By Shesby Chabaya – head: operations, WearCheck Zimbabwe
The majority of organisations implementing oil analysis face the challenge of maximising operational cost savings against the pressure to achieve full production and enhancing shareholder value. Oil analysis provides a means to achieve the end goal – a positive payback and overall cost savings. However, this is not a given – an organisation may or may not achieve the intended benefits for several reasons, chief among them being failure to implement a sound corrective-action strategy.
Shesby Chabaya of WearCheck Zimbabwe. Supplied by WearCheck
This Technical Bulletin aims to investigate the reasons behind organisations’ inability to attain cost savings and also to provide information on how to optimise operational cost savings by being responsive to the outcomes of analysis reports or by taking remedial action. I will discuss the benefits and drawbacks of taking remedial action or not doing so, the Key Performance Indicators (KPIs) for tracking progress, as well as “What cost savings look like” and “What cost savings are not,” using data analysis outcomes and case studies.
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 all begins with regular and systematic oil sampling that generates data on an ongoing basis to enhance informed decision-making. The oil analysis or cost-savings cycle is iterative and can be detailed as follows:
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, and then corrective action that addresses the root cause of the problem is implemented, guided by the response time indicated by the laboratory. 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. The following KPIs can be utilised to track the effectiveness of corrective action taken or lack thereof:
*An alarm is a report expressing the need for corrective action. It is characterised by an urgent or critical report severity, a call to action in response to a problem identified, and reported by the oil test laboratory, WearCheck.
The big picture principle
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 ongoing 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.
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. These tailored reports form part of WearCheck’s management-support offering and are available as an optional service upon request.
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.
- One in every three alarms represented a repeat problem.
Interpretation: one in every two oil sample results is an alarm and the total alarm 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 uneconomical.
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 the findings were as follows:
The 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 into day 300 without any response.
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”.
Source: Supplied by WearCheck