Oil Analysis: Corrective Action

In order to achieve financial savings, organisations must implement systems that facilitate the effective operation of the oil analysis programme and conduct periodic audits to ensure that the processes are being followed.

It begins when oil sampling is done on a regular and systematic basis, problems are identified and reported by the laboratory, equipment is scheduled for troubleshooting and investigation, then corrective action that addresses the root cause of the problem is implemented, guided by the response time indicated by the laboratory. 

Problem persists

This results in performance improvement and cost savings. A check sample is taken to confirm improvement, and the process keeps repeating as machine operating hours increase.

It is important to mention that, very often, corrective action is taken but the problem persists. The key is in addressing the root cause of the identified problem

Big picture 

It is not enough to focus on reacting to the individual oil sample result, even though this contributes immensely to overall cost savings. The big picture principle must be applied on an on-going basis, where the maintenance engineer or manager applies a strategic approach. 

This entails examining the overall context, trending results month-by-month, year-by-year and looking at long-term outcomes and indicators, prioritising critical issues and focusing on solutions to identify fleet or plant problems, adaptability and sustainability.

Key questions

Some of the key questions are:

• Is this problem affecting this component only or the entire fleet or plant?
• Is it affecting a specific make and model of plant? 
• Is it affecting how a plant operates in a specific operating environment?
• Is it affected by changes in load or intensity of operation?
• Is it affecting equipment operated by a specific operator?
• Are our operational systems adaptable enough or responsive to current needs or indicators?

WearCheck can assist customers in managing and optimising their oil analysis programmes through comprehensive KPI reports that distil key data such as severity trends, repeat problems, component or fleet-level problem patterns and data-quality issues into clear, actionable insights that assist with reliability improvement and root cause analysis. 

What cost savings are NOT!

In a recent study, we examined a year’s worth of oil analysis data across all components on a mobile plant from engines, transmissions, hydraulic systems and axles for a company within the manufacturing industry. The findings were as follows:

• 46% of the annual oil samples extracted were alarms (Ratio almost 1:2). 
• 28% of the total annual problems or alarms are repeat issues.
• 1 in every 3 alarms represented a repeat problem. 

Thus, one in every two oil sample results is an alarm and the total alarms figure is 27% above the set target for the year.  The percentage of repeat problems is significant, meaning repeat problems are the key driver of the accumulated annual alarms/overall problematic oil samples. These figures are exorbitant and the scenario can be described as too costly and un-economical.

Slow response

A repeat problem is a pointer to a slow response-rate to alarms, or that the corrective action implemented did not address the root cause of the problem. Alternatively, it is simply indicative of the absence of corrective action. We decided to test this assertion further by examining the level of feedback, and findings were as follows:

Percentage feedback for the year was 28%. 

Average feedback days for cases where feedback was submitted: 186 days, some of the reports needing feedback were running nto day 300 without any response.

No feedback

Interpretation: only 28% of alarms had feedback submitted and it took 186 days to submit the feedback, with some cases going into 300 days with no feedback, indicating a poor responsiveness to alarms.

Given the findings above, it can be argued that with a feedback level of 28%, a greater percentage of alarms went unresolved, resulting in fault repeats and lost potential cost savings. Identified problems continued to recur, exposing the fleet to the risk of catastrophic failure – a situation which would negatively impact productivity. This is indicative of a “snowball effect”.

Snowball effect

A snowball rolling down a slope will pick up more snow on its way, thereby growing bigger in size and gaining more momentum, to the point that one may not even be able to stop it. By the same token, a regular study of oil analysis data over two decades has revealed that small, identified problems – if not resolved early – will grow into much larger and more complex challenges over time. The identified problem keeps repeating and getting worse, in most cases to the point of component failure. 

Therefore, we have seen that the longer a client waits or procrastinates in addressing a problem, the higher the likelihood that it may not even be addressed, exposing plant to the risk of component failure, expensive repair costs and lost production.

Correlation

In the study, we raised further questions to determine if there was a correlation between low feedback levels, fault repeats, component failures, and component changes, among other factors. We discovered that there was a link between component changes of oil-wetted components and oil analysis fault repeats. 

The components that were being repaired had a history of repeated contamination and wear problems. There was also a common pattern noticeable with the third consecutive occurrence of a fault (three counts of a fault repeat). Three out of four components with fault repeats either went through a parts change on the third consecutive occurrence or a complete component change.  

Common phenomenon

This was the case in areas of high intensity of operation. In areas of low intensity of operation, repeated parts changes were a common phenomenon. Below is a trend for Fleet D01 Transmission showing movement from “Normal” severity status to “Borderline” in month three, then further deterioration in months four and five, with resultant component failure three months after the water-contamination problem was discovered:

This is true to the key phrase “Oil analysis helps the most if you pick up a problem and address it at its onset.” We also noticed that this phenomenon of excessive fault repeats was synonymous with over-expenditure. The phrase “We have overshot our budget” was common during feedback sessions

Reaping the benefits

Undoubtedly, the above scenario provides a compelling case for every organisation that has decided to embark on an oil analysis programme to put in place and relentlessly enforce systems that enhance effectiveness and efficiency, guided by the vision to achieve cost savings. 

Poor responsiveness to oil analysis reports creates a huge opportunity cost, as every alarm presents an opportunity to save. It therefore follows that, if an organisation is to reap the benefits of investing in an oil analysis programme, a sound corrective-action strategy must be at the heart of the maintenance system.