes and can be missed just hours later. This makes it extremely difficult to capture an accurate and representative sample of oil health when using offline sampling methods.

Since online oil condition monitoring is real-time and continuous, it is able to identify events and allows for optimized oil change intervals for each asset. Using this data RUL can be estimated and life extension actions can be optimized based on operational needs. Actions such as bleed and feed can be measured and overall oil life can be extended through many tools available to reliability teams.

As you can see for all the above reasons, having a large amount of high quality data is extremely important in order to make the best decisions on how to operate your assets and minimize issues. Online oil condition monitoring systems are able to provide the data necessary to make optimal maintenance decisions and have proven to be critical, cost-saving tools.

For more information on why online oil condition monitoring is a best practice for reliability programs, check out our white paper on the subject here!