We are always keen to share our learning and just this week our team was analysing several sets of oil sample data from two sites owned by the same client. This client has a strong focus on ISO cleanliness codes as a mechanism to perform proactive maintenance. Our system is able to automatically provide more detailed advice and direction for our client when a code does not meet its required target.

 

There is either contamination due to external ingress, internal generation or the code does not meet the target due to other substances in the oil. With external ingress we can easily identify this and provide the site the correct advice to correct the ISO cleanliness. Similarly, with internal ingress we can also provide more details on why it maybe generating this contamination. In the final case, where there is no sign of internal or external contamination but the ISO code does not meet the targets we can order a patch test to determine the cause of this and not have people taking unnecessary actions on site.

 

All Transmission oil samples and their ISO results plotted against the OEM recommended levels.  Close to 50% of all transmission oil samples taken exceeded the OEM guidelines for 6 micron, and over 20% of all samples taken exceeded the OEM guidelines for 14 micron.

ISO 6M, 14M

Transmission Samples were then filtered further to remove all samples that returned ISO levels within the OEM guidelines. Leaving behind only the oil samples that had exceeded the OEM recommended Guidelines for 6 and 14 micron.

OEM

Theses ISO exception samples were then plotted to show dirt ingress and wear metals. This was done to determine how many of the Transmission oil samples had underlying issues that were contributing to the high particle count readings.

Dirt Trends

Iron Wear trends

Fe Trends

Cu Wear trends

Cu Trends

PQI Trends

High ISO - PQI Trends

From the transmission samples taken across 3 different sites oil samples that exceeded the OEM recommended limits, only 12% of these samples showed signs of increased wear or external contamination. Of the samples that did show increased wear or external contamination they were all identified by the algorithms and would have resulted in actions to inspect and correct the underlying issues.

 

For the remaining  88% of Transmission samples flagged for High ISO results but showed no evidence of wear or external contamination, the challenge is determining which of these oil samples are potentially indicating a failing clutch pack or other underlying issue. The use of specifically designed algorithms, enable the cleansing of this data to remove the normal samples and the noise they create, which often masks the real underlying issues. From there further algorithms apply the same experience and logic as a 20 year experienced condition monitoring expert, to flag the components that require further investigation to confirm condition.

 

Our goal is to develop a software tool that incorporates the experience of a 20 year experienced condition monitoring expert without the need to have that person on site. We are pleased with our progress to date in order to achieve this goal.