"Do you have any technical documents that describe how to determine oil analysis frequency? I am being questioned why we test quarterly."

Determining oil analysis frequency is much more in-depth than people often realize. The Sample Frequency Generator below provides a systematic method to estimate the optimized sampling frequency, taking into account economic penalty of failure, fluid environment severity, machine age, oil age and the tightness of goal-based targets like contamination control.

To use the tool, select the best-fit default frequency in Step 1. Next, score the application-related factors identified in Step 2. Finally, multiply the best-fit default frequency by the lowest application score to arrive at the adjusted sampling interval.

Please note that Step 2 should be considered pseudo-quantitative, meaning that a number is selected representing your opinion. Because opinions vary, each machine type should be scored based on a group consensus. This approach has proven to be more effective with this type of tool.

Economic Penalty of Failure

As expected, the economic penalty of failure adjusts the factor according to the cost of failure. That is, it would double the sampling frequency if it were very low but would increase tenfold if it were high. The penalty of failure must consider the cost of downtime, the cost of repair or rebuild, the overall interruption to business and the impact on product quality or output where applicable.

Fluid Environment Severity

Fluid environment severity not only incorporates the opportunity for particulate, process chemical and moisture contamination but also takes into account the demands placed on the lubricant by the machine. This includes the pressure, speed and load, as well as the duty cycle. The greater the risk of lubricant damage, the more frequent the sampling should be.

Machine Age

Geriatrics has an impact on establishing sampling frequencies. Sampling frequencies must be modified according to the classic “bathtub” curve used to explain the probability of equipment failure. In general, component failure is most likely during break-in due to infant mortality and as a component reaches the end of its natural life. For this reason, sampling frequencies must be increased during these periods of higher failure probability, particularly when analysis results indicate impending machine mortality.

Oil Age

This geriatric rule also applies to the lubricant. Aside from the obvious new oil sample for baseline purposes, the lubricant needs a frequent recheck in the first 10 percent of its expected life to ensure that it is bedding in correctly. This is especially true when a new oil type or manufacturer is used. Notice how the adjustment factor is somewhat different between the age of the machine and the age of the oil. A lubricant is more likely to suffer a mid-life crisis than a machine when impacted by accidental ingress conditions and is thus less recoverable than a machine at that point.

Target Tightness

The final consideration is the tightness of any goal-based limits. For example, if a fluid cleanliness target of ISO 15/13/10 is set, and the average fluid cleanliness is normally around ISO 14/12/9, then this is considered tight. However, if it typically trends at ISO 11/9/6, then this is considered loose. Tight targets require more frequent sampling because the possibility of exceeding the target will occur more readily than targets that are relatively loose.