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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For most plants, condition monitoring consists of multiple technologies that are cobbled together in an attempt to enhance machine reliability. Clearly, these efforts are founded in good intentions, and many such programs enjoy considerable success. Still others languish due to a lack of symmetry and central focus. Money is spent and efforts expended, but results are too often disappointing.

Condition monitoring requires a proper foundation from understanding and aligning criticality and failure mode analysis. Alignment greatly helps to optimize deployment of activities and spending to minimize waste and redundancy. Alignment also keeps the maintenance and reliability professionals on the same page by providing a clear understanding of what’s being done and why.

This column is Part 3 on this topic. In Part 1 “A New Look at Criticality Analysis for Machinery Lubrication”, I discussed the concept of Overall Machine Criticality (OMC) and its importance on a wide range of decisions relating to machinery lubrication and oil analysis. When optimized, these decisions define the Optimum Reference State (ORS) needed to achieve the desired level of machine reliability. It is intuitively obvious that smart maintenance decisions require a heightened sense of both the probability and consequences of machine failure.

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The sheer number of infographics in the condition monitoring field is staggering; they show up on social media, and in conference presentations, whitepapers, websites and books. Infographics are effective at helping people comprehend difficult concepts that integrate an array of variables and factors.

My soon-to-be-published book, “Inspection 2.0,” covers a host of different condition monitoring methods, including sensory inspections. I was looking for an infographic to illustrate failure modes and detection methods in the time domain for different types of machines and applications but was unable to find a graphic that fit my needs.

Necessity is the mother of invention. Left without choices, I decided to construct my own graphic, naming it Condition Alarm Mapping (CAM). The final product is shown in the figures on the following pages. However, the number of variations and uses of the CAM graphic is extensive and goes far beyond the scope of this article. As an introduction, I can show and describe what it is, why it is needed, and how it is used.

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Condition monitoring should never be limited to a single technology or method. Instead, it should combine and integrate an optimum selection of purposeful tools and tasks. Condition monitoring can be largely technology based but can also be observation or inspection based.

Most machines share condition monitoring and inspection needs with many other types of equipment. This is because they have components and operating conditions in common, i.e., motors, bearings, seals, lubricants, couplings, etc. At the same time, their operating conditions and applications may demand unique inspection requirements. These influence failure modes and machine criticality.

As discussed in previous columns, inspection should be viewed with the same serious intent as other condition monitoring practices. In my opinion, a world-class inspection program should produce more “saves” than all other condition monitoring activities combined. It’s not an alternative to technology-based condition monitoring but rather a strategic and powerful companion.

The technologies of infrared thermography, analytical ferrography, vibration analysis, motor current and acoustic emission are generally used to detect active faults and abnormal wear. Conversely, a well-conceived inspection program should largely focus on root causes and incipient (very early stage) failure conditions. Detection of advanced wear and impending failure is secondary.

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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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The best maintenance techniques for mechanical machinery are condition-based techniques. Condition-based maintenance is maintenance prescribed by the real-time needs of the machine according to changes in specific operation conditions. These conditions fall into two categories.

The first set of conditions are those that present a risk to a machine’s health if allowed to persist. These are operating and environmental conditions that precede failure, i.e., root causes of failure. They are not failure symptoms, which is after the fact. Examples of root cause conditions are misalignment, lubricant contamination, and overheating. The activity of detecting and correcting root cause conditions is referred to as proactive maintenance. Its singular purpose is to extend a machine’s operating life.

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These days, reliability professionals are faced with diverse options related to technologies and methods to detect, troubleshoot and remediate problems. Figure 1 is a simple example of the available options to collect data and arrive at decisions regarding the health of machinery and machine components.

The logical starting point is always to carefully rank failure modes by both criticality and probability of occurrence. For more information on this topic, see my previous column titled “A New Look at Criticality Analysis for Machinery Lubrication.” This method is known as failure modes and effects analysis (FMEA), and has been extensively documented.

The failure mode ranking sets into motion the critical-path process in reaching optimized decisions related to condition monitoring followed by the prescribed response or remedy. This response should not simply be corrective but also incorporate proactive measures to prevent or restrict recurrence. The emphasis is on optimized decisions and actions.

It’s easy to go cheap (penny wise, pound foolish), but there also can be temptation at the other extreme (a state of reliability excess), often driven by fear of the unknown. The optimum reference state is an activity of seeking balanced decisions. After all, you are not trying to maximize reliability. There is no greater source to find this balance than knowledge and education.

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Condition monitoring can be easily performed by following a few simple principles. Among these principles include monitoring two sets of conditions:

1. The operating and environmental conditions that precede failure, and
2. Early-stage failure symptoms

Several models are presented that show the benefits of monitoring machine conditions, as well as the consequences of ignoring them. Also discussed is the integration of both proactive and predictive maintenance techniques to extend machine life.

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The majority of wear related failures occur as the direct result of particulate contamination. A recent article published in Lubrication Engineering magazine concludes that more than 82% of wear related losses are contaminant induced. And, the largest portion of this is abrasive wear; the direct result of particles wedged between rolling and sliding surfaces.

According to work done by SKF, bearings can have “infinite life” when the influence of particle contamination is eliminated. In some cases more than a 75-times life extension can be achieved by maintaining exceedingly clean lubricating fluids. It is also worth noting that the penalty associated with a contaminated lubricant is identical to that of using a lubricant with just 25% of the recommended viscosity.

There are few forms of internal machine failure that don’t release particles into the lubricant; detecting increases in particle contamination can be extremely important. Figure 1 lists some of the failure types detectable using contaminant monitoring.

As a predictive maintenance technique, abnormal particle trends are the early symptoms of several non-particle induced conditions. Once the abnormal trends are recognized, a more precise assessment of lubricant condition or machine malfunction can be pursued.

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Catastrophic machinery failure in most cases can be avoided if the early symptoms are detected and appropriate action is taken. This is the essence of new condition monitoring technology which, if well conceived, can extend machine and component lives by as much as an order of magnitude. This paper discusses current condition monitoring methods including available sensor technology. Applications and rationale are also discussed.

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The field of maintenance technology going through a revolution of change. Gone are the t days when a machine had a predictable service life, after which it was replaced, continuing the cycle. Today, machinery and equipment can be maintained to achieve useful operating lives many times that attainable just a few years ago.

In the past, the popular practice of predictive maintenance and condition monitoring to combat rising maintenance costs. In the 1990s, we implement predictive maintenance with greater confidence and precision. These early warnings have proven effective at reducing the magnitude of failure and amount of unscheduled downtime; however, no real progress has been made in reducing frequency. Any maintenance strategy targeting the reduction of failure frequency must address the fundamental causes of failure. Such a strategy of eliminating causes would be “proactive” to failure, not “reactive” to failure.

This approach, known as proactive maintenance, is a promising wave of new maintenance technology. Its fundamental and logical approach seeks to make major inroads into the cost-driven maintenance industry this decade.

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The field of maintenance technology is going through a revolution of change. Gone are the days when a machine had a predictable service life, after which it was replaced, continuing the cycle. Today machinery and equipment can be maintained to achieve useful operating lives many times that attainable just a few years ago. It is no longer a truism that all machines are built to fail. Why? Because there is an increasing understanding of the causes of failure, and, armed with this information, it is possible to prevent the initiation of failure proactively. The field of proactive maintenance targets this very objective.

When maintenance is performed in response to failure it is called breakdown maintenance. When maintenance is performed according to a schedule it is called preventive maintenance. When maintenance is performed in response to a detected impending failure it is called predictive maintenance. When maintenance is performed in response to detected conditions that avoid the onset of failure (by correcting the conditions) it is called proactive maintenance.

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