Use Meaningful Oil-Analysis Alarm Limits

Sampling practices and lab communication play major roles in determining the reliability of your alarm limits.

By David M. Gawelek, CLS, Eurofins TestOil 

An oil-analysis report contains a lot of data. Most are composed of 4 to 7 tests and include 20 to 40 different measurements. Each of these measurements has a limit or limits (upper and/or lower bound) that indicate when a measured value has deviated from an expected value so much that the deviation is evidence of a potential failure. Additionally, each of those measurements may have its alarm limit(s) set using different methodologies based on the test method, specific lubricant product in use, the type of equipment in use, or even the specific equipment model in use, among other factors. Furthermore, each measurement typically has two levels of alarm; the terminology varies by lab. Our approach uses “Marginal” (synonymously yellow or caution) for the initial level and “Critical” (synonymously red or alert) for the second, more “important” level.

Despite the granularity involved in determining alarm limits, the data in an oil-analysis report is often most meaningful, and sometimes only meaningful, when considering other variables within the operating context of the equipment being monitored. This contextual information, when considered along with condition-monitoring data, is often the missing piece and, in fact, the cornerstone of a successful condition-monitoring program.

What a Lab Knows

A commercial lab has trained analysts who review oil-analysis data in reports and write recommendations based on data that is in alarm, or outside of the alarm limits. These analysts understand the nuances of laboratory test methods, the alarm limits for those tests and how they are determined, how some test data correlates to other test data, characteristics of different lubricant types/chemistries, lubrication-related failure modes, industrial equipment applications, and lubrication requirements.
These are some of the underlying competencies of an analyst who reviews your oil-analysis report. Their knowledge is wide and deep, but it can only be applied within the context of the data on the report.

Ideally, this data has been collected consistently over time and trends have been established. Sometimes this is not the case. Note that a single oil-analysis report is a snapshot in time and does not indicate trends and rates of change. Also note that there are many operational variables involved in lab test data. Without an understanding of these variables, even the best-trained and most-experienced analyst will have only a partial picture with which to assess data and determine machine and lubricant condition.

What a Plant Knows

The plant staff charged with operating and maintaining assets possess the contextual information that make an oil-analysis report data meaningful. This information includes any activity performed on or related to the equipment that might affect its operation or the lubricant within it, including the samples drawn from it.

First and foremost, the plant team knows how and when samples are collected. The quality of lubricant samples and the consistency used to obtain them are the primary determinants of the resulting data reliability.

Second, lubricant top-offs, drains and fills, changes to the lubricant product in use, any mechanical maintenance, changes in operational cycles, and potential introduction of contaminants from nearby activity are contextual factors that can affect lubricant-analysis data.

Alarm Limit Methodologies

Broadly speaking, there are two types of alarm limits: static and dynamic. Static alarm limits do not change in value and are based on fixed characteristics. They are often specified by OEM requirements and industry governing bodies. Most commercial labs can implement custom static limits according to customer request and can provide guidance to that end. Among common tests found in routine oil-analysis test slates, static limits are employed for viscosity, particle count, and water concentration. 

Some common modern viscosity standards are the ISO (International Standards Organization) 3448 standard for industrial lubricants, and SAE (Society of Automotive Engineers) J300 for crankcase (engine) oils, and SAE J306 for gear oils (all measured in centistokes, or cSt). These standards classify lubricants into “grades,” each of which encompasses a range of viscosities around a midpoint. The ISO standard is +/-10% from that midpoint. Often an OEM will require an ISO-grade lubricant, for example ISO 32. In this case, the acceptable viscosity range for a lubricant in this system is 32 +/-3.2, or 28.8 to 35.2. Therefore, the static alarm limits are 35.21 (upper bound) and 28.79 (lower bound). These are the marginal alarm limits.

Critical alarm limits are most commonly +/- 20% from the midpoint, or 38.41 (upper bound) and 25.59 (lower bound). These static limits will not change based on trended data. The in-service fluid is either in or out of the OEM specification of ISO 32 grade. More information about the SAE and ISO standards is widely available.

Similarly, the alarm limits for the particle-count test depend on the specific equipment application, such as the component clearances and fluid pressure levels. Particle count is measured by the ISO 4406 Standard Cleanliness Code system, which is based on the number of particles within specified size ranges in 1 ml of fluid or oil. The ISO “code” n is 2^n = number of particles of that size per ml.

Based on OEM recommendations and accepted industry standards, there are target ISO cleanliness levels for various industrial equipment types and the limit is typically two codes above the target, one code to account for the test’s inherent uncertainty of +/- one code, and one more because the alarm should be set at the nearest gradation from the target. There is also significant information available regarding the ISO cleanliness codes and how to set targets.

Dynamic alarm limits, on the other hand, update with each sample submitted because they are set by algorithms that account for the trends established by historical data. These limits are ideal for measurements that are not necessarily unique to a lubricant product or equipment type, or that are known to change over time but do not necessarily indicate a potential failure unless there is a step change. Perhaps the most useful application of dynamic limits is in measuring wear metal rates over time.  

There are two factors to consider when using dynamic alarm limits:

There must be a data history to establish a trend and an acceptable delta. Static limits must be used for wear metals until a sufficient set of data has been collected—typically three to five samples. Also, the sample must be collected in a way that maximizes the signal to noise in the data (in other words, a sample that is representative of equipment operating conditions).

Dynamic limits are very sensitive to change. Communication between end user and lab is of utmost importance. If oil changes and other maintenance activities occur between scheduled samplings, and the lab is not notified and continues to trend the data, it is likely that the limits set will not correlate to the actual component wear rates of that asset. The limits will be set based on measurements that were acquired under different sets of conditions.

There are very different but complementary sets of knowledge between a commercial oil lab’s analyst team and a maintenance-and-reliability team. The alarm limits for laboratory tests are set using the best information that the lab has available but, because so many variables are at play with industrial equipment, without steady communication regarding equipment operation and conditions, even the most meticulously set alarm limits might fall short of catching potential failures. Ultimately, alarm limits don’t tell the whole story. Expertise is required. This is where a strong working relationship with a trusted lab is key. EP

David M. Gawelek, CLS, is Reliability Concierge Program Manager at Eurofins TestOil, Strongsville, OH (testoil.com).