By: Reggie Fett, MCA/IR Analyst

Time Context

Tuesday, April 16, 2013

Process Information

This asset is a pump used to pump water for the milling process and cannot be shut down for more than 3 hours during the milling process. Shutting down the pump causes operations to have to switch tanks for that period of time and requires constant monitoring to prevent product overflows.

Summary of Action

During routine on-line (energized) motor circuit data collection, test results indicated a 26.5% current imbalance, along with a 35.36% impedance imbalance. Looking at Figure 1, the Power Phasor shows the current imbalance indicated by the shorter current 1 and current 3 lines. Figure 2 shows the imbalance in the current section of the power test results page. Figure 3 is the Current Time Domain showing current 2 higher than currents 1 and 3. Voltage was checked and found to be balanced across the motor starter at 283 VAC phase-to-neutral and 490 VAC phase-to-phase.

Vibration data was collected and found the motor was in alarm for a 2x line electrical frequency, indicating there was a possible electrical issue (Figure 4). An infrared scan was conducted on the electrical enclosures containing the fuses and motor starter. The B phase fuse and connections on the motor starter were operating with an above alarm level temperature differential. A thermographic scan of the motor revealed that the housing was operating hotter than normal, indicating a possible issue within the circuit. Figure 5 is an infrared image taken of the motor soon after the current imbalance was discovered by the on-line test. It shows the motor temperature was running above normal at 215°F, caused by the current imbalance. Figures 6 & 7 are infrared images taken of the motor starter and fuses. The temperature differential of the B phase circuit is caused by the imbalance in the circuit due to the high resistance connection. A work order was written to perform an off-line (de-energized) motor test to isolate the cause of the imbalances.

An off-line test was conducted from the Motor Control Center (MCC) and found a 44.65% phase-to-phase resistive imbalance, along with an 11.65% inductive imbalance. Figure 8 shows the phase-to-phase resistive imbalance and inductive imbalance from the off-line test conducted from the MCC indicating a high resistive connection in the circuit. It was decided that further testing should be done by going to the motor and disconnecting the motor from the circuit to further isolate the cause of the imbalances. Upon opening the motor junction box, a bad connection was discovered (Figure 9). All connections were repaired and another off-line test was conducted from the MCC, which indicated that the repairs had corrected the issue.

Post Notification

Department reliability coordinators and maintenance supervision were notified as soon as it was confirmed that there was an issue and made aware of the motor running hot, creating a potential burn hazard for employees.

Supporting Data

Plan Of Action

Monitoring with MCA both on-line and off-line will help to identify this type of issue before it can damage equipment or injure personnel.

Conclusion

Not only is this type of condition shortening the life of the motor, but is also a potential hazard to personnel in the form of a shock hazard or burn hazard. If the connections were touching any part of the motor frame and the motor was not properly grounded, an individual who happened to touch the motor would become the least path of resistance to ground and could be seriously injured, suffering burns from the motor running hot, or worse, loss of life.

By using the multi-technology approach to reliability – on-line/off-line motor circuit analysis, vibration analysis, infrared analysis, and other reliability technologies including oil analysis and ultrasonic analysis – this type of anomaly, as well as others, can be detected early and help reduce unexpected downtimes, production losses, and most importantly, safety concerns for a facility’s personnel.

Synopsis

Figure 1: Unit 4 East Drain Heater Pump Motor

Table 1: Motor Information

Figure 2: Unit 4 East Drain Heater Pump Motor

Figure 3: Unit 6 East Drain Heater Pump Motor

Figure 4: Motor CB1 Phase A Before Repairs

Figure 5: Motor CB1 Phase A After Repairs

Figure 6: Motor Missing Internal Cover

Figure 7: Similar Motor Showing Internal Cover

Plan of Action

Conclusion

By: Aubrey Green, Lead Analyst

While gathering data on a regular monthly route, I was working on the ground floor collecting data on the critical equipment. My next piece of equipment to be checked was the non-drive end of the after dryer pulper (Figure 1).

As I approached the non-drive end of the paper machine pulper agitator, I noticed that the bearing housing was moving axially. This is not a normal operation mode for this piece of equipment. I placed my hand on the bearing housing and could feel an irregular bumping coming from the bearing. I took my vibration measurements using my normal route analysis parameters (Figure 2).

The vibration spectrum showed peaks of turning speed vibration. There was nothing that was really shouting out that there was an issue with the equipment. In the middle of the spectrum, one might pick out sidebands of ½ orders of turning speed, but the spectrum did not show vibration levels with which I would have been concerned.

I felt the spectrum was not showing what I was feeling and seeing. The Emerson CSI 2130 data collector I was using has the ability to collect data with much better frequency resolution. This means that the spectrum is divided further along the bottom axis in order to be able to better separate frequencies. The compromise for this better data is that the time to collect the data increases. I set the data collector to the highest resolution and took another reading.

The high resolution data presented a different diagnosis (Figure 3). The peaks along the right side of the spectrum are at ½ orders of turning speed and harmonics of that speed. These peaks are indicative of a looseness condition. The raised noise floor indicates random vibration coming from the bearing.

Supporting Data

Figure 1: Non-Drive End Bearing of After Dryer Pulper

Figure 2: Spectrum of Vibration Data Using Route Parameters

Figure 3: Spectrum of Vibration Data Using High Resolution Parameters

Summary of Action

I immediately informed the Reliability Leaders about the condition of the after dryer pulper. They devised a plan for the next outage, which lasts long enough for the mechanics to complete the necessary work. The mechanics will pull the bearing cap and inspect the bearing and adapter. If it is determined that the adapter needs changing, the work will be scheduled. A new bearing and adapter are also being ordered to have on-hand in case replacement is necessary.

Conclusion

My senses told me there was a problem with this equipment. As a qualified Vibration Analyst, I understood the limitations of my data collector settings and I knew to change the settings to match the event I was trying to capture. In a situation such as this, believe your senses, but use your data collector to validate your findings.

By: Aubrey Green, Lead Analyst

In early January of 2012, I assumed the responsibilities of the vibration analysis program at a customer’s site that had been using another contractor before Allied Reliability transferred me to the site. The former company was using Emerson’s AMS software and the CSI 2120 data collection equipment. We continued using the same software with the newer 2130 Machinery Health Analyzer.

I looked over the existing database and realized that the former PdM contractor was not using PeakVue in its analysis. PeakVue, or the peak value analysis methodology, is Emerson’s process of using demodulated data for vibration analysis. One can set up the database so that the PeakVue reading is acquired at the same time that another reading is being acquired.

I ran the initial route on the support equipment for the paper mill in February, which included the vacuum pumps that pull water out of the pulp stock to help form a sheet of paper. I noticed a pattern on the drive end of the #2 pump matching how an inner race defect should appear. I did not have the bearing information, so I noted this for further investigation. The pattern was not visible on the normal vibration data.

In March, I had the proper bearing information and pump speed set up for data collection and acquired data on a regular route. Normal vibration readings did not show any bearing defects (Figure 1). However, PeakVue analysis showed that the bearing fault did indeed exist (Figure 2). The next step would be to try to assess the amount of damage to the bearing as the site wanted to know if failure was imminent.

PeakVue uses ultrasonic emissions and signal processing to produce the spectrum for analysis. Ultrasonic emission is usually a very early detector of bearing failure. The system is purported to detect a defect before it breaks the surface of the bearing race. However, ultrasonic emissions degrade quickly each time they move through an interface. An inner race defect must move from the defect into the roller, then through the roller into the outer race, and finally through the outer race to the accelerometer on the machine surface.

Based on my findings, I advised the site that catastrophic failure of the bearing was probably not imminent, but the bearing should be changed in the near future. To do this, the site would need to schedule a contractor to perform the work. This large vacuum pump is the second pump in a set driven by one motor and is furthest from the motor (Figure 3). The pump would need to be moved from its mount in order to change the bearing, and the work was estimated to take at least 12 hours to complete. The Planner for the area questioned me a few times about how certain I was about the call. As this would be a large expense for the site, he wanted to make sure he needed to spend the money. I told him I was positive that the failure was there.

The site opted to change the bearing two months later during a regularly scheduled outage, which allowed them to minimize downtime on operations. The pump’s coupling was disassembled, the pump was moved away from its mounts, and the bearing was removed. An inner race fault about 3/8 of an inch wide and 1 inch across the bearing was found (Figure 4). The bearing was changed and the pump was reinstalled and put back into operation. Total time to perform the work was 12 hours.

The savings potential for this discovery is immense. The obvious savings could have been at least 12 hours of downtime while the bearing was changed out in an emergency situation. Realistically, the time would have been greater as no preparation would have been made to get the proper tools to the job site. Personnel would also have to be moved around in order to accomplish the work. If the failure had occurred during off hours, mechanics would have had to be called in to perform the work. All of this would have added up to a best case scenario.

The worst case scenario would have been if the inner race had cracked and the impeller had worn down. A new rotor would cost in excess of $100,000, and new rotors are not kept on hand at the manufacturer.

PeakVue, or demodulation, is a tool that should be used to help determine problems in our equipment. Proper use will help keep equipment running and avoid unwanted downtime.

Figure 1: Normal Spectrum Before Repairs

Figure 2: PeakVue Spectrum Before Repair

Figure 3: #1 and #2 Vacuum Pumps

Figure 4: Inner Race Defect

Figure 5: PeakVue Spectrum After Repair

Addendum to Case Study: A Question From a Reader

When this case study was posted on Allied Reliability’s blog, Carlos Hernandez asked an interesting question: did the PeakVue time waveform and autocorrelation waveform give indications of the inner race defect issue?

The PeakVue waveform showed a pattern of increasing amplitudes at the rotational speed of the inner race. As the spall begins to enter the load zone, the amplitude increases. This increase is due to the added load causing the rollers to impact the spall harder. The level generally peaks at the bottom of the load zone, then the level decreases as the roller moves away from the load zone.

Figure 6: PeakVue Waveform With Rotation Markers

Autocorrelation of the PeakVue waveform uses statistics to reduce the random impacting shown in the waveform. The waveform after it passes through the autocorrelation formula clearly shows the increase in impacting at rotational speed and the inner race defect impacting.

Figure 7: PeakVue
Spectrum After Autocorrelation

By Guest Blogger- Andy Page, Principal GPAllied

Certification Training Classes:

People believe that simply attending a class on vibration analysis makes them qualified to manage a vibration analysis program. This is not the case. Vibration certification training, such as Category 1, 2, or 3, is designed to teach someone how to collect and analyze data. That’s it! Nothing else. These classes are not designed to teach someone how to design a vibration analysis program, how to manage a vibration program, or even how to integrate the data coming from the vibration analysis program into the daily work execution management scheme. While I used vibration analysis as an example of Predictive Maintenance (PdM), the preceding commentary is the same for all PdM technologies – including infrared thermography, oil analysis, ultrasonics, and most especially motor circuit analysis. Another type of class is required to learn to design and manage a PdM program.

Implementation:

Why would we worry about the design of the PdM program? Don’t we implement as much as we can as quickly as we can? No, not at all. PdM program design is about complementing the existing Preventive Maintenance (PM) program in such a way as to maximize work identification and minimize the amount of PM inspections. This is done through a failure modes analysis and a technology mapping exercise.

Too Much Too Fast:

Many companies have made the mistake of trying to implement as much PdM as quickly as they can. This is not healthy either. The introduction of a new work identification method, especially one as sensitive as PdM, takes some time to get used to. The workflow processes have to be adjusted to compensate for the increased flow of work and the notice that PdM jobs provide the organization before they fail. These increased numbers of work orders and increased lead times are very difficult for plants to integrate quickly. A maturity progression plan helps the organization bite off smaller, more digestible chunks that make it so easy for people to get their heads around and understand.

Understanding the data:

Not all PdM technologies are created equally. Some technologies are easy to understand and easy to use. Take airborne ultrasound for example; this inspection technique is easier to implement. Why? It is audible and in some situations the analyst may be able to tighten a fitting on the spot and get instant results.  Vibration analysis, for example, is a different story altogether.  It is very difficult for people to see that tiny little blue line and believe, even for a moment, that the little blue line on the screen means the brass cage is defective in the motor bearing. It just seems too difficult to believe. So, helping people understand what technologies are easier to implement than others and where the challenges exist makes the design of the PdM program much more comprehensive.

In PdM program management, the most often abused and improperly managed aspects are the data collection and route compliance. There is a method to ensuring that the data is collected and managed properly that aligns with route compliance. Route compliance is the measure of how many machines someone actually measured divided by the number of machines they were supposed to have measured. This concept is similar to schedule compliance in a CMMS. Poorly managed route compliance tends to degrade the credibility of the program as data not collected means defects missed. In the best case, the missed data collection means that we have a shorter warning interval for dealing with the problem. The worst case is that the poorly managed data collection means we miss a failure that actually occurs and the company loses production time as a result.

Keeping Credibility:

A missed opportunity is where the PdM program should have caught an impending failure before it occurs but did not or when the rest of maintenance fails to work on something that PdM identified. These missed opportunities severely degrade the credibility of the program and are not particularly helpful to the machinery on which the missed fault occurred. Managing missed opportunities is a critical part of PdM program management. They can really impact the quality of the program.

There are many metrics that can be used in PdM program management. We have already discussed a couple of them, route compliance and missed opportunities. Others include mean time to implement findings, number of new defects, number of old defects that have not been addressed yet, and the king of all PdM metrics, asset health – the measure of how many machines have no identifiable defects. Some of these metrics are leading metrics and some of them are lagging metrics, but all of them tell a specific tale and help us manage the PdM program.

These are just a few of the items included in the design and management of a PdM program. Becoming aware and somewhat proficient with these concepts make the PdM program easier and easier to manage.

About the Blogger:

Andy Page is the Integration Director with GPAllied. As the Integration Director, he is responsible for combining the philosophies and daily practices of the 2 companies that came together to form GPAllied: General Physics and Allied Reliability.

Andy has 15 years in the maintenance and reliability field where he has played several different roles. First, as a Maintenance Engineer for Noranda Aluminum, he was responsible for implementing a comprehensive PdM program and continuous improvements of the planning and scheduling function. Next, he held the role of Regional Services Manager for CSI where he provided technical services to new customers and for the sales staff. After that he worked for Martin Marietta Aggregates as the Asset Reliability Manager responsible for PdM and maintenance improvement process effort across 23 plants in Ohio, Indiana and Michigan. Next he served as the Vice President – Operations for a small consulting firm called Reliability Solutions, Inc. in central Ohio providing PdM services primarily to the mining industry.

Andy has an engineering degree from Tennessee Technological University and is a Certified Maintenance and Reliability Professional (CMRP) through the Society for Maintenance and Reliability Professionals (SMRP) and is a Six Sigma Black Belt.

Andy resides in Charleston, South Carolina with his wife, daughter, and son.

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By: Danny Blackford,
Remote Diagnostics Reliability Professional, Allied Reliability,
blackfordd@alliedreliability.com

What do you think of when you hear the term ‘remote’? Probably operating something from a distance – cars, planes, or maybe televisions? What about a Condition Monitoring Program?

Let me ask you a few other questions. Do you have a Condition Monitoring Program at all? Do you collect data at your facility that never gets analyzed? Do your analysts have the experience and qualification needed to make correct recommendations based on the findings from your equipment? Is employee turnover an issue for retention of those qualified analysts?

In today’s challenging economic climate, companies are continually looking for ways to maximize the return on their maintenance investment. It has long since been accepted that condition monitoring provides the best opportunity for early defect detection and root cause identification and is the staple for the majority of targeted failure mode-based maintenance strategies. The difficulty many organizations face during the development and implementation stage is that the correct resources and specialized skill sets are not available on site. Many organizations also find it cost prohibitive to build this capability on their own and from the ground up.

Yes, building a Condition Monitoring Program takes time and a lot of capital and training. And it can be difficult to achieve consistency in a Condition Monitoring Program. But there is a solution that can ease the burden of establishing these programs, lead to more consistent and effective activities and results, and provide a number of other benefits for your organization.

It’s simpler than you think… when you utilize a Remote Diagnostics Program.

What Is ‘Remote Diagnostics’?

Remote Diagnostics is a condition monitoring application method that utilizes on-site resources for technology-specific data collection and off-site contract resources for data analysis. By using a combination of resources to perform routine condition monitoring activities, splitting up data collection and analysis responsibilities, you can produce a low-cost model for your Condition Monitoring Program.

Depending on a company’s needs, a provider of Remote Diagnostics may recommend a condition monitoring model where the company’s own resources are utilized for technology-specific data collection or a hybrid approach that makes use of contractor personnel to gather the data. This hybrid approach reduces the time and travel requirements for contracted services, enabling a lower-cost solution. This shared application also utilizes the unique expertise of all participants, allowing for a quick implementation with highly skilled resources, which can generate rapid results.

When Is Remote Diagnostics the Right Model for Your Plant?

Companies who find themselves in any of the following situations should consider choosing a Remote Diagnostics program:

A Remote Diagnostics method may also be very attractive to organizations that value internal participation in technology use and are also trying to build internal skill sets for further condition monitoring coverage or applications.

How Does Remote Diagnostics Work?

Figure 1: Remote Diagnostics

A Remote Diagnostics model breaks down the individual tasks necessary for a successful Condition Monitoring Program and utilizes a cooperative effort between contract site resources to complete these responsibilities. Duties are typically split up to accommodate two separate avenues of responsibility that inherently follow individual areas of expertise, which pairs the best of both worlds as site resources responsible for data collection are equipment history and process knowledgeable while the Remote Diagnostics analyst is a certified and qualified condition monitoring specialist.

On-site resources should focus on the collection and submission of routine data, as well as qualitative equipment observations. The on-site team should also play a key role as the communications link and act as the investigative arm of the Remote Diagnostics team, providing concrete feedback and insights into scenarios and observations.

The off-site Remote Diagnostics team resources focus on the analysis of supplied data. It is imperative that the Remote Diagnostics technicians are technology certified and have the understanding and background to assess asset health based on applied technologies. Remote Diagnostics resources will then provide comprehensive condition assessments and corrective action recommendations to the on-site team. The role of training and mentoring will also fall to the Remote Diagnostics team, enabling continuous improvement in the development and application of a World Class Condition Monitoring Program.

The following Remote Diagnostics Program design delivers the best possible results as well as the required support during critical steps in the process:

1. Equipment Walkdown – During the program setup phase, a contractor resource should utilize equipment walkdown software to capture machine configurations and attribute information. This information should then be used to develop the technology databases for Remote Diagnostics condition monitoring activities.
2. Route Development – The equipment should be divided into logical routes for data acquisition based on a hierarchy established by location, process, access, and availability.
3. Technology Database – Asset configurations should be established within the technology database with component-specific collection and analysis parameters, as well as customized alarm parameters based on technology standards. Equipment attribute information should be input into the technology platform in order to establish customized fault frequency sets to aid in early defect identification.
4. Reporting Database – Using industry-preferred software, the Remote Diagnostics analyst should build a custom integrated reporting database for your organization, setting up appropriate and meaningful metrics and KPIs.
5. Training – Without properly collected data, accurate analysis is impossible. An experienced Remote Diagnostics service provider should also offer task qualification for your data collection personnel, teaching them best practices for data acquisition or lubrication sampling methods.
6. Results and Support – An ideal Remote Diagnostics Program service provider will offer 24/7 access, detailed condition assessments, history, and recommendations, as well as KPIs. In addition, continuing education for data collectors and advanced troubleshooting and phone support availability should be provided. It is of extreme importance that your site has access to your analyst when you need him.

Remote Diagnostics Program Benefits

Establishing a Remote Diagnostics Program can result in a cost savings of up to 40% versus other types of Condition Monitoring Program models, but more importantly, a Remote Diagnostics approach allows organizations to reap the rewards of an effective maintenance and reliability initiative in a fraction of the time typically necessary to build a World Class program. It incorporates contractor knowledge, processes, and technology standards without full-time contract resources. A successfully implemented Remote Diagnostics Program can yield the following on-site benefits:

• Builds on-site ownership of and ‘buy in’ for a Condition Monitoring Program.
• Establishes ability and resources for root cause identification.
• Enables precision maintenance practices and a proactive workflow.
• Allows for equipment repair validation.

Furthermore, with the separation of responsibilities, you can in effect double your potential resource pool and allow for increased coverage levels.

Choosing a Service Provider

Everyone knows there is not one ‘silver bullet’ when it comes to evaluating complete asset health. Each condition monitoring technology has component failure modes that it is better suited to identify and typically there are numerous failure modes associated with asset types based on their component makeup. As such, a Remote Diagnostics provider should be able to support multiple PdM technologies, including:

• Vibration Analysis
• Mechanical and Electrical Infrared Thermography
• Ultrasound
• Oil Analysis
• Motor Circuit Analysis

Ideally, the provider you choose would be able to provide a combination of remote analysis review and support, coaching and mentoring with task qualification of site resources, and assistance with identified issues utilizing contractor resources.

Figure 2: Ideal Remote Diagnostics Process

If you have decided that a Remote Diagnostics Program is a good fit for your organization, here are a few program design considerations to keep in mind while you are looking for a contract service provider:

• What condition monitoring technologies do you wish to incorporate?
• How involved do you want to be in the asset health condition assessment process?
• Is there a desire to internalize the program eventually?
• Do you have internal resources that you could devote to condition monitoring activities?
• Are you alone in your efforts or can you consolidate with neighboring facilities?

When considering a Remote Diagnostics method, the keyword in a successful application is ‘flexibility’. Successful implementation of a Remote Diagnostics program requires agreement between the site and the Remote Diagnostics team to document and establish maintenance and reliability initiatives for the program, as well as alignment with future goals and objectives. As such, the Remote Diagnostics contract service provider must be prepared to tailor its approach to reflect the site needs while making the best use of available resources.

The Remote Diagnostics team should support a wide range of site participation. Some sites may choose to just collect and submit required data for analysis without the desire to access the technology-specific software platforms. Others may prefer to have full access to and use of the same tools available to the analysts, with continued integration, training, coaching, and mentoring in order to build internal skill sets.

Along those lines, the skill sets necessary for data analysis should not be software platform dependent. Remote Diagnostics analysts should have the knowledge to support many different technology hardware and software platforms. The analysts’ utilization of these systems may vary from standalone systems utilized by the Remote Diagnostics analysts to remote access through client network services or even online continuous monitoring applications.

In Summary

A Remote Diagnostics model is a universal application and yields similar benefits regardless of the Reliability Program maturity level or size of the organization. The Remote Diagnostics method has been found to be extremely beneficial for sites endeavoring to implement a new Condition Monitoring Program or enhance their current capabilities and coverage levels.

By guest blogger Carey Repasz, Principal Technical Advisor
The position of the Reliability Engineer (RE) is very common in today’s maintenance organizations. What is uncommon is an understanding of what the RE actually does, should do and shouldn’t do. The responsibilities of this role vary wideley from organization to organization.

While the following tasks are not by any means a complete description of what the RE does, these tasks represent the most important tasks that every RE should be performing in a maintenance organization.

Task #1:  Manages the equipment hierarchy and equipment
criticality databases.

The equipment hierarchy and criticality are the foundation that all reliability improvement strategies rely on. The level of completeness and accuracy of these databases are absolutely essential in order to build appropriate maintenance strategies and target reliability improvement tools to the appropriate systems where the greatest benefit will be realized. Hierarchy also includes all necessary component information and attribute data that will enable failure mode analysis. Maintaining an effective criticality databasebinsures that the relative importance of each piece of equipment is understood so that strategies can be determined and work can be prioritized for the most effective use of resources.

Task #2: Ensures that all plant equipment has an equipment maintenance plan on file that matches the expected failure modes.

The RE crafts a strategy of both preventive and condition monitoring tasks that are specifically designed to identify or prevent failure modes.  By using collected information about the equipment, failure modes are identified and the appropriate tasks are
selected to identify or prevent these failure modes as early as possible. The strategy is implemented according to the criticality database. Methodologies to determine the failure modes of equipment include Reliability Centered Maintenance (RCM) and Failure Mode Mapping.

Task #3:  Development and Management of the PdM/CBM program

As the owner of the failure mode based strategy, the RE will develop and implement the Condition Monitoring program, often referred to as CBM or PdM. This entails determine what technologies will be deployed to which equipment based on an understanding of the capabilities of the CBM technologies to address failure modes and the resources available to apply to
the most critical assets. Using the foundational elements to determine which equipment should initially be included as well as what technologies are deployed to what failure modes is a key to early success. By measuring and understanding the health of the equipment included in the strategy will determine the next phase of implementation.  The RE will manage the CBM program by tracking key indicators such as equipment health, route adherence, mean time to implement recommendations and
defect elimination.

Task #4: Performs statistical analysis on equipment failures to determine changes to the equipment maintenance plan

Understanding what types of failures are most common through analysis of the Failure Reporting and Corrective Action System (FRACAS) enables the RE to make adjustments to the existing equipment maintenance plan. Collecting and analyzing equipment failure data allows for the tracking of bad actors and identifying dominant failure modes. Implementing the appropriate strategies enables a robust defect elimination strategy. Statistical analysis of failure data using tools such as Weibull analysis allows the RE to accurately determine what type of maintenance strategy is most appropriate.  Tools such as Availability Simulation allow for the optimization of task intervals.

Task #5: Leads and manages the Root Cause Analysis process

Managing the Root Cause Analysis (RCA) Process consists of identifying appropriate triggers, facilitation of RCA and managing the Action Item Register. Effective triggers allow opportunities to be identified without overwhelming the system. Proper facilitation will obtain the true root cause and identify appropriate action items that will not only solve the problem at hand but make possible system and process level improvements. Effective management of an Action Item Database will drive ownership of the corrective actions as and make for an effective method to communicate and track results.

Establishing processes for these five activities allow the RE to fulfill the primary mission: creating and implementing an effective strategy to identify machinery defects and eliminate the source of those defects and use the appropriate tools to continuously improve that strategy.
Carey Repasz, Principal Technical Advisor

Carey has held positions as a vibration analyst, PdM analyst, program manager and technical director for operations. Today he is a Principal Technical Advisor and is one of Allied Reliability’s Senior Instructors for the PM/PdM Best Practices Training.  Carey jointly developed the curriculum and shares his many case studies from his experiences with our clients in implementing best practices.

Carey is a Certified Maintenance & Reliability Professional (CMRP) through the Society for Maintenance and Reliability Professionals (SMRP), and his certifications include Thermography ASNT level I, Vibration ASNT level II, Ultrasonics level I
and RCM Blitz™.

Carey is a frequent speaker at industry conferences and focuses on Asset Health, Condition Monitoring program design, Reliability Engineering, Mechanical Engineering and Condition Monitoring program implementation.

By Guest Blogger Andy Page, Integration Director, GPAllied

While there is an abundance of information out there about managing your rotating and stationary mechanical assets, not much exists about how to manage your electrical equipment. The good news is that the concepts are precisely the same; it is only the inspection techniques that change, and they do not change all that much.

There exists some belief that simply because electricity is flowing through the asset that the management of that asset is different in some way from the mechanical or stationary equipment. This is not the case. The asset still needs to have hardware and fastener connections tight and be clean, dry, level, well aligned, free from oxidation, and properly protected from environmental attack. In this respect, mechanical equipment and electrical equipment are exactly the same.

There also exists a belief that the preventive maintenance program and the condition monitoring program for electrical assets should be different because of the fact that electricity is flowing through them. This is not the case either. Electrical equipment experiences failure modes just like mechanical equipment. Some of those failure modes are a function of time, some are a function of duty cycles, and some are a function of poor maintenance and operational practices. Just like with mechanical assets. Inspections and time-based activities are required to prevent, detect, or mitigate these failure modes, just like in mechanical assets. So then the concepts of preventive maintenance and condition monitoring are applied to electrical assets the very same way they are applied to mechanical assets.

Preventive maintenance activities fall into one of six types.

Type 1: Inspect. This is the most famous of all of the preventive maintenance activities. Inspections are the staple of any preventive maintenance program. The inspection provides information about the degradation of the defect and determines at what stage the defect is in its failure progression. This information is then used to trigger the planning and scheduling process. All condition monitoring or predictive maintenance (PdM) activities are nothing more than inspections.

Type 2: Clean. This step is usually not thought of as a preventive maintenance activity type, but it absolutely is. Cleaning is an integral part of understanding the condition of the equipment and any defects that may be present, though this step is not necessarily performed by highly skilled maintenance technicians. Most cleaning activities can be accomplished by those task qualified to clean the equipment.

Type 3: Adjust. This activity type usually requires someone to perform a measurement of some kind and then change the settings, clearances, etc. on the unit to bring it back to within acceptable tolerances. This step is often called calibration. Just remember that not all adjustments require measurements. Some machines are equipped with go/no go gauges or similar instruments that negate the need for a measurement.

Type 4: Replenish. This simply means ‘add to’ or ‘top-off’. The most common examples are coolants and lubricants that need to have the reservoirs refilled.  This type is commonly called lubricate, but that leaves out all of the non-lubricant fluids that are consumed in the process and need replacement from time to time.

Type 5: Replace. Some assets have parts with known wear rates or parts that become worn due to cyclic loading. Therefore, the part(s) need replacing periodically. An electrical example of this is the contacts on an electrical starter on a machine that is stopped and started frequently under load.

Type 6: Rebuild. Some assets have multiple parts that fail due to time or cycles. These assets simply require a rebuild on specific intervals.

It should be noted that all of these preventive maintenance activities have to be done on regular intervals for them to qualify as preventive maintenance activities. If they are done on an as-needed basis, then they are simply corrective maintenance activities and do not qualify as preventive maintenance.

After the correct activity types have been identified, the required machinery state must be identified. Machines have five distinct states in which they may be for the PM/PdM activities to take place.

Machinery State #1: Running – Loaded. While the machine is running and material is going through it, then it is considered running-loaded. The percentage of speed and percentage of load is irrelevant. For some electrical equipment, this would mean both potential and current are present in the unit.

Machinery State #2: Running – No Load. The machine is still running, but no material is passing through it. For electrical equipment, this means there is still a potential, but no current.

Machinery State #3: Idled. This means the machine is off and locked out, but no disassembly has occurred.

Machinery State #4: Partial Disassembly. The machine is off, locked out, and minor disassembly has occurred. Minor disassembly could mean that a guard has been removed or an inspection cover has been removed. In essence, the essential operation of the equipment is still possible, though not safely.

Machinery State #5: Disassembled. The machine is taken apart, even if it is only partially disassembled. The essential operation of the equipment is not possible in this state.

Before a PM/PdM technique is chosen to combat a particular failure mode, the activity type and machinery state have to be evaluated. We are looking for the machinery state that is the least intrusive to operations while allowing the activity type that effectively prevents, detects, or mitigates the failure mode.

These concepts are universal as they apply to mechanical, stationary, and electrical equipment.

Andy Page

Andy Page is the Integration Director with GPAllied.  As the Integration Director, he is responsible for combining the philosophies and daily practices of the GPAllied SMEs and Instructors.

Most recently Andy was a Vice President for Allied Reliability and was responsible for the alignment of the daily practices with what was being taught in their Reliability Engineering training classes.  Andy joined the Allied Reliability team in March of 2004.

Andy is well grounded in reliability and maintenance engineering topics with particular emphasis on PdM technologies to include advanced experience in Vibration Analysis and Ultrasonics and Level 2 certifications in Infrared Thermography and Oil Analysis. He is a Certified Maintenance and Reliability Professional (CMRP) through the Society for Maintenance and Reliability Professionals (SMRP).

Andy has an engineering degree from Tennessee Technological University and is a Certified Maintenance and Reliability Professional (CMRP) through the Society for Maintenance and Reliability Professionals (SMRP) and is a Six Sigma Black Belt.

Andy resides in Charleston, South Carolina with his wife and daughter.

Written by T.J. Garten, Regional CBM Analyst

Synopsis

Well pumps in municipal water treatment systems are typically standalone remote installations. The motor starter is usually installed in a manfacturer supplied controller cabinet. The large motor size on this system, 100HP 240VAC, was controlled by an autotransformer style motor controller to allow for efficient start-up power consumption while providing proper torque for the motor to overcome start-up loading conditions. Being at a remote location, physical inspections of the electrical and mechanical equipment is usually performed during or after a service call event. The data within this case study is a result of baseline testing for a new Predictive Maintenance program developed by the customer. The technologies to be deployed were Motor Current Signature Analysis (MCSA) online and Motor Circuit Evaluation (MCE) offline technologies. During the intial connection process, a visual inspection of the motor controller cabinet identified several anomalies that showed evidence of previous overcurrent events and poor troubleshooting practices. The MCSA data documented a high current imbalance (16%) under normal loading conditions. MCA offline data documented a high resistance imbalance as well as a potentially elevated inductance imbalance. Visual inspection of the motor make-up box connections proved these data analyses to be accurate and timely.

Fault

The initial inspection of the motor controller cabinet (Figure 1) showed previous arc-flash evidence on the run contactor. Carbon dust was still on the control conductors, contactor housing, and auto transformer. Also, the CTs on the main starter showed evidence of extreme heat; cracking and melting could be seen in the casings. Lastly, the B phase overload had been replaced with a solid piece of copper. The motor was running at the time of arrival for testing at the site. Initial MCSA online testing was performed. The results were as shown in Figure 2.Upon seeing the 16.26% current imbalance, an opportunity to perform an MCE offline test to verify the findings was requested. The feeder conductors were removed from the contactor lugs to prevent upstream resistance readings from influencing the motor and feeder cable data. The DC voltage selected for the test was 500VDC to maximize the potential for locating insualtion anomalies while staying within the votlage withstand rating of the conductors and motor windings. The offline test results showed a 32% resistance imbalance (Figure 3). Based on this data, a visual inspection of the motor make-up connections and motor isolation testing were requested. The electrical installation included only conduit and wire from the motor controller cabinet to the motor make-up box. This install, as well as isolation of the contactor from the testing circuit, indicated that the source of the high resistance connections, and resulting current imbalance, was either a defective make-up connection or an internal brazed joint. Upon visual inspection of the make-up box, evidence of heat damage to the insulating tape was noted. During the process of motor t-lead and feeder conductor isolation, the additional anomalies of arcing within the connections, corrosion, insualtion embrittlement and damage, and damaged internal brazed joints were encountered. As a result of the brazed joint failure, a rewind of the motor was required.

Summary of Action

Based on the current imbalance and the high resistive imbalance, it was requested that the motor make-up box be inspected for potential connection issues.

The team discovered the following conditions:

1. Heating of connections on B and C phases (Figure 4)

2. Embrittled insulation on motor leads of B phase

3. Broken insulation on motor lead T-1 (Figure 5)

a. Upon further inspection, it was noted that one of the motor leads, T-1, showed evidence of heat damage to the insulation at the point of extreme bending. The motor lead insulation on both T-1 and T-2 were extremely brittle and heat aged.

b. Mismatched lugs were also noted.

4. Broken 460VAC tap brazed joint within motor housing (Figure 6)

a. The end of the conductor had a molten spot in the center of the stranding and the insulation was missing for about 1.5”.

5. Arcing evidence within make-ups of B and C phases (Figures 7 and 8.)

During the next year’s survey, the post repair data confirmed that both the current imbalance and the resistive imbalance anomalies had been corrected by the rewinding of the motor (Figures 9 and 10).

Supporting Data

Figure 1:Motor Controller Cabinet

Figure 3: MCE Offline Test Results

Figure 4: Evidence of Excessive Heating on B Phase Motor Connection

Figure 5: T-1 Motor Lead

Figure 6: 460V Motor Taps, brazed splice failure within the Motor Housing

Figure 7: Evidence of Significant Arcing and Heating Following Removal of Varnish Tape and Electrical Tape

Figure 8: Varnish and Electrical Tape Removed from All Three Connections, Showing Additional Arcing Evidence on C Phase

Figure 9: Post Repairs MCSA Data – Current Imbalance from 16% to 2%

Figure 10: Post Repairs MCE Data – Resistance Imbalance from 32% to <1%

Conclusion

Routine inspection of the electrical components on remote infrastructure installations will add value to the reliability and operational life of these systems. Anomalies such as resistance imbalance are additive in nature, meaning that the number of components within the circuit that are affected by the anomaly increase as the operational time with the defect progresses. A loose or corroded connection can transfigure into a motor rewind, feeder cable replacement, and motor starter controller overhaul as evidenced in this study. Visual inspections, in the least, can identify evidence of heat damage, arcing, insulation fatigue or failure, and electrical overcurrent protection deficiencies within the motor controller cabinet. Utilizing technologies to evaluate the motor circuit’s efficiency and health, such as MCSA and MCE, will allow for implementation of preventive maintenance steps to achieve maximum life out of assets and increase the overall return on investment of these systems.