Archive | Condition Monitoring


4:28 pm
September 16, 2016
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Quick Return-on-Investment for IIoT Pilot Projects

This slide depicts the infrastructure needed for one of the case studies.(Source: Mitsubishi Electric)

This slide depicts the infrastructure needed for one of the case studies.(Source: Mitsubishi Electric)

As I’m putting together the upcoming Industrial Internet of Things column for October, it’s hard to deny the return-on-investment (ROI) numbers being released at industry conferences and user conferences. At a recent ARC Advisory conference in India, three new applications — from Mitsubishi and Schaeffler — demonstrated the robust ROI for three different industry examples: Continuous Process, hybrid and a discrete production line.

Here’s a quick rundown of these projects and below is a link to the presentation at ARC in India:

These applications include a sensing system, a device and entire production line being connected to a cloud-based system. The waste water case study presented details the return on investment (ROI) and overall costs for a new condition monitoring systems for gearboxes on a line of pumps at this Germany utility.

The results are staggering. Four months after installation of the CMS, the company identified a €3,300 savings for gearwheel defects that were detected. Also, the process avoided a gearbox overhaul and loss of service.

In the paper mill CMS application, the Mitsubishi HiTec Paper wanted to add 26 smartcheck vibration sensors to better monitor a cooling system for its four-story coated thermo-sensitive paper system. After installing the vibration sensor at cost of €25,500, the paper manufacturer reported a €10,500 ROI due to the avoidance of three failures, service-loss and machine damage.

>> Download the Mitsubishi Electric & Schaeffler Group Presentation 

1601Iot_logo>> For more IIoT coverage in maintenance and operations, click here! 


6:16 pm
May 3, 2016
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Predicting Maintenance at Hannover MESSE

One of the specialty areas set up at the Hannover MESSE show (April 25 to 29, Hannover, Germany) was called predictive maintenance. It was a rather mixed bag of equipment/brand-specific offerings and predictive maintenance “tools” for general use. Here’s what some of the exhibitors had to offer.–Gary L. Parr, editorial director

They weren’t in the actual predictive-maintenance area, but Azima DLI, Woburn, MA, was exhibiting their Trio C10 Series ruggedized 10-in. tablets. The tablets are vibration data collectors and diagnostic instruments. The CX10 is a diagnostic data collector/expert analyzer and the CA10 is a vibration data collector/field analyzer. They are loaded with the company’s ExpertAlert diagnostic software.

Festo, the pneumatics and automation company based in Hauppauge, NY, demonstrated a predictive software component for their systems that takes advantage of Internet of Things technology to monitor all aspects of the automation system.

Hydac Filter Systems, Bethlehem, PA, demonstrated a turnkey fluids condition monitoring unit that can be used in retrofit and new hydraulic applications. The unit uses an optical particle counter and a multi-parameter sensor that measures temperature, water content, conductivity, and dielectric constant.

Asseco Solutions AG, Karlsruhe, Germany, offered their Smart Connected Solutions software, which is a subscription-based service that helps companies map all of their service and maintenance processes. The software manages data from individual sensors to deployment planning and on-site maintenance and documentation. SCS can be linked, using standard interfaces, to a wide range of ERP solutions, in addition to supporting processes such as invoicing. (An English version of the site doesn’t appear to exist.)

Bruel & Kjaer Vibro, Darmstat, Germany, demonstrated their turnkey vibration monitoring system. The system can be used on any rotating machinery, consists of all necessary hardware and software, and is scalable from a single machine to an entire plant. They also offer installation service training.

Aventics Corp., Lexington, KY, was showing their sensors and software system for monitoring pneumatics. The Industry 4.0-ready system monitors all aspects of a pneumatic system, including shock absorbers, positioning, and speed. Software tracks and analyses data, providing reports of declining performance.


5:05 pm
April 14, 2016
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Video | Deep Dive on Condition Monitoring Services

Kory Chance, instrumentation and controls technician at the City of Ames, Iowa municipal power plant discusses some of the benefits in moving to a valve condition monitoring service from Emerson Process Management. Chance reveals the benefits of having an outside condition-monitoring service for such a small operation and be able to remove certain preventative maintenance routines.


7:09 pm
April 11, 2016
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IIoT Maturation Coming?

grant gerkeBy Grant Gerke, Contributing Editor

February’s inaugural “Industrial Internet of Things” (IIoT) column discussed how the massive move to more sensors and analytics in manufacturing isn’t just a passing fad: It’s transformative. How do companies implement a data strategy with current production systems in place?

Each company needs a starting point in the IIoT journey, but a fully realized data strategy is hard to wrap your arms around today—and was even harder in 2012. That’s when Southern Company, Atlanta, an energy producer and transmission line supplier, decided to tackle the problem. The company is a large energy player in the deep-South region, with 27,000 miles of transmission lines that run through Georgia, Florida, Alabama, and Mississippi, in addition to operating several natural-gas and generation assets.

In a recent manufacturing webinar, Elizabeth Bray, principal engineer at Southern Company, discussed some newly enacted pilot projects involving the corporation’s transmission businesses and the move toward condition-based monitoring for its transformers at more than 3,700 substations.

Before the recent pilot, Southern Company began to add sensors and monitoring capabilities to make a future business case for a centralized program. Southern Company uses the eDNA data historian and PRiSM modeling from Schneider Electric for its transformers. These tools allow operations and maintenance teams to organize data into easy-to-read charts on monitoring screens and identify rates of changes or current deviations for its assets.

One example of success in the recent pilot program alerted a maintenance engineer to capacitor issues with a particular transformer. The eDNA trend tool and PRiSM modeling allowed centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

The eDNA trend tool and PRiSM modeling allowed Southern’s centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

The eDNA trend tool and PRiSM modeling allowed Southern’s centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

This is a great example of software and platform analytic delivering on a large sensing development. In Maintenance Technology’s “Final Thought” column, guest columnist Rene G. Gonzalez noted that this type of trend is quite pervasive in the energy industry. As an example, he cited a typical refinery as increasing its number of sensors from 20,000 five years ago, to 100,000 today.   

Some industry observers, such as Joe Barkai, former VP of Research at IDC, Framingham, MA, are pushing for standardization of instrumentation and devices to reduce costs for manufacturers. According to Barkai, “There aren’t enough standards for the industrial IoT space, and the robust use of standards is critical to accelerate innovation and scalable IoT ecosystems.”

While Barkai is right, most enterprises need solutions now to visualize trapped machine and system data for maintenance teams. With the increasing number of mergers and acquisitions added to the mix, large manufacturers are now assimilating disparate platforms and control architectures to the current plant-production systems.

John Rinaldi, president of Real Time Automation, Pewaukee, WI, spells out specific problems for manufacturers using older controllers in a recent article, titled, “Mining Manufacturing Data | Leveraging Trapped Data for Results” (, Aug. 21 2015). “Many controllers,” he wrote, “do not have the software and hardware to communicate data to asset-management and information systems using current computing methods.”

Beside the exceptional computing power of the cloud, industrial networking is another huge component of IIoT. Rinaldi pointed to the advantages of intelligent network gateways, which can “extract information residing in PLCs and communicate data to maintenance-management or asset-management systems.” This allows disparate networks or systems to communicate and even perform math functions on process data and send email alarms to maintenance technicians on changes-of-states.

Operations and maintenance now can measure machine cycles, runtime, and other data to perform predictive maintenance without disrupting control architectures and plant performance. Also, a minimal capital investment solution holds water with management. MT

Grant Gerke is a business writer and content marketer in the manufacturing, power, and renewable-energy space. He has 15 years of experience covering the industrial and field-automation industries.


4:54 pm
December 1, 2014
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Speeding Up the Manufacturing Connection


Researchers say the Internet of Things may have its strongest influence on the manufacturing sector because of its heavy reliance on well-applied data. Getting up to speed is the challenge.

By Rick Carter, Executive Editor

Manufacturing can be like professional sports in the way it churns out statistics. In both cases, the better those stats are understood and applied, the better the outcome.

In manufacturing, precise data application means assets last longer, less energy is used and product quality rises, along with company profits. But while it has long been a mission of most manufacturing operations to apply data to these ends, a challenge to getting there has been having the ability to gather data accurately enough and regularly enough (often by hand, on paper) to make it useful. The Internet of Things (IoT) makes this much less of a challenge and more of a conscious business decision/strategy to buy, install and use IoT-enabled devices that do the gathering automatically. These devices can now overwhelm manufacturers with good production and maintenance data—on equipment temperature, alignment, vibration, energy usage, and a host of others—that, properly interpreted, can help take operations to new levels of efficiency.

In the next six to eight years, expect about 50 billion devices worldwide to be connected to the Internet, says IT solutions provider Cisco Systems, Inc. Of these, about one-fourth will be used by manufacturers. Similarly elevated numbers exist in many places on the Internet regarding anticipated purchases of IoT devices, the savings they’ll provide and the production they’ll stimulate. It’s clearly the coming thing.

But there are some growing pains. While it may be automatic for your young son or daughter to believe that smartphone ownership (one step toward IoT integration) is as natural as breathing, manufacturers are not so easily swayed. Though there seems little doubt that the manufacturing world is headed in this direction, research suggests business in general is doing so slowly. In a recent (Sept. 2014) finding from LNS Research, for example, 250 executives (from manufacturing and other sectors) were asked how the IoT was impacting their business, and nearly half—43%—said they “didn’t understand or know about” the IoT. About a fourth of the group also said they were pursuing IoT investments for various reasons, and the rest were in the middle, either “investigating” IoT or aware of it, but still unable to detect its impact.

To learn more precisely the extent to which the above attitudes do or do not exist in the world of industrial maintenance and reliability, Maintenance Technology prepared its own study on the Internet of Things, and distributed it to our subscriber base by email. Based on 299 qualified responses, it reveals the following highlights:

40% currently have at least one to 10 or more IoT-enabled solutions for maintenance, and have plans to buy more.

37% have no IoT-enabled solutions for maintenance in their operation, and their plans to purchase them are uncertain.

The most common IoT-enabled maintenance solution, used by almost half (49%) of those with such devices, is for remote temperature detection.

Among both users and non-users of IoT-enabled solutions, the majority (84%) say they believe such devices will have either a “moderate” or “strong” impact on industrial maintenance in the next five years.

What is the Internet of Things?

Following are two definitions. The first is a high-level view that addresses both the manufacturing impact of the IoT and its vast social impact that will come through devices that can help us control or monitor various aspects of our lives and homes. The second is more technical, and describes the IoT in terms familiar to those in the manufacturing environment. For the best interpretation of what the IoT is, keep both in mind.

“The Internet of Things is a growing network of everyday objects—from industrial machines to consumer goods—that can share information and complete tasks while you are busy with other activities, like work, sleep or exercise.”

SAS Institute, Inc., a North Carolina-based data-management software firm

“The Internet of Things is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure. IoT is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine communications (M2M) and covers a variety of protocols, domains and applications. The interconnection of these embedded devices (including smart objects) is expected to usher in automation in nearly all fields, while also enabling advanced applications like a Smart Grid.”



In this snapshot of IoT-enabled manufacturing, responses suggest a nearly even split among respondents who use IoT-enabled devices and those who don’t. By a slim majority, most (40%) of respondents are IoT-enabled, and have plans to invest in more. But more than a third (37%) do not currently have IoT-enabled devices and are uncertain about plans to invest in them. Among the remaining 23% who say they “don’t know” if they have IoT-enabled devices or not, such usage in their operations may be split along the same lines.


Are facility managers leading the charge on integrating IoT-enabled devices in manufacturing operations? The above responses suggest this possibility, but the fact that development of IoT-enabled building controls has a slight jump on that of maintenance devices may explain the strong showing for facility control solutions. For the same reason, the nearly-as-strong integration of remote monitoring solutions for temperature and vibration detection suggests especially rapid (current and, likely, ongoing) acceptance among maintenance pros for these particular devices.


As expected, IoT-enabled devices clearly simplify the job of gathering data for maintenance pros. A clear majority of survey respondents (83%) who have IoT-enabled devices say they’ve made their jobs either “significantly” or “somewhat” easier. The devices also have a perfect record in this survey for not making anyone’s day more difficult.


These responses indicate that IoT are also generally easy to master. Most (80%) who have them rate learning how to use them “somewhat easy” or “easy.” Another 20%, however, rate the learning process “somewhat difficult” or just plain “difficult.”


Training, or the lack thereof, may be the reason for the levels of difficulty reflected in the percentages shown in Chart 4. Less than half (48%) of respondents with IoT-enabled devices say they received specialized training in their use, while the remainder did not. With the wide range of available functionality and complexity in IoT-enabled devices, it’s evident that training should be included in the investment.


Future purchase plans for IoT-enabled equipment basically parallel current-ownership levels, but with more than a third (39%) who say they either have no plans to buy more IoT-enabled equipment in the next six months or don’t know what those plans are. The good news: Nearly two-thirds of those surveyed who currently own at least one IoT-enabled device will purchase another device of some type before mid-2015.


Whether a current user of IoT-enabled devices or not, most survey respondents (84%) believe that these types of devices will have a “moderate” or “strong” impact on manufacturing in the next five years. Regardless of individual company budgets, cultures or other concerns that might impact the spread of IoT-enabled devices within their own firms right now, respondents clearly see the growing use of such devices as inevitable. MT

Our Survey Respondents

An overview of those who took our survey, based on the top responses to questions about the type of operation where they work, their age and title:

  • 38% work in a process-manufacturing operation with fewer than 1000 employees
  • 55% are over age 55
  • The most common title among respondents is Maintenance Manager (28%), with Maintenance Team Leader (17%) and Plant Engineer (14%) in the next closest positions.


6:54 pm
September 28, 2014
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Detection Of Cooling-Water Intrusion Into Standby-Power Diesel Engines


This case study discusses pitfalls associated with the condition-monitoring of oil in a generator’s lubrication system.

By Randall Noon, P.E.

Diesel-engine generators, the stalwart mainstays of standby-power systems, offer several advantages: They efficiently provide electrical power, when needed, with the push of a button or automatically, perhaps, when under-voltage conditions in the grid trip their start relays. Also, the handling and storage of diesel fuel presents fewer safety concerns than gasoline or natural gas. And finally, an on-site storage tank full of diesel fuel offers more reassurance in a crisis than pipeline-supplied natural gas, which could be disrupted by an earthquake, flood or other extreme event.

Despite their robust natures and practical attributes, however, diesel-engine generators require certain levels of care and predictive/preventive maintenance—especially units that function in a standby capacity. Discovering in the middle of a power blackout that a site’s critical standby-power system won’t run is a high-stress headache no maintenance department needs. Allowing water to enter undetected and wreck havoc in these units’ lubrication systems is a sure way to induce that type of headache.

Cooling-water intrusion into the lubrication system often results from a faulty gasket around a cylinder head, a cracked cylinder liner, a warped head or uneven bolting of the cylinder head to the engine frame. In any case, water in the engine oil is undesirable. Such intrusion can have a significant impact on the unit’s ability to run: If enough moisture has entered the lubrication system, water carried by the oil may evaporate during the combustion cycle and leave dry spots that allow the piston and cylinder walls to make metal-to-metal contact. This usually results in damage to the cylinder, the liner and the engine. Continued operation of equipment with this condition will damage the unit and can lead to complete engine failure. With that in mind, consider the following example from the real world.

Uncovering the problem

In a routine test run of a standby 5000 KW, 16-cylinder diesel-engine generator unit, water was observed in a lubrication-oil sight glass. Subsequent investigation discovered a jacket-water leak in the 1-left cylinder.


During troubleshooting, the water jacket was pressurized to 11 psig, and water began running off the piston on the interior of the cylinder liner. The fuel injector was then removed and a bore scope employed to examine the internal area. As shown in Fig. 1, the liner was found to be leaking from a point about one inch below the piston-ring reversal area and filling the top of the piston. Subsequent examination indicated that the liner had cracked.

As with many units, the water jacket had an automatic refill feature. When the coolant level in the engine-water jacket drops, cooling water is automatically replaced in the standpipe by a level-control device. Given this arrangement, if a leak were to occur in the water jacket, any “missing” water would not be noticed. Consequently, attempting to determine when the liner crack started by checking for “missing” coolant was a dead end.

The coolant consisted of demineralized water with an added corrosion inhibitor: sodium nitrite. Since coolant leaking into the lubrication system would also carry with it sodium nitrite in solution, the presence of this corrosion inhibitor in the oil was used as a marker to indicate when cracking in the liner had sufficiently developed to allow coolant intrusion into the oil. The engine oil was regularly tested, and one of the tests looked for sodium content.


A review of oil-analysis reports showed that on the day of the engine test during which water was observed in the sight glass, the sodium content of the oil exceeded 15 parts per million (ppm)—which was the trending alert level. The sodium content of the oil versus time, as reported in oil analyses, was then plotted as shown in Fig. 2. Since the oil was sampled at quarterly intervals, the resulting plot appears choppy. The plot in Fig. 2 is further complicated by the fact that the oil had been changed several times during the period of the plot. Each oil change would, of course, knock the concentration of sodium back to zero. Despite this complication, interpretation of the plot in Fig. 2 suggests that leakage had likely begun two years earlier.

Since the concentration of the sodium nitrate in the jacket-cooling water and the sodium content in the oil were known, it was possible to estimate the amount of water that had crossed into the lubrication system. This was then compared to the amount of water that had layered out in the bottom of the lubrication reservoir and that remaining in solution in the oil.

When these evaluations were done, the estimate of water carryover through the liner crack matched the total amount of water that had both layered out and remained in solution. This finding further corroborated that the origin of the sodium was the jacket water—and not any other source. The use of the sodium concentration data depicted in Fig. 2 also allowed rough estimates of leakage rates when engine operating time and oil replacements were considered.

While a laboratory report for an oil sample taken prior to the engine-test run had indicated a sodium content of 18 ppm, it also indicated nil for water content. Water content for the previous six summary laboratory reports also indicated nil with respect to water content. These findings begged the question: If water had been leaking into the lubrication oil long before the test run, why didn’t the previous laboratory reports pick it up? Answer: Because the previous reports had indicated “nil” water, the significance of the sodium noted in previous reports was overlooked. To better understand this chain of events, keep in mind that water can be present in lubrication oil in one, two or three forms: 1) in solution; 2) in an emulsion; 3) as free water.

If not otherwise already saturated, oil is able to take a certain amount of water into solution. In this condition, it will look clear and cause minimal problems in lubricated equipment. If, however, oil has taken into solution all the water it can—i.e., when it is saturated—any excess moisture is held in suspension or emulsion. In this condition, it looks cloudy. If more water is added, the oil and water will separate into two layers. Because water is heavier than most lubricating oils, excess water will sink to the bottom. This is “free” water.

To get a sense of the amounts of water associated with these three forms of water, consider the following:

  • A saturation level of a mineral oil might be about 100 ppm, and the amount of water it can hold in emulsified form could be as much as 1000 ppm. Free water occurs when the concentration is greater than 1000 ppm.
  • Similarly, an ester-based hydraulic fluid could have a saturation level of more than 2000 ppm, and also might be able to hold as much as 5000 ppm in emulsified form. Water in excess of 5000 ppm would then form a free water layer under the oil.

Fig. 3. Representative Chart of Water Solubility in Oil (Source: “Factors Affecting Water Solubility in Oils,” by Senja Paasimaa, Application Manager, Vaisala, [])

The amount of water that can be taken into solution also depends on oil temperature (as shown by the graph in Fig. 3). Oil at a higher temperature generally can take more water into solution than oil at a lower temperature. (The lubrication oil in the referenced diesel-engine generator unit is maintained at a “ready to run” temperature no lower than 104 F and no higher than 185 F.)

In this case, the water content of the lubrication oil was checked using the “Crackle Test.” This procedure involves putting two drops of oil on a hot, flat surface (about 130 C) and documenting any bubbling or “crackling” (the sound a sample sometimes makes during this type of test). The size of the bubbles is then used to indicate the amount of water in the oil. For example:

  • If no change is observed in the two drops of oil on the hot surface, it can be concluded that no free or emulsified water is present.
  • If very small bubbles (about 0.5 mm in diameter) appear, then disappear, the water content can be estimated at 500 to 1000 ppm.
  • If bubbles of about 2 mm appear, move to the center of the hot plate, increase in size to 4 mm, then disappear, the water content can be estimated at 1000 to 2000 ppm.
  • If bubbles of about 2 to 3 mm appear, increase in size to 4 mm and the process repeats with possible violent bubbling and audible cracking (hence, the test’s name), the water content is more than 2000 ppm.
  • The following limitations to the Crackle Test, however, are crucial to the discussion of this case study:
  • The method is approximate and not considered quantitative. It simply provides a rough indication.
  • If the hot-plate temperature is above 130 C, the heat can induce rapid scintillation that may not be detected by the observer.
  • The method provides no information about the amount of water in solution in the oil.

Developing new best practices

Based on the limitations of the Crackle Test and the data in Fig. 3, it became clear to the site’s maintenance department that water content could “hide out” in solution within the oil of a generator’s lubrication system. This situation had gone undetected over time because oil samples were usually taken right after a test run, when the lubrication oil was still hot (higher temperature => more water in solution).

In short, to proactively detect engine-cooling-water intrusion into the lubrication oil system before it affects the readiness of this site’s standby-power equipment, the amount of oil in solution must be monitored along with the amount of sodium detected in the oil.

Furthermore, personnel now understand that before the standby unit’s lubrication oil is changed—or fresh oil is added—samples of the existing oil must be evaluated. This way, any increase in sodium or water in solution can be compared to where it left off the last time.

Randy Noon is a Root Cause Team Leader at Nebraska’s Cooper Nuclear Station. A Registered Professional Engineer, book author and frequent contributor to Maintenance Technology, he has been investigating failures for more than three decades. Contact him at


5:38 pm
August 28, 2014
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Are You A Psychologist, A Condition-Monitoring Analyst, Or Both?


The roles and responsibilities of today’s equipment-health-focused professionals go beyond collecting and analyzing data.
MT asked a condition-monitoring expert to tell us what the job descriptions don’t. 

By Jane Alexander, Managing Editor

Many colleges and universities require their students to take a basic psychology course. Most students wonder why. But according to Trent Phillips of LUDECA, Inc., a condition-monitoring (CM) analyst would be very likely to know why.

As the study of mental processes and behavior, psychology teaches the use of behavior and scientific methods to investigate questions and arrive at appropriate conclusions. Such tactics, says Phillips, are critical to anyone who aspires to be a successful analyst—including those in the field of equipment condition-monitoring.

Observe and listen 

A CM analyst must observe and listen to equipment, fellow employees and management, says Phillips. Information from these groups, considered with their actions, will often provide the answers the analyst seeks. Additionally, the CM analyst must review the facts (data) and weigh them against other information. “The wise CM analyst learns to distinguish between anecdotal evidence and facts,” notes Phillips. “And this process will determine the course of action the analyst must take.”

In Phillips’ opinion, convincing others of the unseen, unheard and dire consequences that are likely to occur if appropriate actions are not taken is arguably the greatest difficulty an analyst faces. “Failure to plan almost always results in a failure to succeed,” he explains. “This is absolutely true when it comes to conveying critical condition-monitoring information to maintenance, operations, production and management within a facility.”

But therein lies a problem: Each group will process information differently, demonstrate different behavior, have different priorities and different objectives. To address this problem, Phillips says, a CM analyst, must learn to communicate the required information differently to each group based upon their exhibited behavior, objectives and understanding. This requires careful planning and implementation to succeed.

How to influence

Although CM analysts are usually not empowered to implement the changes required to improve equipment health, Phillips says their role and responsibilities typically involve more than simply collecting data to detect, diagnose and confirm equipment-health conditions. “Proper data collection and analysis is only part of the battle a CM analyst will routinely face,” says Phillips. “Understanding how to influence those responsible for funding, implementing change, directing repairs and engineering resources to improve equipment health are also qualities of the most successful CM analysts.”

In addition to collecting data, Phillips says CM analysts must be able to:

  • Identify individuals and groups responsible for implementing changes that are required to maintain and improve equipment health and become their partner in reliability.
  • Understand the goals, motives and objectives of these individuals and groups.
  • Understand how to motivate these individuals and groups to provide the support required to improve equipment health and reliability.
  • Understand the knowledge level of each individual and group.
  • Present the information in a way that is meaningful, understandable and motivates others to take necessary action.

Work with others 

According to Phillips, the right attitude is often a major factor in the success of a CM analyst. He notes that “works well with others” and “has a high tolerance for rejection” are characteristics necessary for success in the role. “The CM analyst by definition must interact with others, because his or her efforts can only be brought to fruition by others,” he says. “Information is the deliverable supplied by the analyst. The way in which it is conveyed will determine the success of the individual, facility, corporation and reliability efforts.”

Phillips notes that as challenging as technology and interpretation of results can be, they are among the easiest hurdles a CM analyst faces. The most difficult part may be getting others to follow the recommendations needed to improve maintenance and reliability.

“The successful condition-monitoring analyst must have the unique ability to determine what is important, what motivates and what creates a reaction from those responsible for equipment maintenance and reliability,” says Phillips. “They must be prepared for constant rejection and be willing to keep advocating until the needed action is taken.” MT

Trent Phillips is the Condition Monitoring Manager of LUDECA, Inc., a leading provider of shaft alignment, vibration analysis and balancing equipment. He has worked for many years in creating and managing reliability programs and developing condition-monitoring technologies, and holds several certifications in the field. Contact him at

Work Environments and the Success of CM Analysts

How important is the management of expectations?

LUDECA’s Trent Phillips says work environment can have a major impact on the success of CM analysts. In a facility or business with a well–planned production and reliability process, employees know what is expected of them and the role they play in the organization’s success. “This type of atmosphere makes it much easier to be a successful CM analyst,” he explains. “But it’s the exception. Few analysts today work in such environments.”

Phillips has found that expectations placed on many of today’s analysts and channels of communication are not always clearly defined. Furthermore, since many facilities still operate in a reactive state, their actions are focused on getting through current production cycles, not on improving long-term reliability and plant capacity. These situations keep CM analysts on the hunt for ways to effectively advocate for the equipment they monitor; convince responsible plant personnel to take appropriate action(s) before unwanted consequences occur; and, ultimately, improve equipment reliability. It doesn’t have to be that way, he says.

A wise—and successful—CM analyst will reach out to others with an offering of service, suggests Phillips. “The analyst who makes it his or her job to help others be more successful will soon become an integral part of the organization,” he says. “Support is easier to obtain when others see the CM analyst as one who is committed to helping them succeed, improve maintenance and increase reliability.”