Predictive Maintenance Guidebook - Azima DLIazimadli.com/wp-content/uploads/Special-Report-PdM... · Predictive Maintenance Guidebook | 2 How does PdM generate operational efficiencies?

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Predictive Maintenance GuidebookYour handbook on how to build an effective PdM program, from business case to technology innovations.

Special Report

How does PdM generate operational efficiencies? / p.2

8 Financial Reasons to Deploy PdM Technology / p.3

The Predictive Maintenance Quiz / p.16

Is Online Monitoring Right for You? / p. 24

Watch Your Assets from the Cloud / p.35

Predictive Maintenance Guidebook | 2

How does PdM generate operational efficiencies? Listen in on this exclusive conversation between Thomas Wilk, chief editor of Plant Services, and Burt Hurlock, CEO of Azima DLI.

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8 Financial Reasons to Deploy Predictive Maintenance Technologies | 3

8 Financial Reasons to Deploy Predictive Maintenance TechnologiesLeave time-based maintenance and reactive maintenance for the non-critical equipment

Maintaining equipment on a set schedule has long been an accepted practice for industrial facilities. If a plant can “fix it before it breaks,” precious uptime is preserved.

Is uptime ALL that matters? Is overhauling a machine just because the schedule says so the best use of your maintenance dollars and resources?

Today’s reliability experts say “no” to both of these questions.

A growing number of facilities are improving uptime and productivity while simultaneously reducing maintenance costs. They are doing this by moving away from the concept of preventative (time-based) maintenance in favor of predictive (just-in-time) maintenance.

By employing non-invasive technologies such as vibration analysis, oil analysis, and IR surveys, plants are able to determine what specific maintenance is needed and when it is needed. Pinpointing a specific worn part and replacing it before it fails or triggers broader damage is far less costly than overhauling an entire machine with no knowledge of what – if anything – is wrong with it.

Few maintenance professionals will dispute the benefits of predictive maintenance. After all, who wouldn’t want to know about a fault before it becomes critical, and who wouldn’t want to plan maintenance around what actually needs repair?

Moving to a predictive maintenance program, however, is not always easy to do. Getting management to approve the budget needed for routine, condition-based monitoring can be a tough sell.

Here are eight financial reasons your maintenance department can use to justify the move to management.

• Preventative Maintenance Creates Unnecessary Work• Unnecessary Maintenance Can Introduce Equipment Failures• Condition Monitoring Enables Better Maintenance Planning• Predictive Maintenance Helps Satisfy Agency Regulations • Labor is a Finite Resource• Knowing Which Equipment is Critical Drives Down Maintenance Costs• Monitoring & Analysis Improves Planned Outage Efficiency• Detecting Problems While Equipment is Under Warranty Saves Money

Reason #1: Preventative Maintenance Creates Unnecessary Work

Preventative maintenance may very well fix a problem before it happens, but it comes at a higher cost.

Plants performing time-based maintenance typically spend more in annual maintenance costs than those using predictive maintenance. Blindly overhauling equipment on a schedule means you are likely paying for unnecessary repairs on a healthy machine.

Heather DeJesus, director of technical services at Azima DLI (www.azimadli.com) and a certified vibration analyst, says the most common unnecessary repair is changing out components after so many hours of service.

“Plants will change out bearings that are in absolutely fine condition simply because they have been in use for a set period of time,” she says. “That is a waste of maintenance dollars and resources.”

DeJesus said she’s encountered customers that stop equipment and swap them with their spares just because the schedule says it is time to do so.


“It’s not necessarily a good idea to do this without justification,” she says. “You are tying up maintenance personnel and usually impacting production. Plus, an electric motor going through starts and stops induces a lot of electrical failures. Why run that risk without knowing whether the equipment actually needs to be taken out for maintenance?”

Time-based programs also see their costs rise when equipment problems arise in between scheduled overhauls.

“That’s when your time-based maintenance program turns into a reactive maintenance program,” says DeJesus. “Now you’re looking at even higher costs. You may need to pull maintenance personnel from another area, you may need to pay overtime or a premium for a vendor to make an emergency call, and you may need to expedite shipping on a part. There are countless ways the costs grow in this situation.”

DeJesus says the bottom line is that condition monitoring – whether outsourced or a hybrid – saves money.

“By avoiding the time-based PMs and doing work when PdM analysis tells them to, plants typically save 16 to 20 times the cost of the monitoring program itself,” she says.

Reason #2: Unnecessary Maintenance Can Introduce Equipment Failures

DeJesus, who spent time testing Naval helicopters and worked in the power and automotive industries prior to joining Azima DLI a decade ago, says it is common for failures to be introduced simply by doing maintenance.

“Any time you work on equipment you run the risk of introducing problems,” DeJesus says. “So, with a time-based program you may be sending a healthy motor out to be rebuilt just because the schedule says to do it. Then, it comes back with issues it didn’t have before you sent it. All kinds of things can happen. Just the vibration from it being transported can cause problems.”


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This means your plant is not only paying for unnecessary work on a healthy machine, but is also paying to repair problems resulting from that work.

“Why risk introducing problems if you don’t really need to be working on the equipment in the first place?” DeJesus asks. “There are technologies that can confirm when and where work is needed. Why not use them?”

In-house maintenance can also introduce problems, says Dan Hogan, a vibration and oil analyst at Azima DLI. Hogan’s background is primarily with mechanical drives and gearboxes, as well as electrohydromechanicals, or mechatronics.

Hogan says over lubrication, use of the wrong oil/grease, and improper belt tension are the most common mistakes that result in equipment issues.

“Over greasing bearings can have a detrimental effect on bearing life,” he says. “The wrong lube oil or grease can have similar outcomes. Loose or, more often, too much belt tension can cause rapid belt failure and chronic bearing failures.”

Reason #3: Condition Monitoring Enables Better Maintenance Planning

You still have PMs to do, but, by monitoring the condition of your equipment, you can schedule those PMs with more accuracy.

DeJesus points out that being armed with information about exactly what repairs are needed enables you to plan the work in the most cost effective manner. Plus, she says, if you also perform a criticality assessment of your equipment, you can ensure the machines that impact production the most are worked on first.


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Case study

“The bottom line is it saves money and a whole lot of stress and aggravation,” she says.

DeJesus cites one client with a large gearbox from a manufacturer in France. Getting parts for it from overseas could take as long as five to six weeks.

“We were picking up what looked like gear-tooth chatter in the vibration readings,” she explains. “Oil analysis verified the vibration findings based on particulate in the oil sample. We then looked back to our vibration data to pinpoint the exact gear that needed replacement.”

Because of this information, the replacement was able to be ordered early enough to have it on hand for the plant’s scheduled outage.

Bill Ruiz, another Azima DLI analyst, is a certified oil analyst and has 17 years of experience in infrared thermography. He says oil analysis is often used to confirm vibration findings, but can also stand on its own as a predictive technology.

“We know the importance of oil changes in our own automobiles, and we use mileage as the oil-change marker,” he explains. “Industry relies on oil analysis to determine the protection quality and remaining life of the oil. Particle count analysis tells us if the machine is clean. Metals in oil samples are indicators of component wear. With this information in hand, maintenance schedulers can plan ahead of future problems for repair or for corrective action before costly failures.”

Another technology, thermography, when done routinely can eliminate the guesswork with electrical repairs, Ruiz says.

“With routine inspections, a thermographer can quickly detect issues with most any electrical, mechanical, process equipment, piping and vessels, or any other problems,” says Ruiz. “It’s fast, noninvasive and safe. Most of the faults that are found in electrical inspections are loose wire connections, stress and tension on wire and connection, improperly sized equipment or components, and improperly installed equipment. IR will eliminate guesswork and accurately pinpoint problems, which can then generate work orders for repair.”


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Reason #4: Predictive Maintenance Helps Satisfy Agency Regulations

Besides improving uptime and the bottom line, predictive maintenance programs are proving their worth across verticals for other reasons.

Many industries are shifting to condition-based monitoring to comply with the rules and regulations of outside agencies.

“I see it being used for safety compliance in the oil and gas sector,” says DeJesus. “With new demands from the American Petroleum Institute and OSHA to prove system integrity, oil and gas companies are relying on PdM results to properly and effectively maintain their systems to meet these requirements.”

She says pharmaceutical manufacturers are also starting to embrace the predictive mindset relative to FDA requirements.

“Pharmaceutical manufacturers are finding that condition-based maintenance satisfies FDA requirements with respect to the integrity of their process equipment. They are able to meet these requirements by showing that they are addressing problems before they impact the process, instead of just doing time-based maintenance,” DeJesus says.

Reason #5: Labor is a Finite Resource

The truth is, most facilities are lucky to get their PMs done at all.

“The main bottleneck in most maintenance programs, besides the financial budget or bottom line, is the available labor time,” says Hogan. “Available labor is a finite resource. You can help to direct your labor most effectively by using multiple technologies, such as IR, vibration, and oil, to identify the faults, assess the severity, and predict the progression.”

Doing this, he says, arms the maintenance staff with the data they need to go after the assets that have the most impact on production.


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DeJesus says some of her customers close out preventative maintenance tickets based on the reports that come from the predictive technologies. This, she says, can help a heavily taxed maintenance staff keep focused on the areas in which they are really needed.

“One power plant had reduced its maintenance staff from 15 to three, so they only had time for necessary PMs,” she explains. “From a CMMS standpoint, it looked bad for them to have a backlog of time-based maintenance work that they just couldn’t get to. By deploying vibration analysis they proved they didn’t need to do the time-based PMs.”

Hogan says predictive technologies are also effective as an alternative to intrusive PMs, such as overhauls and rebuilds. For example, he says, oil analysis may allow you to increase oil change intervals by using data to flag the appropriate end of life. Vibration and IR allow you to monitor a rotating asset and, in a similar method, trend and track the change in mechanical condition to identify the best time for overhaul or rebuild.

DeJesus agrees, noting that often maintenance work requires quite a bit of labor, such as in the case of changing a bearing. Being able to extend the frequency of the work goes a long way in managing your resources.

“The labor to disassemble a motor and change out the bearing could be half a shift with multiple people or even a full shift,” says DeJesus. “If you rely on vibration and oil analysis for bearings, you can postpone changing out a bearing for a month or even a year, depending on how well the machine is cared for and the quality and care of the bearing. The same goes for motor current testing. Often the motor is pulled out and sent to a motor shop, and that’s not necessary. That’s even more expensive.”

Hogan says many companies are outsourcing their condition-based programs as fewer and fewer have dedicated in-house PdM employees. “Outsourcing this type of work is attractive given the lower upfront costs versus a full in-house program and staff,” he explains. “One of the biggest advantages a contracted program has is dynamic scale and controlled costs. A contracted, outsourced program has the flexibility to dynamically add and shrink the size or cost of programs, which can help keep costs within budget


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However, he says the most successful PdM programs recognize the value of condition-based monitoring and ensure their program provides “a full picture of their whole plant.”

DeJesus agrees that consistent, routine monitoring delivers the best results.

“A lot of customers want to know if they can get away with doing vibration twice a year on a machine that runs all the time,” she says. “Monthly monitoring is predominantly what we shoot for. We build a baseline to determine what’s normal for the machine. Based on what we see, we can pick up seasonal changes for outside machines. The more mature your program is, the more accurate it is.”

She recalls a paper mill that had an induction fan that constantly came out of balance due to dust buildup.

“A big unbalanced fan can be catastrophic,” DeJesus says. “From the routine vibration readings, it seemed to happen on a three-month cycle, so they now have a PM that says, ‘Verify vibration readings and clean fan blades.’ ”

Reason #6: Knowing Which Equipment Is Critical Drives Down Costs

Knowing the impact of each machine is the key to developing a PdM program that keeps your facility on-line.

A criticality analysis can help a facility prioritize its maintenance work and focus predictive technologies where they have the most impact. You will spend maintenance dollars more wisely and simultaneously increase the efficiency of your facility-- all of which drives down overall costs.

“You don’t paint every asset with the same paintbrush,” explains DeJesus. “You look at safety, production, and compliance. If you deem a machine very important to any of those areas, then it’s automatically a candidate for predictive maintenance.”


She said looking at the purpose of each machine is the key.

“Maybe a 25-hp machine doesn’t need to be monitored,” she says. “But a 25-hp machine running a giant compressor does. You really have to look beyond the machine itself and consider the domino effect from a failure of the machine.”

DeJesus says she often performs criticality assessments to help her customers determine whether a machine should be on a time-based or condition-based maintenance program.

She says a lot is taken into consideration to make the determination. For example, in some cases equipment uptime is tied to contractual obligations in which there are stiff penalties for failing to deliver on time. Others have strict environmental regulations that must be met to avoid being shut down and/or fined.

Hogan points out that redundancy makes a machine less critical. This, too, is a factor to be considered in the assessment.

“The power generation industry is the standard in this regard,” says Hogan. “Most plants double up or have redundant support-equipment assets on every function to ensure there’s aa


the composite Risk index and Why you should know What they can’t tell youBy BuRT HuRLOCK, AzImA DLI CEO

The Composite Risk Index (CRI Report) was developed to help our customers (with bigger problems than cost) see risk. The report uses machine health data to generate a score of site operating risk and to rank sites by that score. The CRI Report is automatically available to all Azima DLI multi-site customers, and by no coincidence it is the industry leaders among them that are most likely to use it. CRI Report users share some common traits. Leadership and line management tend to be aligned through clear command chains and communications channels. There’s a premium on high-quality information and a shared interest in the rapid adoption of best practices. Perhaps most interestingly we see organizational humility, an acknowledgment by line managers that they can’t always see what management needs to know, the same way battalion commanders can see the battlefield but not the front. The CRI Report is the first in a family of enterprise performance metrics Azima DLI will deliver to improve visibility of production site performance and expose more best practices sooner across the fleet.

always one available asset in case of an unknown or unplanned failure. Identification of critical assets requires evaluation and examination of the whole production process or the experience and knowledge of a site engineer to pinpoint these critical and important machines.”

All of this is taken into consideration when a Compound Risk Index (CRI) is determined for each machine, DeJesus says.

Reason #7: Monitoring & Analysis Improves Planned Outage Efficiency

When you have a scheduled outage approaching, information from your predictive technologies can help you determine which machines to pull for repair.

Repairing a machine that truly needs it at a time when there is no impact on production avoids the high cost of it failing when the plant is back online.

“It’s a common practice to use your PdM program to queue and schedule work based on the findings of vibration, oil, and IR prior to an outage,” says Hogan. “I just had a power customer request an expedited review of data collected to provide this ability for the


Why customers have the best ideas and the genesis of risk reportingWhen customers spend money we assume they need to justify the investment, and the inclination is to present measures of return-on-investment (ROI). The problem with ROIs is that they can be subjective and are too easily critiqued for being self-serving. They also defy standardization because some companies place more value on some variables than others, which means the same formula can produce very different pictures of return. Even audiences within the same customer differ on the relevance of performance measures.

When a long-standing customer told us we didn’t charge enough to merit an ROI calculation and he had larger problems than cost, he had our full attention. “Risk,” he said, “is my problem. I know it’s out there and I can’t see it. Can you show me risk?” It was a seminal moment in the evolution of our organization because (1) the request was modest and easily accommodated and (2) the relationship acquired a new dimension, becoming strategic, as well as economic. By focusing exclusively on the economic equation, we overlooked what the customer wanted and underestimated the value of available information he needed. Customers always have the best ideas because they frame the vendor’s role in the context of their needs faster than can the vendor. And what matters to one customer often matters to another, as we have found.

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Read about how Kimberly Clark Paper mill avoided

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program. An outage or shutdown is the best time to do the bulk of preventive work or work impossible to perform when a site is in production.”

Faults or problems identified over multiple testing intervals and trending toward an increasing severity are the prime candidates for repair during an outage, advises Hogan. Conditions severe enough to warrant immediate inspection or suspected conditions with unknown failure rates are also good candidates for outage repairs and work.

One thing to note, however, is that predictive technologies work best when employed over time. If you have never monitored a machine and then collect vibration from it once, you can diagnose current faults. However, not having a history of data to trend means you lack the ability to identify fault patterns and progression leading to early warnings of faults.

“Regular data collection on the needed interval is the best prescription for identifying machinery problems and fault progression,” says Hogan. “Annual screening or once-in-a-while monitoring isn’t the most effective use of the PdM toolbox.”


the disruptive power of visibilityTo speak of risk and presume to manage it feels, well, risky. While risk can be expressed numerically, it remains an abstraction, and risk scores rarely capture the full spectrum of risk factors. But, unlike ROIs, risk can be depicted, both in an absolute sense, subject to the limitations of the risk model, and, more importantly, in a relative sense. The power of the latter cannot be underestimated because it creates the context for performance relative to potential. If we agree on the risk factors and accept they can be measured, then it follows that Site A is more risky than Site B when more risk factors are present; and this is what our customer knew. Risk factors were present, and they needed to be quantified.

The highest risk sites never want to see their scores, especially relative to the balance of the fleet. The information is threatening even though it simplifies identifying and mitigating risks. Ironically, the managers who need it most tend to reject it while the ones who need it less embrace it, further reducing their risks. Visualizing relative risk and sharing it across the fleet will expose cultural strengths and weaknesses and will polarize the operating community. Continuous improvers will use it to improve performance and advance, while laggards will find it meddlesome. The disparity in performance and riskiness between adopters and laggards will widen.

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Knowing the outage schedule is also important.

“A nuclear plant, for example, will shut down every 18 months,” explains DeJesus. “When they have a planned outage, they’ll ask us what maintenance they should do during that time. We’ll use vibration as our heavy hitter, plus infrared, motor current analysis, and oil analysis. Sometimes problems manifest themselves in other technologies before we see them in vibration. You can see something in a motor current analysis long before you see it in a vibration reading. We might use oil analysis to verify what we’re picking up with vibration analysis.”

Reason #8: Detecting Problems While Equipment Is Under Warranty Saves Money

If something is broken, why not get it repaired while it is still under warranty?

It sounds simple, but in practice it is not always easy.

After an outage, an installer generally warranties his work for 30 to 60 days. With time-based maintenance, you likely would not notice a problem until it escalates. The time that takes could very well put you outside of the warranty.

With predictive technologies, you can quickly check equipment post-installation to check for signs of problems.

“We often perform testing right after an outage, machine overhaul, or the commissioning of a new asset,” DeJesus says. “When you put something back together you have the opportunity to make mistakes. Things being aligned or bolted down properly is very important. When you’re trying to get through an outage quickly, you might put a bearing in wrong, and it will show up immediately in a vibration reading.”

If the work was done by a third party and a problem is caught within 30 to 60 days, it is usually under warranty, she says. If the work was done in-house, you may need to review your installation processes and procedures to make sure they are not the cause of the problem.


Predictive technologies provide a clear picture of the asset before and after maintenance work or a repair.

“This documents the effectiveness, or lack of in some cases, and helps to identify any areas of improvement,” says Hogan. “It’s a common practice for most of my customers to want to document the effectiveness of a repair and confirm the work.”

Varied installation practices and protocols can introduce all sorts of headaches, much like a driver with a heavy foot or a knack for hitting potholes impacts a car, says Hogan.

“All these technologies can help identify faults with newly installed assets. A factory-tested machine may have passed its vibration compliance testing in the factory only to fail after it was installed improperly on the ground at a customer’s site,” he says. “The identification of these faults is important to the longevity and reliability of these machines. Vibration and IR are two excellent tools for this work.”

One of Hogan’s customers had an emissions control fan refurbishment during an outage. The fan was rebuilt with new bearings, coupling inserts, and a standard alignment and balance.

“During our routine vibration analysis a month after the work, the data showed the fan end had severe indications of bearing looseness and wear,” explains Hogan. “Our report was expedited due to the high severity of the condition and the customer was in disbelief, given they had just spent a large sum to fix these fans.”

The contractor was contacted and confirmed the condition. An operations problem was identified as the cause of the condition and corrected. The fan had to be rebuilt, balanced, and aligned again before going back into service.

“Our routine monitoring helped identify a failing fan, identify the faulty operations

procedures, and put corrective action in place to avoid failures in the future,” says Hogan.


The Predictive Maintenance Quiz – How does your program stack up? | 16

The predictive maintenance quizHow does your program stack up?

H ave you ever wondered how your predictive maintenance (PdM) program stacks up to others? Would you like to know how to improve? If you don’t already use PdM, are you

curious about how it could benefit you? If you answered yes to any of these questions, then you’re in the right place. Take our quick quiz, tally your results, and then read on to learn ways to help ensure your PdM program meets best practices.

Step 1: take the quiz1. RELIANCE OR COMPLIANCE? − Do you rely on your PdM program to improve uptime and drive down costs? (Yes = +5) − Is the ONLY reason for your PdM program to comply with a mandate? (Yes = +2)2. PRETENDING YOU’RE TRENDING? − Does your program trend machine conditions over time to maximize your maintenance effectiveness and efficiency? (Yes = +5) − Is your primary goal to identify machines with serious or critical issues? (Yes = +2)3. IS YOUR SKILL FOR REAL? − Does your staff have the technical field expertise to detect issues on ALL of your critical equipment? (Yes =+5) − Is your team trained on how to combine the results of vibration, infrared, oil, ultrasound, and motor testing to get to the root of a problem? (Yes = +5)4. ABORTING REPORTING? − Are regular reports being generated on equipment health, collection compliance, program performance metrics, and maintenance performed in response to recommendations? (Yes = +5) − Are reports generated only for machines identified with serious or critical problems? (Yes = +2)5. IS YOUR COST LOST? − Do you know the cost of your PdM program within 10% of total spend? (Yes = +5) − Do you have the necessary information to accurately calculate your PdM program’s ROI? (Yes = +5)

Step 2: tally your score25+ PointsCongratulations! You have a solid PdM program in place. Check the topics below for ideas on how to fine-tune and sustain your program.

18-24 PointsYou are on the path to a very successful PdM program. Read the topics below to find out where you can make further improvements.

10-17 PointsYou have the potential to get more from your PdM program than you are currently realizing. Review the topics below to identify areas where you can make improvements.

2-9 PointsCongratulations on having a PdM program in place – that’s an important first step, but it doesn’t end there. To be truly effective, it needs to meet more than the minimum standards. Use the information below to identify where your program can be strengthened.

Step 3: Step up your game

Reliance or Compliance?“Both mandated and chosen PdM programs can be equally successful or unsuccessful,” says Tim Kelley, Director of Watchman Services at Azima DLI (www.azimadli.com). “One approach is not necessarily better than the other.”

Programs that are internally mandated may experience slower adoption or internal resistance compared to those brought in by choice, and they may require more internal selling and education up front. On the other hand, having executive support increases its odds of sustainability, and tying plant managers' incentives to performance can enhance its degree of success.

Chosen programs benefit from champions who understand the value of PdM and are willing to put forth the effort to implement it. However, if your champion or other PdM talent retires or moves on, the program risks failure, particularly if the duties are handed off to someone lacking the time or interest to ensure continued success.


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“The perfect mesh is when a champion is invested in implementing a PdM program and the concept is sold to corporate. That’s the best of both worlds,” adds Kelley.

Regardless of how it originates, a program’s effectiveness depends on how it is implemented. Too often, companies collect condition data but fail to analyze or use it properly. Consequently, maintenance remains largely reactive and subject to firefighting, thus limiting the PdM program’s financial benefits. A best-practice PdM program predicts when it’s time to do maintenance so outages can be efficiently and proactively scheduled, and steps can be taken to ensure troubled machines keep running until the planned shutdown.

Pretending You’re Trending?If you are not trending your data, you are not alone. However, by focusing only on serious

or critical issues and not trending your condition data, you miss opportunities to optimize maintenance performance.

Visibility into the early progression of a fault allows you to properly plan ahead.“In the past, people had more familiarity with their machines. They were tuned in to how

the equipment should sound and operate, and had a better grasp on where to direct their attention,” explains Michael DeMaria, Director of Product Management at Azima DLI. “Now, personnel turnover and changing technology has increased the need for PdM.”

Capturing condition information regularly and tracking it over time allows work orders to be created and completed in time to avoid failure. As machine issues decline and firefighting wanes, there is more time to focus on lower priority opportunities, for instance design and operational performance.

Very often, companies lack the means or capabilities to trend data. Those responsible have additional duties and too little time to spare, or the data may not be centrally accessible. Asset management systems can be part of the problem.

“The goal of a CMMS or EAM system is to be a maintenance repository but their usefulness depends on the initial setups and often times data and asset information is incomplete,” says Kelley.

Another obstacle to trending is the choice of technology. For example, management may want a vibration program, but the cheapest technology – broadband meters – does not support trending. What is needed are narrow-band tools that enable you to see subtle nuances in machines as they start to develop or deteriorate. By finding such conditions early, you can plan downtime that caters to the repair, and only order the parts necessary. Once the repair is complete, you can assess its effectiveness and ensure no new problems were introduced because of it by comparing the machine’s post-repair state to a baseline.


Because some PdM is better than none, companies should tackle the easy wins first and quantify the savings over time. Tracking return on investment (ROI) information makes it easier to justify expanding the program to additional bad actors and machine types.

Is Your Skill for Real?The ability to run an effective PdM program with your current staff depends on workload

and availability, equipment expertise, and PdM skills. Getting up to speed requires a significant, albeit worthy, investment.

“The most successful programs always originate the hard way – following an expensive problem,” says DeMaria.

In companies that attempt in-house programs, PdM is usually a collateral duty rather than a dedicated role. If your staff is already spread too thin and struggling to complete preventive maintenance tasks, then PdM success is unlikely. There is also the risk of employee turnover. Latest trends show that every three to five years, personnel tend to change or leave jobs. If the expertise is lost, the program will have to start from scratch.

When PdM teams favor the machines most familiar to them and lack real-world experience with all of the critical machines in their plant, PdM success is constrained. It takes years to develop expertise on the various machines and component types.

Furthermore, the best programs leverage multiple PdM technologies such as vibration, infrared, oil, ultrasound, and motor testing. There is an art to gathering and aggregating the results from multiple sources and analyzing the data effectively. Vibration, for example, is not an exact science. There are subtle nuances in vibration readings, and brand new machines will respond differently than older equipment. Combining technologies can settle uncertainties. If a vibration technician suspects tooth chatter on a gearbox it can be verified by pulling an oil sample.


Effective PdM teams have:

•TimeavailabletoperformPdMactivities

•ExpertisewiththevariousPdMtechnologies

•Knowledgeofmultipleequipmentandmachinetypes

•Continuityofknowledgedespitepersonnelturnover

•Fundingtomaintainadequateskillsetsandcertifications

Developing the needed skills can be hit-or-miss. For instance, vibration classes use clean data to show what an imbalance looks like, but real-world scenarios may look very different. Or, you may hire a college graduate freshly certified in PdM, but he or she lacks hands-on machine experience, making it difficult for them to diagnose complex problems.

Outsourcing can be a cost-effective solution to the skills gap.“If I were a plant manager starting a vibration analysis program, I wouldn’t want my staff,

fresh from training, to test their knowledge on my most critical machines,” says DeMaria. “Does your analyst have enough experience to make a $1 million judgment call? Even the best analysts sometimes need a second opinion.”

Azima DLI developed software that performs PdM analysis and automatically trends each unique fault condition, using healthy machines as the baseline. A pump requires a different specific frequency range than an electric motor, for example, and certain frequencies come out of a machine naturally. Therefore proper database setup is crucial. Understanding how to capture and account for faults and naturally occurring frequencies can be tricky. External support from a PdM expert or an OEM can be helpful.

In the best outsourcing programs, plants retain the data collection routine while a third party performs analysis. PdM partners can also recommend upgrades to the overall program, for instance changing out certain bearing types, tweaking setups and alarms, or optimizing the EAM/CMMS software. By partnering together, the plant personnel can be the eyes and ears for the program locally and they also have the historical maintenance background of the machines. The PdM services provider can add value with their vibration expertise and also compare similar applications to help identify any maintenance, design or installation faults.

While PdM services from OEMs and local motor shops tend to be side work, Azima DLI’s core business model, capability, and investment centers on PdM options and continuous improvement. “We have many analysts who are well-qualified and experienced on all aspects of PdM and the various equipment being monitored, who can be called upon at any time for help,” says Clint Goodin, a Vibration Analyst at Azima DLI.

Aborting Reporting?Assess the reports that your PdM program generates. The time invested in reporting can

have a major impact on your overall uptime. If they clearly reveal the faults and how they are progressing, you can plan your actions in a timely, cost-effective manner.

If reports show serious or critical machine problems, but lack overall machine health trends, developing issues, repair recommendations or actions taken, then PdM efforts will be


ineffective. If your staff doesn’t have time to create the reports or they are not disseminated to the right people, then your PdM investment is wasted. If your reports don’t relay operational factors such as efficiency, uptime, and ROI, then you aren’t able to measure and communicate the PdM program’s performance.

Poorly designed reports are another concern.“If a report says ‘bad bearing,’ which bearing is it? If it reports ‘looseness,’ is that at the fan

or motor? Pinpoint the problem and give an actionable recommendation, and your PdM will be more efficient and effective,” recommends DeJesus.

For instance, if a trend of fan or pump misalignments are noted, consider retraining the technician on how to align machines. If similar machines all have the same problem, it could be a design problem, a bad bearing, the wrong bearing, or it’s installed incorrectly.

“Show the most critical issues at the front of the report so the users can avoid wasting time weeding through dozens of pages,” suggests Dan Hogan, a Vibration and Oil Analyst at Azima DLI. “Include pictures or mechanical schematics showing problem areas for less experienced field technicians. Talk with your report users about the contents and flow, and consider leveraging a PdM service provider to apply the requested improvements if in-house availability is limited. They know their audiences and can tailor a message without jargon.”

Azima DLI’s reports include a History Table that shows all monitored assets by name and their color-coded severity over a full year, giving management insight into reported condition trends and progress on the faults. They can determine how long it took for a fault to progress, determine whether an unreliable machine or process caused the problem, and judge whether the technicians are not acting quickly enough on corrections. If a catastrophic failure occurs, they can assess whether the condition was not found or the equipment was not monitored.

“It’s difficult to get people to read reports. Our clients can take our report and create work orders from it,” says Goodin.

Delivery format flexibility is also important. Azima DLI’s Watchman Reliability Portal provides the data online in a central repository, but it can also be emailed in a PDF file or physical copies can be printed. Azima DLI’s reports automatically tie in to the customer’s internal planning systems, without a separate import step; the data is visible in both systems concurrently.

Is Your Cost Lost?You should always know, within 10% of your budget, what your PdM program is costing

you. Likewise, it is essential to document and communicate how much ROI your program


is realizing and measure its performance against other plants and business units across the globe. A solid PdM program will enable you to track these figures easily and effectively.

Cost controls are a necessity. An in-house PdM program includes fully loaded costs for each team member plus the costs of the equipment, software, and perhaps some outside consulting services. Data collectors alone can cost as much as $40,000 each, and they need to be refreshed every three to five years with new, supported technology. Annual hardware and software support costs further inflate the budget, as do skills training, certification, and recertification costs.

Some or all of these costs can be assumed by a PdM service provider. Azima DLI’s full-service PdM, offered on a monthly subscription basis, is the most predictable for budgeting purposes. No capital investment is required and the agreements are fixed for three- to five-year terms. Companies with a larger resource pool and budget may instead purchase the hardware and software, perform the data collection, and leverage Azima DLI for analysis and to fill in when internal resources are unavailable. Be aware that some other providers will require change orders for out-of-scope services and charge for time and materials.

Any money invested in an effective PdM program will quickly be offset by maintenance cost savings. Your maintenance budget will decline by replacing scheduled PMs and run-to-failure conditions with work based on actual asset conditions.


PdM ROI potential is substantial:

•Replaceexcessivemaintenancewithcondition-basedmaintenance

•Avoidunscheduleddowntimebybetterplanningwork

•Avoidproductionlossesbypreventingemergencyshutdowns

•Reducesparepartsinventorybyreducingemergencyrepairs

•Reducelaborandovertimecostsbyavoidinglate-nightbreakdowns

•Recoverlostproductivitybyavoidingthedistractionofemergencies

•Reducelostbusinessandlate-deliverypenaltiesbyimprovingon-timeshipments

•Avoidunfinishedproductdisposalbypreventingbreakdownsmid-batchrun

•Avoidhazardousmaterialincinerationcostsbypreventingbreakdownsmid-batchrun

Senior management responds to ROI data. Did you pay $50,000 for a PdM technology that prevented a production shutdown that might have cost $200,000 per day? Did you replace bearings annually but now you can wait until signs of failure appear?

“If you do a good job at minimizing equipment failures and downtime, driving efficiencies and reducing costs, but fail to take adequate credit, management could easily defund the program or reduce the service frequency, assuming it’s not important anymore,” explains Kelley. “Within six months, all of the reliability gains will have been lost.”

ConclusionWe hope that taking this quiz, learning your score, and identifying opportunities for

improvement helps you to move closer toward best-practice PdM. Whether you repurpose your staff and processes, or bring in PdM partners for assistance, you can increase efficiency, lower your overall maintenance costs, and do more with what you have.

Remember, there is no need to outsource your PdM entirely – a hybrid approach where your staff’s strengths are maximized and supplemented with a strong partner is equally effective. Your staff is smart, they work hard, and you need them. Get them the help they need so that they can focus where you need them most.


Is an online monitoring system right for you? | 24

Is an online monitoring system right for you?What you should knoWby Sheila Kennedy, contributing editor, Plant Services magazine

The decision to implement an online condition monitoring system should not be made lightly. Both the pros and cons must be weighed, as well as the ultimate payoff potential.

Which machines are the best candidates? What advantages will be gained? Is it worth the costs? What is the best configuration? Understanding these considerations is essential in order to design the most effective and economical solution for your predictive maintenance (PdM) goals.

Your ideal solution could end up being a stand-alone online system — maybe wireless, maybe automated — or you might prefer a hybrid online and walk-around monitoring approach. The data and analysis could be managed in-house, or third-party services might be preferred. You might even choose to forgo online monitoring altogether until any red tape and budget constraints are overcome. Either way, it’s best to begin the journey with open eyes and a clear PdM vision.

What’s driving online condition monitoring?The motivation for online monitoring is rooted in core business challenges: safety, accessibility, equipment complexity, labor constraints, and insurance requirements. Increasingly sophisticated online monitoring solutions are able to solve problems that walk-around approaches could not.

Safety: With online systems, hazardous equipment and locations can be monitored without risks to personnel or the environment. “Walk-around inspections in unsafe conditions require special access and lockout/tagout procedures, which are labor-intensive, costly, and still potentially risky,” says Laurent La Porte, director of technical services at Azima DLI (www.azimadli.com). An alternative is to install sensors permanently and run the wires out to a safe area and use a walk-around meter to access those sensors.

Equipment accessibility: Machines in distant or hard-to-reach locations are prime candidates for online monitoring. “If you can’t spare the time or cost of a person to drive 200 miles out to a pumping station to collect data every month, then it makes sense to hook up a system that’s automated and will report in on schedule,” suggests Joe Van Dyke, VP of operations at Azima DLI. Wind industry turbines are another example. They are commonly installed on remote land, rough terrain, challenging climates, or at sea, and normally no one is allowed up in a tower while it is operating.

Machine complexity: As machines become more complex and efficient, they require more predictive maintenance attention. “Forty years ago, the machines and subassembly


“ Online monitoring is becoming more prevalent due to the complex nature and running state of the machines.”

components driving process manufacturing were basic, but that is no longer the case. In chemical manufacturing, for example, online monitoring is becoming more prevalent due to the complex nature and running state of the machines,” says La Porte. “Acquiring more and better data, and having it properly assessed, is becoming a necessity.”

Labor pool: If there are not enough personnel at a particular site to absorb the testing tasks, an online strategy can fill the gap. “When your desire for machinery condition awareness exceeds what you can reasonably achieve from walk-around data collections, then an online system will be of value to you,” explains Van Dyke. “If you want to test twice a day but don’t have the resources available, then you need an automated system.” The industry trend is toward fewer personnel and more remote work, particularly in the United States, where labor costs are high. Online systems don’t require salaries or benefits, and they don’t take time off for coffee breaks, holidays, or vacations.

Insurance requirements: Insurance companies may request that certain machine classes be covered by an automated surveillance system, without necessarily defining the specific kind of system or how responsive it should be. Online vibration monitoring systems tend to satisfy


OnlIne mOnItOrIng desIgn cOnsIderatIOns• Selectable input types: DC, 4-20mA, ICP

• Selectable data types: Scalar or process, waveform, FFT (spectra), demodulation,

advanced bearing detection algorithms

• Automation: Data collection, diagnostics, and resulting repair recommendations

• Simple and complex logical parameters: Simple = if X, then Y; complex = if X and/or

Y, then Z

• Ability to set multiple alarms, thresholds, baselines, averages

• Data buffering and/or database storage

• Wireless or wired

• Modular and expandable (hardware and software)

• Fully customizable and instantly re-configurable settings

• Ability to interface with third-party software

this need. “One major pharmaceutical company permanently installed sensors and a dedicated monitoring system on one of its gas turbine generators just because a mutual insurance company required an online, automated condition monitoring system for this critical unit,” says Van Dyke.

Benefits of online versus walk-around monitoringTaking an online approach under the right conditions yields compelling process and cost advantages, such as greater operational efficiency, downtime avoidance, extended asset life, simplified training, and system scalability.

Process efficiencies: Data collection can account for 80% of the labor involved in a walk-around vibration monitoring program. With an online, automated program, the labor burden is near zero because users can remotely command tests, modify test frequencies, and run special tests when needed. “It’s also easier to get online condition system data into other enterprise systems and in front of more people,” says Dave Geswein, director of engineering development at Azima DLI.

Early fault detection: Online systems can detect mechanical problems much sooner than walk-around systems. Delivering notifications and expert diagnostics within seconds allows the equipment to be taken off production and repaired before greater harm is done. “We monitored an air separation unit at a commercial air product company for several years and noticed the compressor pinion’s bearing clearances open up to the point that the OEM had to become involved. The OEM did an in-field, low-cost bearing replacement, avoiding a catastrophic failure of the machine,” says La Porte. “If the unit had gone down catastrophically, it would have cost in the $1 million range for repairs and downtime, or possibly multi-millions for replacement.”

Lifecycle extension: Some machinery operators have equipment with known, common flaws, but they still need to run them. Installing an online system can allow continued use of the equipment while covering them against a fault. If the equipment exhibits signs of the failure mode, it can be addressed right away. “A government agency had a certain class of marine reduction gears with a design flaw operating in four locations. They implemented an online system to look at that gearbox and check for signs of the fault. If detected, they could turn the gearbox down or off, or use a companion unit. This allowed them to maintain operation of the units until a redesign could be instituted a couple years later,” explains Van Dyke.



InterferenceIndustrial wireless condition sensor

technologies fall into two general

technical categories: mesh technology

or a direct-node-to-access-points (APs)

arrangement like regular Wi-Fi 802.11. In

either case, they typically use ISM band

frequencies such as 2.4GHz typical.

Mesh devices form their own self-

healing network and can theoretically

survive the temporary introduction of an

electromagnetic interference source or

sink that interrupts a communications

path between elements of the mesh.

This model is indeed robust, but not

failure-proof, since a node that has only

one connection can get disconnected,

and interference can affect more than

one pathway.

Node-to-AP-based arrangements

rely on a robust array of receivers and/

or repeaters for reliability. While the

set of APs can be designed to provide

redundancy, many wireless devices will

lock onto a preferred wireless access

point and, even when it is weakened or

unreliable, will continue to use it rather

than switch to a temporarily stronger

Node

Node

Node

Node

Node

Node

Node

Node

Node

Node

Node

Monitoringsystem

Controller

mesh technology

LAN


more constant access point signal. This

can introduce reliability issues.

Sources of interference or wireless

signal problems can be as simple as

an object or structure placed between

a transmitter and a receiver, or a

strong magnetic field like having a

transmitter or receiver too close to

an energized motor or other wireless

device. Sometimes having the devices

themselves too close to each other

can cause problems. To remedy this,

there are Wi-Fi surveyor companies

and tools that are available on the

market. Use of these services or tools

can help identify persistent issues,

but don’t always capture intermittent

interference, which can be the most

common type of interference.

When sensors, surveyed assets, or

access points are subject to intermittent

strong EMF, a wireless system that

transmits only small amounts of data

will be more robust. A system that

must transmit long sets of readings will

have more trouble because the longer

time required is more likely to span an

interference event.

Node Node Node

Node Node Node

Access Point

Monitoringsystem

LAN

access Point / repeater technology

Node Node Node

Access Point

Node Repeater Node

Access Point


suPPOrt mOdels

Remote/distance support models cover the spectrum and differ widely but can be divided roughly into three definitions.

1. Data and systems stay in the plant and with remote access allowed via secure connection. This is more common for plants

with restrictive corporate data policies.

2. Data stored/hosted off-site with access to the hosted data for analysis via Web apps, websites, or dashboards. This is

becoming a very common model, with the availability of highly secure hosted data and data services. In this scenario,

systems for acquisition of data communicate their information off-site for secure storage and management and analysis. The

plant personnel access the data via applications running on workstations or corporate servers or as Web applications.

3. Mixed, with remote access to components in place at the plant, and hosted cloud components with some data on-site and

some off-site. This is generally the most flexible solution, offering the best plant systems integration options while still allowing

for good distance support.

everything onsite and Optional services outsourced

data and analysis systems hosted offsite

OPC, SCADAhistorian

CBM Monitoring,Analysis, and

reporting system and services

CBM DataCBM Devices

Optional ExpertAssitance via

remote-desktopor equivalent

Plant ITInfrastructure

OPC, SCADAhistorian

CBM Monitoring,Analysis, and

reporting system and services

CBM DataCBM Devices

Plant ITInfrastructure

Training savings: Walk-around data collection can be taught in a couple of hours, but becoming expert in data analysis can take months or years of ongoing training. On the other hand, automated acquisition tools eliminate data-collection training altogether, and outsourcing data analysis to a third-party service provider eliminates analytical training and turnover concerns.

Scalability advantage: Online condition monitoring systems should be modular and expandable in order to accommodate additional sensors and greater data volume as new requirements or opportunities are identified. “A maintenance team used a condition monitoring system for walk-around inspections and later added an online system to one of their gas turbine generators. Because the existing monitoring system was scalable, they were able to collect the online data in the same database where the walk-around data resided, and no new training or software systems were required,” says Van Dyke.

Understanding the cost factorsA hybrid approach of both online and walk-around monitoring is often the best and most economical course of action. “It’s usually not practical to put online systems on all machines,” says Geswein. “I normally recommend putting online systems on the most important equipment and continuing manual monitoring on the rest of the plant.” Over time, additional classes of machines may be added to the online system if the walk-around program reveals a need for better coverage.

Implementing an online condition monitoring system is usually expensive compared to a walk-around system, and the price can be a hurdle for some organizations. Typically, about 40% of the cost is sensors and cable, 30% is installation labor, and the remaining 30% is the monitoring system itself. Additional costs may include the infrastructure (software, network), training, outsourced monitoring, extended warranties, and future hardware and software upgrades.

Getting permission to install the system carries costs, as well. The approval process can be particularly difficult if significant modifications are required to an existing plant. In industries such as nuclear power, the red tape can be considerable, even if the business justification is solid.


Another often unexpected cost pertains to the role of the information technology (IT) department. “Many companies don’t include IT people in the decisions until the day of the install,” explains Geswein. “The data won’t get from Point A to Point B if a firewall is blocking communications; it’ll have to be configured to allow the data through. At one nuclear facility, getting the firewall modified took two or three months to complete because no procedure existed for doing so. They had never done that type of change before.”

Wired systems have higher installation costs. “I would budget about an hour per sensor to install it and run conduit. That’s the biggest cost of field installation,” says La Porte. Using

wireless monitoring devices can reduce installation costs by reducing the amount of cabling and red tape involved, although the associated batteries introduce maintenance and reliability costs and can limit the data quantity and/or quality.

An online system can be up and running within 30-45 days, depending on the number of machines involved. After that, they generally require little maintenance. Sensors and wires can be damaged, acquisition devices have a finite lifetime, wireless components can be less than robust, and anything that needs batteries requires maintenance. Calibration requirements can also add to the cost. “If you have 100 sensors, you could average a half hour every two months troubleshooting them remotely. For in-plant troubleshooting, I’d estimate about an hour every two months,” adds La Porte.

Calculating the valueThe true value of an online monitoring system is recognized over the remaining life of the facility. Avoiding machinery failures, eliminating data collection labor time, and preventing safety or environmental incidents can easily and very quickly produce bottom-line benefits. “Given enough time, the system’s benefits will outweigh its costs. For instance, if a power plant receives early notification of a turbine problem and takes quick action to prevent further damage, it can be worth millions of dollars,” says Geswein.

“The heightened awareness of a machine’s status gives you the opportunity to make more saves and avoid more failures and unplanned downtime,” explains Van Dyke. “Timeliness is paramount. A wind turbine operator detected signs of a gearbox bearing failure while the


“ the heightened awareness of a machine’s status gives you the opportunity to make more saves and avoid more failures and unplanned downtime.”

gearbox rebuild was still under warranty, so the rework was conducted for free. Had the fault been discovered outside of warranty, a $20,000-$30,000 bearing replacement would still be far more economical than a $200,000 gearbox replacement.”

Standardization and compliance advantagesAutomated online monitoring programs facilitate data collection, testing, reporting, insurance, and warranty compliance. Online monitoring systems allow for standardization of how condition data is collected, stored, and presented. “I’ve seen fingers point to vibration analysis as being ineffective after a critical equipment failed, when it was actually a lack of compliance in data collection that hindered the analysis process,” remarks Van Dyke.

“When you remove people completely from the process and let computers do the work, you get consistent results every time,” explains Geswein. “In vibration analysis, all you are really looking for is a change. If you have consistency from the ground up and a change is detected, then you know it’s real and not some outside influence.”

A corporation that standardizes its predictive maintenance and risk reporting practices and systems will benefit from a larger knowledge base, better history for compliance, and centralized decision making. Other companies prefer their plants to be autonomous and make decisions that are best for them. “Larger organizations like power or paper companies usually let their individual sites determine which technology resources to use for vibration monitoring and analysis,” says Van Dyke.

Technology and tool considerations“A lot of people get caught up in the specifications of the online systems,” cautions Geswein. “To me, what’s more important is whether the software and system that is receiving the data is able to handle the volume that will be collected. People who go from all-manual data collection to even just a few online systems are suddenly swimming in more data than they’ve ever had before. You’ll need the system to screen the data and flag the machines that require attention.”


Increasingly sophisticated online monitoring solutions are able to solve problems that walk-around approaches could not.

Maintaining data security is essential. A company may not want its data to go up to someone’s cloud-based server for fear it falling into the hands of a competitor or hacker. In that case, containment of the data and isolation of the systems come into play. Government agencies with tight restrictions on IT fall into this category, and steel plants sometimes do, as well.

Security concerns also drive some companies to purchase the online system, install it on their own or with some assistance, and then they run and analyze the data internally or put it in the hands of the consultant in charge of the facility. “We call this an ‘inside the fence’ solution when they want to keep all of their data inside. It’s a fairly common model,” says Van Dyke.

The adoption of wireless sensors in vibration monitoring is growing but not particularly widespread. While less expensive to install, wireless technology usually comes with batteries, which require maintenance and can therefore cause the sensors themselves to be less reliable. Additionally, because wireless systems usually transmit the data over radio waves, they try to reduce the data down to a few single parameters rather than the high-definition data that an analyst may prefer to have on every measurement. “Rather than complete high-resolution spectra and waveforms, the analysts may only receive overall measurements. If they detect any changes in an overall measurement, they’ll need to reconfigure the system to collect the spectral data if possible,” adds Van Dyke.

ConclusionWeighing the pros and cons of online monitoring will help you decide if it’s right for you. Each company’s business case is unique, but the flourishing predictive nature of online monitoring systems is simplifying their justification. Automated solutions, enhanced data capture, rapid analytics, and early warning of potential failures are among the compelling features designed to solve operational and budget challenges. Organizations that incorporate online monitoring with or without a walk-around program are empowered to operate more efficiently, reliably, and safely, with fewer mechanical failures and costly unplanned outages.


“ acquiring more and better data, and having it properly assessed, is becoming a necessity.”

Monitoring magic | 35

Monitoring MagicWatch your assets froM the cloudby Sheila Kennedy, contributing editor, Plant Services magazine

The introduction of cloud computing and a new design paradigm for predictive maintenance (PdM) instrumentation are adding versatility to the implementation of PdM

programs. Automated online condition monitoring, supported by the cloud, is shifting the burden from front-line maintenance personnel to remote specialists, whether in-house, third-party service providers, or both.

Compared to the early days when screwdrivers were pressed to the ear to hear machinery problems, this new approach works like magic. It is far more practical, comprehensive, safe, and cost-effective.

“Since 2000, the instruments have gotten faster. They can measure and store larger quantities of data, the graphics have improved, and the data exchange process is much faster,” says Ken Piety, vice president of technology at Azima DLI (www.azimadli.com). In addition, systems now exist that allow unmanned and more frequent data collection, and the introduction of cloud computing makes the data and analysis more widely accessible to authorized personnel.

The reliability gains that result from online data collection and remote diagnostic analysis are game changing. “Our communications infrastructure and mobile devices have shrunk the world, and radically changed both our personal and business lives,” adds Piety.

Why change was neededImprovements to PdM over the years have enabled more timely information, sophisticated analysis, effective data presentation, and impressive return on investment (ROI). As a result, the number and scope of PdM programs and the size of the audience are expanding within and beyond the four walls of the plant. This is causing the machines, reliability professionals, and other stakeholders to become more geographically dispersed, and increasing the demand for the flexibility of a distributed PdM model.

Traditional monitoring models brought in-house or external analysts to the machines. Internally driven programs were generally informal and limited in scope because the startup and maintenance costs and resource demands were high. Often, interest in the program would wane if the champion moved on. Programs that were outsourced created a dependency on the supplier for the equipment, data collection, and analytical services. Timeliness was sometimes lacking and any changes or increases in the machines monitored came at a cost.


The distributed approach brings PdM data and information to the people who need it, when they need it, wherever they are located at the time.

The DisTribuTeD MoDel

Data Collection

Data Analysis

Execute Corrective Actions

Plan and Schedule Maintenance

Program and Plant Management

The more modern option today is the distributed approach, where PdM data and information is brought to the people who need it, when they need it, wherever they are located. “With a distributed model, companies can elect to operate entirely with an in-house PdM staff, or they can outsource all manpower, use a blended staff routinely, or seek assistance during specific periods or for special problems or second opinions,” explains Piety.


With the information stored in the cloud, authorized personnel at any location can track machinery performance, troubleshooting data, corrective actions, and program results.

inTerDePenDenT sTakeholDers

Corporate Management

Plant Management

Maintenance Planning and Performance

Data Analysis and Machine Health Reporting

Data Collection

Remote monitoring access can be provided through an Internet connection. Companies with strict corporate policies may elect to maintain the data and systems at the plant and enable secure remote access. Others prefer offsite hosting and storage of the data, with analysis performed over the Internet.

“All of that information is sent to a central repository and analyzed by trained analysts 24/7, so maintenance personnel fix only the equipment that needs attention at that moment,” explains Joe Van Dyke, vice president of operations at Azima DLI. “The benefits can be very significant, resulting in advanced notice on machinery problems that could otherwise have devastating financial and safety ramifications.”

A third, more versatile and increasingly popular approach leverages a combination of plant-based and cloud-based components. “The mixed approach provides remote access to components in place at the plant, as well as hosted cloud components with some data on-site and some off-site,” says Van Dyke. “This is generally the most flexible solution, offering the best plant systems integration options while still allowing for good distance support.”

Program benefitsThe primary functional benefits of a distributed PdM program include automation of data collection, access to dynamic information, and the elimination of communication barriers.

Monitoring automation: Automated monitoring systems enable more frequent and more predictable machine condition monitoring without the aid of data collection personnel. They can gather readings on many machines on a near-continuous basis, making them more cost-effective than the labor-intensive walk-around programs. “Near-real-time test frequencies are possible when testing high-speed equipment or gathering overall vibration or scalar data like temperatures and pressures,” says Van Dyke. As a result, plant personnel can focus on higher-value activities while the system sends its updates to the cloud.


Dynamic awareness: Automated or online systems can observe dynamic changes in machine fault conditions arising from certain load, speed or operating condition changes, but at a lower cost, according to Van Dyke. Compared to walk-around monitoring programs, online systems are always on duty so the sought-after events won’t be missed. When integrated into SCADA systems, the online system can be designed to collect data only under specified loading and operations conditions, which avoids collecting data when machines are idling, unloaded, or turned off.


automated monitoring systems enable more frequent and more predictable machine condition monitoring on a near-continuous basis, making them more cost-effective than labor-intensive walk-around programs.

reliabiliTy PorTal DashboarD

Open communication: Cloud-based condition monitoring breaks down communication barriers within the plant, across the corporation, and among trusted reliability service providers. Plant and corporate operations, maintenance operations, diagnostic center operations, and the field data collection and data analysis teams all have a stake in the program and its outcome. With the information stored in the cloud, authorized personnel at any location can track machinery performance, troubleshooting data, corrective actions, and program results.

Strategic benefitsBest practices in condition monitoring are supported by this model, and it addresses strategic concerns about costs, expertise, safety, and corporate performance.

Reliability cost efficiencies: Remote data collection and diagnostic analysis ensures more consistent, near-real-time insight into equipment conditions, enabling proactive steps to improve performance and avoid failures. It generates ROI through accurate and timely machine performance assessments, including efficiency, throughput, etc., and relating that data to the machine condition.

Sustainable expertise: Mitigating the loss of critical talent is a universal goal in the industrial space. “Machinery analysts tend to turn over every three to five years, and it requires a minimum of two years to train a new analyst,” says Piety. “In addition, very few analysts are experts in analyzing all types of machines and all types of faults.” The distributed model allows companies to assign program functions to those who can execute the tasks at the lowest cost and with the greatest effectiveness, whether it’s internal personnel on site or at a sister plant, or an external service provider.

Improved safety: Online monitoring systems help to keep personnel away from unsafe environments and equipment. “It allows for collecting data in sensitive, dangerous, or hazardous areas without risking harm to your personnel, processes, tools, or the assets you are monitoring,” says Van Dyke. “Even when the equipment or the environment is considered safe, safety ratings should be expected to improve because automated data acquisition eliminates the need for personnel to be physically entering machinery spaces or carrying instrumentation up and down stairs and ladders, and it all but eliminates the potential of contacting energized equipment.”


Corporate standard: The distributed PdM model encourages the adoption of industry best practices across all sites. “It allows the sharing of information with corporate counterparts for the purposes of consultation, troubleshooting, collaboration, and reporting of KPIs and other performance-related issues,” says Van Dyke.

Outsourcing and the cloudThose seeking outside assistance might consider a diagnostic service provider and storing the PdM data in a commercial virtual data center. Virtual diagnostic centers are generally staffed by large teams of experts with diverse expertise who use state-of-the-art, cloud-based communication methods. Their high-bandwidth physical data centers are accessible globally over the Internet, and their hardware and software excels at communicating data and information. Closed-loop communication methods connect all team members, and the operational infrastructure is designed to secure data from loss.

Piety summarizes the business benefits of this approach as follows: • Centralization: PdM data is centrally stored for access by multiple users• Collaboration: Multiple analysts can collaborate, thus increasing diagnostic accuracy• Integration: PdM is accessible to other business systems, which opens the door to data

exchange between systems• Transparency: The more people who see PdM information, the more valuable the program

becomes• Communication: Email alerts or text messages can notify specified individuals when specific

events have occurred, such as health state change notifications, due and overdue reminders, and the delivery of program KPIs

• Participation: Others can gather data, contribute knowledge, and record observations• Optimization: The right people can perform each function at the lowest cost

Special considerationsA rigorous IT data security policy is needed for condition monitoring systems that push data to the cloud or allow access in from remote users. Firewalls must be constructed and managed to restrict all unnecessary and unauthorized access, and suitable data encryption methods must be employed.


Users of data centers and cloud-based systems must also address data ownership and data protection. Although data is generally considered the property of the asset owner, Van Dyke recommends that explicit, contractual provisions be made to ensure that the data is protected, not copied, and returned if and when the contract is canceled.


a distributed, automated condition monitoring system leveraging cloud computing and today’s PdM instrumentation is far more flexible and functional than prior options.

soluTion: The DisTribuTeD MoDel

Controlled costs through

efficiencies

Increased effectiveness

through collaboration

Sustainable expertise through

virtualization


Continuity of services from an IT perspective is another consideration. If a critical link is severed because someone at the data center accidentally changes a password on a server used by a remote monitoring system, it can cause cessation in monitoring. Another example is if a monitoring system data feed stops due to a permissions issue, it could generate an erroneous problem report, leading to wasted time chasing the problem at the plant.

ConclusionA distributed condition monitoring system leveraging cloud computing and today’s PdM instrumentation is far more flexible and functional than prior options. It heightens the breadth and depth of expertise accessible to an organization; supports transparent communications and collaboration; improves skills application; and helps to control costs and mitigate safety concerns. It pulls the curtain back to expose the true value of predictive and condition monitoring.

Not only will it ease the rollout of PdM where such programs do not already exist, but it is a logical upgrade and enhancement for plants running traditional, in-house programs. Any number of predictable or unpredictable events can upend a condition monitoring initiative; analysts may leave, funding may be cut, or a program expansion or new tools beyond current capabilities may be desired. No other approach can ease these transitions as well as distributed PdM.

Sponsored by

Produced by

Azima DLI World Headquarters300 TradeCenter, Suite 4610

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Predictive Maintenance Guidebook - Azima DLIazimadli.com/wp-content/uploads/Special-Report-PdM... · Predictive Maintenance Guidebook | 2 How does PdM generate operational efficiencies?