Using Oil Analysis to Drive Key Lubrication Performance Indicators

Business thrives on performance metrics. For large corporations, share price, earnings per share and return on net assets are used by CEOs and investors alike to assess a company’s financial health.

At the plant level, production managers are accountable for their own performance metrics, like overall equipment effectiveness (OEE), equipment availability, gross production yield and overall product quality. At the safety office, it is common to post the number of days since the last lost production time accident - again, an important performance metric or key performance indicator (KPI).

Unfortunately, the same kinds of KPIs have not existed in the world of machinery lubrication. This can lead to some serious failures in recognizing the impact lubrication can play on equipment reliability and availability, particularly by those not directly involved in equipment maintenance. For example, during a recent visit to a large pulp mill, a critical hydraulic system was identified as a persistent leaker.

Figure 1. Synergy Between Safety,
Production and Reliability Goals

When I started asking questions about the severity of the leaks, the criticality of the system and recommending how the problem could be fixed, I was informed that despite constant feedback from the lubrication department, the decision had been made at a management level not to fix the leak, but rather continually add make-up oil at the rate of 10 barrels per months, or an average annual cost of $30,000, so that production would not be disrupted.

This $30,000 annual cost was accepted by production as the cost of doing business; an appealing decision if you’re a production manager given that the $30,000 comes from a maintenance budget, not a production budget! While it is important to be mindful that the company’s role is to produce saleable products not to perform maintenance, it needs to be recognized that there is a strong correlation between maintenance success and equipment availability, production yield and product quality - the three key components of the OEE metric.

Why do maintenance goals take a secondary role to the agendas of other departments, when these goals are, in fact, integral to their success? In the author’s opinion, it is because there are few clearly defined performance metrics for maintenance-related activities that are used on a regular basis.

For example, when was the last time you walked past the plant manager’s office and saw a trend for the plant’s overall fluid cleanliness with the statement “we have worked 102 days without exceeding our target cleanliness levels” right next to trends of production quotas and time since a lost time injury?

While this comment may seem asinine, safety, production and maintenance are symbiotically linked (Figure 1) and must all be considered if a company is to realize the corporate goal of producing as much quality product as possible, at the lowest cost, without compromising safety.

Redressing the Balance: OLE - a New Maintenance KPI

So how can we establish meaningful maintenance KPIs? In a recent article published in Machinery Lubrication magazine’s July-August 2002 issue,¹ Drew Troyer proposed a new metric, overall lubrication effectiveness (OLE) as a KPI for lubrication-related maintenance activities.

OLE is a global metric designed to evaluate the critical areas that can compromise an effective lubrication program. It is setup the same way as the OEE metric used by production, as the product of three compliance measurements:

1. Percentage compliance with lubrication- related preventive maintenance tasks (PC_lpm)

2. Percentage compliance with contamina- tion control targets (PC_cct), and

3. Percentage compliance with lubricant quality targets (PC_lqt).

The benefits of this simple formula are two-fold. First, by defining this metric as the product of three compliance measurements, failure in any one area will have a significant effect on the overall OLE rating, making it a more meaningful global metric. Secondly, by structuring OLE in an identical form to the OEE metric used by management and production to rate overall plant performance, it is more likely that this maintenance metric will be both understood and embraced by people outside the maintenance department.

The Role of Oil Analysis in Determining OLE

In order to accurately track OLE, it is necessary to carefully track all three performance criteria: lubricant condition, lubricant contamination and preventive maintenance (PM) completion ratios. While PM completion ratios are relatively straightforward to track using modern lube scheduling or CMMS software, monitoring compliance with lube condition and contamination control targets requires a carefully planned oil analysis program. This includes well-engineered test slates, appropriate alarms and limits and well-documented data.

In using oil analysis data as a KPI, it may at first be tempting to include out-of-condition wear debris alarms as an indicator in addition to fluid cleanliness and condition. However, because most if not all abnormal wear conditions are directly linked to lube condition, contamination or poorly executed PM tasks, these are by default accounted for in the OLE metric and should automatically decrease over time as PC_lpm, PC_lqt, PC_cct and OLE increase.

Oil Analysis Targets and Limits

If oil analysis data is going to be a meaningful KPI, it is vital for targeted alarms and limits to be set appropriately. While setting fairly loose limits may result in good compliance with lube condition and contamination targets and a subsequently high OLE, their meaning may diminish to such an extent that OLE becomes irrelevant as a KPI. It is important when setting targets not to consider where the plant is today - after all, it is likely that significant problems currently exist which need to be addressed - but rather what targets need to be set to achieve the plant’s stated reliability goals.

Setting target cleanliness and dryness limits are relatively straightforward. They can be determined by assigning a reliability penalty factor, based on factors such as safety, cost and length of downtime; cost of repair due to contamination related failures; and a contamination severity factor, used to determine the equipment’s sensitivity to contamination and any extenuating operating environmental factors related to contamination.^2,3 Lube quality targets are also fairly easy to set using industry-accepted values in conjunction with routine base-lining of new oils.

Once appropriate targets have been set, logging exception results becomes relatively straightforward given the availability of excellent commercial oil analysis software packages. However, simply flagging one sample result which exceeds a stated limit may result in an oversensitivity to both lube condition and contamination control indexes due to conditions unrelated to lubrication effectiveness, such as a poor quality or anomalous sample, a dirty sample bottle or lab error. For this reason, it may be more effective to use the strategy outlined in Figure 2.

Figure 2. Criteria for Noncompliance (Ref: Komatsu, KOWA)

In this approach, any three consecutive samples that exceed a cautionary limit, or any one sample above a critical limit triggers an exception condition, resulting in noncompliance.

Percent Compliance with PMs

Although oil analysis has no direct impact on compliance and completion of scheduled PM tasks, there is a direct correlation between certain PM tasks and oil analysis. One obvious example is oil sampling.

Taking regular, routine oil samples should be part of the scheduled PM task list, and as such, factors into the percent compliance with PMs. However, oil analysis also plays an indirect role with many other PM-related tasks that are driven by decisions tied to oil analysis and other predictive technologies. These include:

• On-condition oil changes

• Oil sweetening based on lube condition

• Filter changes based on the results of particle counting

• Scheduling off-line filtration based on particle counting

• Deployment of vacuum dehydration or centrifuge based on high water content

• Resampling based on an exception routine oil analysis test result

• Regreasing based on high-frequency vibra- tion analysis or ultrasonic detection

• Cooling system pressure testing based on evidence of a coolant leak

• Inspection of fuel injectors or fuel pump based on evidence of a fuel leak

• Inspection of air intake system based on elevated silicon or high soot loading

• Boroscope inspection based on evidence of active machine wear.

As such, the effectiveness of the plant oil analysis program contributes to both the number of prescribed PM tasks, and indirectly, the completion ratio.

Using OLE to Track Lubrication Cultural Change

Achieving sustainable change of an ailing lubrication program is an evolutionary process. Depending on current inadequacies, complete transformation can take anywhere from two to five years. According to an article by Drew Troyer published in Machinery Lubrication magazine’s November- December 2002 issue,⁴ no one singular event will create a lasting cultural change in any lubrication program, but rather a cohesive plan of linked smaller steps over a sustained period is required to create the desired culture shift.

OLE and its subcomponents are excellent metrics to mark significant events along the transformation pathway to lubrication excellence. Figure 3 illustrates a hypothetical plant and the impact of the required changes during the 36-month implementation phase of a lubrication excellence initiative and their effects on the PC_lpm, PC_lqt, PC_cct and OLE metrics.

While compliance with lubrication-related PMs, contamination control targets and lube quality targets fluctuates depending on the program’s phase, the overall trend of all three is upward. This is clearly illustrated in the Figure 3 OLE graph which charts OLE rather than each discrete variable. Despite the variability in PC_lpm, PC_lqt, PC_cct and OLE has the effect of smoothing out minor changes, giving a clearer overall picture of the program’s success. This is the principal value of global metrics like OLE.

The type of charting shown in Figure 3 is a vital part of cultural change. At face value, it offers the lubrication department some assurance that changes are having a positive effect. Perhaps more importantly however, it also offers management a simple means of verifying that their investment in the project is paying dividends, something that may have great significance during annual budget-crunching time.

Recipe for Lubrication Success

Over the years, I have seen many oil analysis and lubrication best practice programs head off track. When this happens, it is not uncommon for the plant to either blame the technology, or to simply state “we’re not ready for this,” and return to the status quo.

Achieving lubrication success is like running up hill. It takes a certain amount of effort and momentum to reach the top of the hill before you can begin running down the other side. More often than not, this lack of momentum can be directly attributed to the lack of an incentive or stated end-goal. This goal could be as simple as increasing the OLE from 40 percent to 80 percent over the next three years as illustrated in Figure 3.

In this case, the simple act of tracking a meaningful metric such as OLE, using simple oil analysis parameters may be all it takes to get the whole organization - maintenance, production and management - moving forward in a concerted and unified direction toward lubrication excellence.

References

1. Troyer, Drew. (2002, July-August). OLE! Rallying for a New Lubrication Performance Metric, Machinery Lubrication, pp. 4-9.
2. Williamson, Martin. (2001). How to Set Optimum Target Cleanliness Levels for Contamination Control Practicing Oil Analysis Conference Proceedings, pp. 6-10.
3. Duncanson, Marianne. (1999). Water contamination and Oil/Water Demulsibility Practicing Oil Analysis Conference Proceedings, pp. 171-175.
4. Troyer, Drew. (2002, November-December). The Pathway to Lubrication Excellence: Creating a Cultural Transformation, Machinery Lubrication, pp. 6-13.