Executive Summary
Oil analysis programs are important to prevent failures and costly downtime. A variety of testing methods are available, some performed in-house and others by third party conditioning monitoring services. Limitations of oil analysis programs are often due to costs and lack of education; the benefits of investing in effective condition monitoring can pay off, as many readers recognize. Q.1 Ideally, what kind of tool would you like to assess the effectiveness of your oil analysis program?

A program to keep track of mean time between failures (MTBF).

Faults discovered and cost of remediation versus cost of failure. Operating hours saved/downtime avoided.

We use a third party lab.

Analytical tools such as viscometrics, inductively coupled plasma (ICP), infrared (IR) analysis, acid number, cleanliness, etc.

Remote monitoring.

Chromatography methods.

Monthly sampling and immediate action if needed based on results.

My company makes an analysis program available to customers.

Real-time issues are not readily solved.

Regardless of today’s communication protocol, a conversation with a knowledgeable technician/engineer solves many problems in a quick and efficient manner. Canned autogenerated responses are only applicable by accident.

A comprehensive report with great longitudinal metrics. The report would include a summary/overview page.

Compliance reports on scheduled samples versus actual, plus a breakdown of alarms and assets to highlight common issues.

One which demonstrates money savings.

Graphs with all pertinent information for the application of the sample: engine oil base number (BN)/acid number (AN) always included. Remote sample port valves to acquire a good sample rather than from the dipstick or oil pan plug.

Tool that predicts failure timing.

A tool that does in-line test sampling and is reliable.

Automated sampling and reporting.

Mostly analytical tools when the equipment is on test, or we receive samples from field testing. We use well-calibrated instruments and have established robust methods for fluid sampling. We use the program to monitor the fluid/hardware under test as well as determine the effectiveness of the fluid for longevity of life and hardware protection.

A competent contractor combined with reliability reports that have detailed and accurate failure analysis data.

If I was in charge of an oil analysis program, I would want some kind of feedback loop that provided information about what was found if oil analysis indicated a problem. What actions were taken? What were the results? That seems to be missing in most cases.

ICP, AN/BN, particle counter.

Artificial intelligence (AI)-based prognostic tools.

This is not a tool, but I would like a better understanding of the oil analysis report.

Currently if the report shows green, the report goes into file without reading. When it shows orange or yellow, let’s read it, and in case no immediate action it goes into file. Only when the report shows red something will be done, but that is all too late.

Dashboard key performance indicators (KPIs) from a top-down program management perspective. Feedback from actions and outcomes done/not done, etc.

If you could change anything about your current oil analysis program reporting, what would it be? What metrics would you like to see?
Are the samples being taken on schedule? 58%
Are the problems discovered being corrected? 65%
What percentage of samples submitted are alarmed, and what is the breakdown of the alarms? 46%
Are other tasks being carried out concurrently with oil sampling, and if so, what tasks? 46%
Are certain types of alarms more or less prevalent among certain types or models of equipment? 46%
Which equipment or areas are performing best? 35%
Which equipment or areas are “bad actors?” 50%
What percentage of samples taken actually led to a maintenance action (or other predictive maintenance measurement), and what is the percentage of various maintenance actions/predictive maintenances resulting from the samples? 69%
Based on an informal poll sent to 15,000 TLT readers. Total exceeds 100% because respondents were allowed to choose more than one answer.

Q.2 What types of tools/metrics do you currently use to measure the effectiveness of your oil analysis program?

Track various KPI such as MTBF.

We don’t currently have anything in place.

Third party analysis data.

Follow the trend of all the correlated parameters to see whether they match.

In-house lab analysis and at times outside lab testing sites.

Statistical tests of the media chosen were analyzed with Fourier-transform infrared spectroscopy (FTIR).

Lack of downtime, lack of repair/replace costs, third party oil analysis, four years of data trends.

We do not control the results given by our company.

Changes in maintenance and repair costs are the only facts that count. Applicable data is only valuable if it is usable.

We do get regular reports but rarely look at them because they are so complex.

Catastrophic failures avoided and consequently savings in downtime and corrective maintenance costs.

Equipment availability (%), saving by anticipation ($).

More than one sample. Trends over time to determine oil sample quality.

Oil condition monitoring trend charts.

Its reliability and ability to look at trends accurately.

Trend analysis with guard rails.

I no longer do a lot of lab work, but to my knowledge we use the ASTM cross check program to ensure our test results are in the ballpark as well as ISO required calibration, etc.

Oil consumption ratio.

MTBF/mean time to failure (MTTF).

It is mainly ad hoc and related to green/orange/red coloring in the heading. That is why oil analysis programs are treated as a cost and not as a value.

Excel.

What information, on a single sheet, would you like to have that clearly summarizes the value of your oil analysis program— that you could bring into a meeting with upper management?
Cost of program—testing and materials 48%
Labor cost of program 41%
Number of samples taken per area/unit versus alarmed samples 48%
Faults discovered and cost of remediation versus cost of failure 74%
Operating hours saved/downtime avoided 78%
Based on an informal poll sent to 15,000 TLT readers. Total exceeds 100% because respondents were allowed to choose more than one answer.

Editor’s Note: Sounding Board is based on an informal poll sent to 15,000 TLT readers. Views expressed are those of the respondents and do not reflect the opinions of the Society of Tribologists and Lubrication Engineers. STLE does not vouch for the technical accuracy of opinions expressed in Sounding Board, nor does inclusion of a comment represent an endorsement of the technology by STLE.