World-class condition monitoring of hydraulic systems involves the successful integration of a number of strategic elements. While in the past, walk-around inspections and gage data were the primary means of monitoring system health, today’s modem oil analysis programs apply a host of sophisticated new tools and instruments. Reliability teams at the plant site frequently commission small laboratories. In many cases the instrumentation suite includes portable and unattended sensors. The situational context is changing too as today’s hydraulic systems are increasingly designed for higher pressures, speeds, and temperatures. This paper presents a review of strategic elements that, when well conceived and implemented, can deliver vital aiding information for achieving even the toughest condition-based maintenance goals. These include the selection of test slate, deployment of incipient failure advisories, setting of targets and limits that define nonconforming conditions, exception testing, and proactive maintenance.

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Analysis of hydraulic fluids, if done properly, can suggest maintenance procedures to improve hydraulic equipment reliability and extend system life. Significant cost savings can result. Where to take a sample There are two types of fluid sampling: static and dynamic. Static sampling involves extracting a fluid sample from a reservoir or a dead zone, where there is slight fluid movement. Little useful information is gained from static sampling because: • contaminant concentration gradients exist within static fluids. Water and particles tend to segregate and settle due to gravity. Therefore, samples taken from different sections within the static container yield completely different results, and • particles from reservoirs may describe system histories, but provide little information on what is happening now. Large reservoir volumes dampen out dynamic changes and conditions within the system.

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Most often, users associate an oil analysis program with a systematic early alert to oil or machine failure, i.e., damage control. While these benefits are helpful and frequently achieved, they should be regarded as low on the scale of importance compared to the more rewarding objective of failure avoidance.

Whenever a proactive maintenance strategy is applied, three steps are necessary to insure that its benefits are achieved. Since proactive maintenance, by involves continuous monitoring and controlling of machine failure root cam:es, the first step is simply to set a target, or standard, associated with each root cause.

In oil analysis, root causes of greatest importance relate to fluid contamination (particles, moisture, heat, coolant, etc.) and additive degradation. However, the process of defining precise and challenging targets (e.g., high cleanliness) is only the first step. Control of the fluid’s conditions within these targets must then be achieved and sustained. This is the second step and often includes an audit of how fluids become contaminated and then systematically eliminating these entry points. Often better filtration and the use of separators are required.

The third step is the vital action element of providing the feedback loop of an oil analysis program. When exceptions occur (e.g., over target results) remedial actions can then be immediately commissioned. Using the proactive maintenance strategy, contamination control becomes a disciplined activity of monitoring and controlling high fluid cleanliness, not a crude activity of trending dirt levels.

Finally, when the life extension benefits of proactive maintenance are flanked by the early warning benefits of predictive maintenance, a comprehensive condition-based maintenance program results. While proactive maintenance stresses root cause control, predictive maintenance targets the detection of incipient failure of both the fluid’s properties and machine components like bearings and gears. Following the oil sampling procedures, selection of appropriate sample testing procedures, and interpretation of test results outlined in this section, immediate corrective action can then be directed to effectively avoid failure chain reactions and further self destruction.

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A few years ago, someone mentioned to me that many of his machines were not good candidates for oil analysis because they used little oil that wasn’t worth saving. He added that by the time you flushed the sampling port and pulled a proper oil sample, you’ve almost done an oil change. Why bother with oil analysis?

I’m sure you recognize the misguided purpose of oil analysis in the mind of this individual. While oil analysis can certainly aid in better timed oil changes, it has so much more to offer. In fact, for machines that are mission-critical, the cost of changing the oil is small potatoes in comparison to the value gained from averting a catastrophic machine failure.

If oil analysis was only about tracking the remaining useful life of the lubricant, only a fraction of the oil samples analyzed every year could be economically justified.

Think of the oil more as an information messenger of numerous failure modes and root causes of failure. As I’ve said many times, it’s hard for a machine to be in trouble without the oil knowing about it first. For most labs, the number of non-conforming samples from oil analysis will generally exceed 20 percent.

In other words, more than one out of every five samples has a reportable condition that requires a corrective response. For this reason, you must be prudent about which machines are selected for oil analysis as well as the sampling frequency.

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I recently received an e-mail from a colleague seeking my opinion about a specific sampling philosophy. Referring to mobile equipment such as excavators, scrapers and dozers, he asked if good oil sampling depended much on sampling location.

He wondered, as he had often heard from others, if what truly matters most is sampling consistently, regardless of location.

Sampling consistently refers to the practice of meticulously following a prescribed procedure without regard to the accuracy or precision of the procedure. This is the way most oil samples, perhaps 80 percent, are taken today.

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Proper oil sampling is critical to an effective oil analysis program. Without a representative lube sample, oil analysis cannot be used effectively to monitor oil condition, predict machine failures or help you extend asset life. Whether you are using a test kit from service supplier or your own equipment, getting a few key details right when you take oil samples will give you more accurate, consistent and useful data.

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Many have read the well-documented case studies that convincingly demonstrate the practice of used oil analysis as a sound approach to reduce maintenance and downtime costs. However, for most users, these rewards have evaded their best efforts due to common implementation errors. Like many pursuits in life, there is often a very fine line that marks the division between success and failure. Success in the analysis of lubricating oils seems to consist of a series of such fine lines that must be carefully navigated.

This booklet draws on many years of experience in working with successful users. Its goal is to define a well-marked pathway to insure the success of new users, while at the same time, help existing users out of the slippery pitfalls they may have encountered. This will be accomplished by first identifying the ten most common reasons why oil analysis programs fail and then transitioning them into durable strategies that effectively overcome them.

It will be shown that these strategies depend much more on excellence in execution than the sophistication of underlying technologies. The guiding principle is the condition-based maintenance philosophy due to its penetrating sensitivity to both the causes and effects of failure. The familiar approaches of proactive maintenance (failure root-cause monitoring) and predictive maintenance (failure symptom monitoring) fall under the broad category of condition-based maintenance.

The practical wisdom of oil analysis pundits worldwide teach us that the most successful programs are those that are thoughtfully designed after careful need evaluation with mission and goals well defined. The emphasis is on designing quality and excellence in the beginning, not force-fitting it in along the way (see Figure 1 ). The many strategies and subsidiary tactics described herein are designed to help users achieve this as efficiently and effectively as possible.

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The term “oil analysis” has been used with respect to lubrication and machine reliability since the 19th century. Yet, over the years I have seen only a few attempts to assign a specific definition to the activity despite its widespread application in industry. Most of these definitions are too narrow or fail to include important integral activities such as machine wear monitoring and fault detection.

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By some estimates, condition monitoring has been around for more than a century, but it is only within the last 5-10 years (and particularly the last 2 or 3) that interest has been at fever pitch. Dozens, perhaps hundreds, of companies are involved in manufacturing or selling services or equipment for lubricant analysis, wear metals analysis, and vibration analysis, any and all of which can be part of a condition monitoring program. Within the realm of oil analysis itself are many types of tests that can be performed and many instruments that can be used to measure factors of interest. What distinguishes condition monitoring from other uses of oil analysis is not so much the specific techniques used as it is the repeated performance of testing and (most important) the tracking and trending of the results to determine changes in the health of an equipment-lube system over time. Using this information, the practitioner can take proactive measures to avert damage and downtime, saving money, time, and resources.

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We’ve addressed the virtues of training numerous times on the pages of Machinery Lubrication and other Noria publications. Still today, we encounter a national workforce in the lubrication field that seems largely oblivious to many of the fundamental concepts that embody excellence in the profession.

We are not sure if it is due to them not knowing what they don’t know, or not caring about what they don’t know. To become aware of what you don’t know requires becoming aware of your incompetencies and leaving the comfort of ignorance.

This editorial column seeks to define a minimum threshold of knowledge and awareness to qualify a person to work in the field rather than addressing the broader topics of educating a lubrication workforce.

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