Archive | 2000

285

3:22 am
December 2, 2000
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The Maintenance Future

Most people know me as a science fiction novelist rather than a maintenance industry expert. As such, I thought a glimpse of the future of maintenance was in order—a glance at a facilities operation in 2012.

Maintenance Manager Mel wakes up and turns on his EU (entertainment unit), a combination of a television, music system, computer, and Internet access rolled into one. As he drinks his first cup of coffee, a streaming download from work appears in the corner of the screen. As he watches the news, he also sees that the third shift has completed preventive maintenance on the HVAC unit in building one.

He also notes that 15 new work orders have come in during the night, most of them generated automatically by the building’s systems. The moisture sensors on the fifth floor picked up a small roof leak, accessed the warranty information, and have already forwarded the work order to the roofing contractor. He has already posted that he will be out by noon to start the work. Two airflow sensors picked up a drop in performance in some of the HVAC equipment and have created work orders based on the data and posted job plans based on the probable causes.

Mel marks these for review by the shift supervisor to pick the best course of action. Before Mel leaves the comfort of his home, he assigns the work orders to the shift supervisors using a Neural Input Device (NID) that he wears on his fingertip. It provides him the capability to use the computer without typing, using his own brain to control the data.

On the way into work he opens a communications link and does a check of his day’s calendar and of the current backlog of work. The system has assigned a number of work orders already to his staff. In the car, he makes some last-minute adjustments. The car is tied to an auto-guide program that sets its speed and literally chauffeurs the vehicle to the office with no human intervention. While he finishes that second cup of coffee, Mel pulls down a copy of the Washington Times to check the sports scores from the night before. He is a little old-fashioned, still going to the news sites rather than the direct data feeds from the teams themselves.

At the office, the maintenance team is already on the job. Each is wearing a tiny device that holds out a small transparent piece of plastic in front of the eye. The device is fitted with a camera and is lighter than a pair of eyeglasses. On the small square of transparent material, an image is projected showing the details of the work order.

What makes the work order so different from old fashioned ones is that it can play video and audio as part of the instructions, all done by voice command from the wearer. It also is linked directly to the manufacturer of both the parts and the equipment itself, pulling down whatever specifications are necessary as well as the exact manufacturing standards. This information is constantly updated and current because it is stored right at the manufacturer, and includes all parts recalls, known problems from other customers, and their resolutions.

As a worker opens the equipment, he notices some burn marks near the circuit housing. Using the camera in the tiny headset, he zooms in on the image and opens a communications link to the manufacturer. A check of known data does not show any probable causes, so the maintenance worker is directly linked to one of the engineers who designed the unit. He can see the image being broadcast and asks the maintenance worker to remove the panel. Inside he sees a burned out board. Asking the worker to zoom in on the part number, he pulls up a feed to the part’s manufacturer. It turns out that a recall was in place on this part. Any damage caused by it is covered by the manufacturer.

An RMA is cut online, while the worker pulls the board and checks inventory to see if there are any others in stock. There is, in a crib across town. He reserves the part and, using the messaging system built into his headset-data feed, asks a runner to go over and pick it up. Using his own finger-worn NID, he updates the work order and includes a video image of the burn marks so if the problem occurs again, no one will have to waste the 15 minutes it took him to track down the problem.

Yes, this sounds like fantasy, but in reality, all this technology exists or is being developed today. NIDs are still in their infancy, but by 2012, they could be reality. The integration of this technology is happening all around us and is in the process of being tested and deployed. The impact on the maintenance operations, as well as the business world as a whole, is not too far away. This passes the era of the smart buildings, and enters the realm of smart departments/companies.

The future is only a click away. MT
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224

3:20 am
December 2, 2000
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Focusing Your Resources

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Robert C. Baldwin, CMRP, Editor

Each fall we survey a sample of our readers to gather information about their pay and how it relates to their age, experience, job responsibilities, industry, and other characteristics. This year’s results are outlined in “2000 Survey of Maintenance Salaries” which begins on page 29. The results are congruent with previous years. Although the numbers change from year to year, patterns remain similar.

We also gather reader opinions in other areas. This year we investigated the relative importance of various reliability and maintenance issues such as installing CMMS, training, predictive maintenance, spare parts management, contract service management, maintenance work planning, safety and environment, and dealing with upper management.

The questionnaire asked the reader to “indicate the relative emphasis or effort being expended by you and your department in the following areas”.

Survey participants were asked to provide answers for their personal effort and for department emphasis using the following scale: 4 = emergency priority, 3 = major effort, 2 = considerable effort, 1 = routine, under control, and 0 = none.

The reliability and maintenance issues on the questionnaire, arranged here in decreasing importance by the simple average of respondent scores, were:

  • Responding to challenging health, environmental, or safety issues. Average score was 1.79, with 29 percent of respondents stressed by major effort (3 or 4) and 49 percent of respondents OK, having this area under control (0 or 1).
  • Improving work planning and job scheduling systems and processes (1.64 score, 20 percent stressed, 49 percent OK).
  • Finding and training reliability and maintenance employees (1.53 score, 19 percent stressed, 47 percent OK).
  • Installing or improving condition monitoring or predictive maintenance systems and processes (1.50 score, 20 percent stressed, 52 percent OK).
  • Developing improved strategies and processes and negotiating with upper management (1.44 score, 16 percent stressed, 54 percent OK).
  • Improving parts procurement and inventory management systems and processes (1.35 score, 13 percent stressed, 59 percent OK).
  • Installing or improving CMMS, EAM, or other information systems (1.25 score, 16 percent stressed, 61 percent OK).
  • Managing and directing contract service providers (1.23 score, 11 percent stressed, 66 percent OK).

By all measures, the spotlight is on safety, health, and the environment. Are you comfortable with your focus? MT

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282

3:18 am
November 2, 2000
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An open window of opportunity

bob_baldwin

Robert C. Baldwin, CMRP, Editor

For years, reliability and maintenance professionals have been complaining, a la Rodney Dangerfield, “we don’t get no respect.” Well, that may be changing. A window of opportunity may be opening to provide some C-level access. Although it may not open wide enough to climb through, it will likely open wide enough for conversation.

That conversation will focus on the goals of the enterprise and how they are to be met. Reliability and maintenance leaders will have an opportunity to respond and possibly sell some best practice concepts that previously fell on deaf ears.

What I have picked up from various conversations with speakers, exhibitors, and attendees at recent conferences (Society for Maintenance & Reliability Professionals and Noria’s Practicing Oil Analysis) and a recent press briefing by Rockwell Automation, is that top management may be ready to listen.

The C-level (CEO, CFO, CIO, etc.) has invested heavily in enterprise level information systems to avoid the effects of Y2K and assure the enterprise has a solid infrastructure on which to base operations in the so-called new economy. Much of this activity has resulted in a flat or negative return on investment (ROI) because not much has happened at the bottom line.

Meanwhile, Wall Street is putting earnings performance under the microscope. Projections must be met or exceeded. Companies are responding by changing their behavior. They are more focused on the bottom line. They are embracing the elimination of waste through lean manufacturing, searching for best practices to assure operational excellence, and freeing up capital by eliminating excess inventory. The term “predictable capacity” is heard.

Return on net assets (RONA) fed by overall equipment effectiveness (OEE) is the primary metric of this new business era. Reliability and maintenance leadership that has done its homework and developed an implementation plan for processes and technology to improve RONA may find an eager ear at the C-level. (If you need a refresher on how reliability and maintenance performance connects to RONA and the bottom line, check out the article links in the box on the first page of our website at www.mt-online.com.)

The C-level will be looking for some quick wins. And reliability and maintenance is in a position to provide them. The installation of best practices can reduce substantially the indirect cost of manufacturing, and that’s what C-level people want to hear.

You better be ready because it many not be hot air that’s blowing through that open window of opportunity. MT

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525

3:16 am
November 2, 2000
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Failure to define failure leads to confusion

Failure modes, failure causes, and failure effects are important concepts in reliability centered maintenance (RCM) and similar processes. Without a clear understanding of these failure terms, the analyses often become confusing and possibly lead to incorrect decisions.

For as long as I can recall, there have been varying degrees of confusion about what people mean when they use terminology that involves the word “failure.”

Failure is an unpleasant word, and we often use substitute words such as anomaly, defect, discrepancy, irregularity, etc., because they tend to sound less threatening or less severe.

The spectrum of interpretations for failure runs from negligible glitch to catastrophy. Might I suggest that the meaning is really quite simple:

Failure is the inability of a piece of equipment, a system, or a plant to meet its expected performance.

This expectation is always spelled out in a specification in our engineering world, and, when properly written, leaves no doubt as to exactly where the limits of satisfactory performance reside. So, failure is the inability to meet specifications. Simple enough, I believe, to avoid much of the initial confusion.

Additionally, there are several important and frequently used phrases that include the word failure: failure symptom, failure mode, failure cause, and failure effect.

Failure symptom: This is a telltale indicator that alerts us (usually the operator) to the fact that a failure is about to exist. Our senses or instruments are the primary source of such indication. Failure symptoms may or may not tell us exactly where the pending failure is located or how close to the full failure condition we might be. In many cases, there is no failure symptom (or warning) at all. Once the failure has occurred, any indication of its presence is no longer a symptom—we now observe its effect.

Failure mode: This is a brief description of what is wrong. It is extremely important for us to understand this simple definition because, in the maintenance world, it is the failure mode that we try to prevent, or, failing that, what we have to physically fix.

There are hundreds of simple words that we use to develop appropriate failure mode descriptions: jammed, worn, frayed, cracked, bent, nicked, leaks, clogged, sheared, scored, ruptured, eroded, shorted, split, open, torn, and so forth. The main confusion here is clearly distinguishing between failure mode and failure cause—and understanding that failure mode is what we need to prevent or fix.

Failure cause: This is a brief word description of why it went wrong. Failure cause is often very difficult to fully diagnose or hypothesize. If we wish to attempt a permanent prevention of the failure mode, we usually need to understand its cause (thus the term, root cause failure analysis). Even though we may know the cause, we may not be able to totally prevent the failure mode—or it may cost too much to pursue such a path.

As a simple illustration, a gate valve jams “closed” (failure mode), but why did this happen? Let’s say that this valve sits in a very humid outside environment—so “humidity-induced corrosion” is the failure cause. We could opt to replace the valve with a high-grade stainless steel model that would resist (perhaps stop) the corrosion (a design fix), or, from a maintenance point of view, we could periodically lubricate and operate the valve to mitigate the corrosive effect, but there is nothing we can do to eliminate the natural humid environment. Thus, PM tasks cannot fix the cause—they can address only the mode. This is an important distinction to make, and many people do not clearly understand this distinction.

Failure effect: Finally, we briefly describe the consequence of the failure mode should it occur. To be complete, this is usually done at three levels of assembly—local, system, and plant. In describing the effect in this fashion, we clearly see the buildup of the consequences. With our jammed gate valve, the local effect at the valve is “stops all flow.” At the system level, “no fluid passes on to the next step in the process,” and finally, at the plant level, “product production ceases (downtime) until the valve can be restored to operation.”

Thus, without a clear understanding of failure terminology, reliability analyses not only become confusing, but also can lead to decisions that are incorrect. MT


Anthony M. “Mac” Smith, San Jose, CA, is a pioneer in the application of Reliability-Centered Maintenance (RCM) to complex plants and facilities. Mac has 47 years of engineering experience, the past 18 of which focused on RCM program installation. He is recognized internationally for his book Reliability-Centered Maintenance.

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914

9:36 pm
November 1, 2000
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A Best Process Model for Asset Management

Significant cultural changes, cost savings, and increases in mechanical availability can be achieved by the implementation of this model.

As many asset-intensive companies have increasingly searched for a competitive advantage, maintenance and reliability of assets have evolved as major contributors. Organizations are being challenged to improve efficiency and work with less. Various processes, such as reliability-centered maintenance (RCM), have been implemented throughout the years as part of improvement initiatives with varying degrees of success. Many of these initiatives result in some progress toward enhanced reliability of assets, but, to achieve world-class performance, a fundamental shift in the mindset of workers and the nature of work is needed. A holistic and evergreen approach to asset management processes provides the capability to change the nature of work and drive a reliability-centered culture.

The model presented here integrates “best” processes to create a world-class approach to asset management. It is illustrated in the accompanying diagram, which is divided into separate processes and sub-processes and shows the high-level flow between each. Criticality ranking, front-end failure analysis, equipment reliability strategy development, equipment reliability strategy implementation, work management, reliability analysis, and external processes comprise the model.

Elements of the model
The Asset Management Best Process Model provides the elements necessary to support a world-class asset management program. Many organizations have done a reasonable job at defining and executing standard business processes for work management. This is most often driven by a computerized maintenance management system (CMMS). The majority of new processes implemented by world-class performers have been proactive, reliability-focused processes and post-execution reliability analysis. Some organizations may find improvement by focusing on traditional work management, but to see quantum and long-term improvements, companies must implement these other processes.

A reliability-centered model for asset management seeks to better understand assets before failure, put in place proactive equipment reliability strategies to cost-effectively eliminate the likelihood and consequence of failures, and move toward an environment where the only equipment failures will be pre-determined and due to wear-out.

The Criticality Ranking Process is used to better understand and identify assets that are truly critical to the business. This process is essential to a cost-effective approach to implementing the model.

This provides the basis for focusing personnel and other resources on the equipment that has the most direct impact on the business. For instance, as a company prepares to roll out its RCM process or any other improvement initiative, this process guides the organization to that area of the facility where it should focus its efforts, along with the specific assets within that area that deserve the most attention.

Equipment identified as “critical” then enters into the Front-End Failure Analysis (FEFA) process. The FEFA process includes traditional RCM elements including identifying functional definitions for equipment (or groups of “like-kind” equipment), functional failures, failure modes and causes, and the expected functional life. The FEFA process is not dependent on equipment history, although comprehensive performance history and analyst experience will allow for better analysis and results.

Equipment Reliability Strategy Development is the natural extension of the Front-End Failure Analysis process. Equipment Reliability Strategies (e.g., one-time tasks, preventive maintenance (PM), predictive maintenance (PdM), etc.) then are developed for “critical” equipment and focus on the detection, mitigation, and/or elimination of the expected failure modes. The strategy’s intent is to ensure the equipment continues to perform its intended functions for the expected functional life, within its current operating context.

Existing PM/PdM tasks, original equipment manufacturer (OEM) maintenance recommendations, and regulatory constraints will provide the basis for the strategies, but they often are improved based on a better understanding of the equipment gained through the analysis. For “non-critical” equipment, “template” equipment reliability strategies can be developed that provide a base strategy for optimal performance (most often defined by equipment type).

A key element of this model, which is often overlooked, is the Equipment Reliability Strategy Implementation process. A considerable amount of work is required to perform the front-end analysis and to develop equipment reliability strategies. Depending on the scope of assets involved and how well technology is leveraged, there also can be a sizable amount of work involved with implementation of the strategies’ tasks. Once a strategy’s tasks have been determined, the best implementation approach must be selected.

For instance, if the strategy calls for a recurring type of condition or process monitoring, a decision must be made whether it can be automated or not, whether it could or should be performed as part of an operator’s round, or whether it should be part of a PM or other mode of implementation. There also will be opportunities to bundle tasks with consistent scheduling intervals so they can be handled more efficiently as one work effort.

The Work Management process in this model is extremely critical. Many organizations have focused on work management excellence, but in a “reactive” environment. The philosophy in a “reactive” environment is to “fix it when it breaks.” This philosophy usually rewards personnel for making quick repairs at the sake of preserving evidence, understanding the cause, and updating the strategy to prevent the occurrence of that failure in the future. Elements of a traditional maintenance organization such as high percentage of reactive work, constant breaking of the schedule, little if any root cause investigation, minimal amounts of PM/PdM tasks, etc., are undeviating and perpetual. The prospect for breaking this “reactive” cycle is poor until an integrated process, focusing on proactive work, is established.

There is and always will be a place for fast and efficient repairs. However, the work management process in this model places the focus on other elements. Better work order prioritization methods based on criticality can be deployed. Proper analysis of the situation using nonintrusive condition monitoring can eliminate or delay unnecessary work. Inventory and spare parts can be forecast better through the understanding of equipment criticality. Forward-looking schedules can be planned and met. More PM/PdM tasks will be performed replacing “reactive” work. Better equipment history can be documented, providing valuable information necessary for failure and reliability analysis.

The Reliability Analysis process utilizes observed equipment behavior and compares it against the expected failure effects and modes identified as part of the FEFA, thus creating a continual or “evergreen” improvement process. This results in “evergreen” reliability strategies that are continually customized to ensure optimal performance for equipment.

The ultimate result of the “evergreen” process is to move toward an equipment-specific reliability strategy for each equipment item based on its actual performance. It is not likely that anyone would ever get to that point nor would it necessarily be prudent or cost effective, but the process provides a path to continually evaluate the actual observed conditions and create the optimal equipment reliability strategy for each asset.

This process enables the equipment reliability strategies to continually move away from a theoretical model to a realistic one based on actual performance. In other words, equipment covered by a template or equipment-group strategy will utilize the template strategy tasks as long as they are providing optimal performance. As observations are recorded, whether good performance, failures, degradation, or any other relevant information, the process provides a path to further customize the template or equipment-group based tasks to the individual equipment they are supporting, migrating from template to equipment-group to equipment-specific reliability strategies.

There are various types of reliability analyses that can be utilized. The “evergreen” process most often is triggered by a failure or other event. However, another aspect is to perform continual “ad hoc” reliability analyses. These can include the basic types of reporting such as Pareto or worst actor charts. As observed history becomes more accessible and accurate, advanced statistical modeling, such as distribution and trend analysis, can be used.

The Asset Management Best Process Model also identifies a number of important External Processes. These processes can (and many do) operate regardless of the status of this model. Each is considered important to the reliability of assets. The more integration with the external supporting processes, the better the overall enterprise asset management program.

Throughout the life of a facility, there are various Environmental/ Operational Factors that impact the Asset Management Best Process Model. The model must be flexible to respond to these factors, which include changes to business strategy, production targets, feedstock/raw material, regulatory compliance, etc. The entire model, its processes, and resulting data should be evaluated for validity upon the introduction of these factors.

For example, it is not uncommon for petroleum refiners to change their crude slate over time. In most cases, the plant was built originally to refine a “sweet” crude. If they make a decision to start using “sour” crude (indicates changing chemical composition of the crude), this has an effect on the type and frequency of deterioration expected by the equipment. With that in mind, equipment reliability strategies should be reviewed and optimized based on the expected impact of the different factors.

Implementation
The model provides the vision and the processes required to support a leading-edge asset management program based on our experiences in various asset-dependent industries and organizations. It is crucial that the implementation of this model be based on the individual needs of each organization. Each organization must evaluate how to best leverage the processes indicated in the model to meet its own strategies, goals, and objectives for asset management.

Implementation of this model also must take into account the effort required to optimize value as quickly as possible. The model, as represented, indicates a continual process, which over the long term can provide significant benefits. To see a quicker realization of benefits, implementation of certain prerequisites is necessary. These prerequisites include a short-term focus on work management basics and initial performance of the proactive elements of the model (e.g. criticality ranking, front-end failure analysis, and equipment reliability strategy development and implementation). Without the proactive elements in place for “critical” equipment, the value of the “evergreen” process is diminished.

Critical factors for successful implementation of this model include:

  • Progressive vision for excellence
  • Long-term commitment
  • Short- and long-term objectives and goals (Key Performance Indicators)
  • Build up basics while extending the model
  • Leadership
  • Communication
  • Training
  • Ownership and empowerment throughout the organization
  • Technology

Benefits of the model
Significant cultural changes, cost savings, and increases in mechanical availability can be achieved by the implementation of the Asset Management Best Process Model. Short- and long-term benefits can be expected. Adoption of this model will provide the following representative benefits:

  • Common vision for world-class asset management
  • An excellence model to train all personnel involved with asset management
  • Breakdown of departmental barriers and elimination of conflicting priorities traditionally found in organizations with a “reactive” culture
  • Migration from “reactive” to “proactive and planned” reliability-centered work and culture
  • Avoidance of significant events due to preventive tasks and predictive monitoring
  • Increased mechanical availability/ decreased lost production opportunities
  • Decreased maintenance and production costs
  • Identified areas of focus for reliability improvement

Enhanced reliability of assets is a critical element in the survival of today’s organizations. This recognition has brought forward the question of how to improve maintenance and reliability of assets while simultaneously freezing or trimming the maintenance budget. There are many sound methods and technologies that individually can provide significant incremental cost savings.

However, to reach quantum and long-term improvement, a change in mind-set and work is required. The reality is that this is a journey, not a destination, and unfortunately, there is no “holy grail” which will work for everyone. World-class performers are continuously pushing the envelope. Therefore, all organizations must continuously search for long-term improvement opportunities. Organizations that adopt a holistic and evergreen model such as the one presented here will set the marks for asset management excellence as we move into the 21st century.

Future articles will deal with the processes presented in this model, their interactions, and the controls an organization must provide to facilitate progress. It is our opinion that the key to world-class performance is to select and integrate the best practices available and adapt them to each organization’s needs. MT


Darrell Ferguson is a senior consultant and services delivery manager within the Asset Management Consulting Group at Plumlee Associates, Inc., 2638 S. Sherwood Forest Blvd., Suite 200, Baton Rouge, LA 70816; (225) 292-4464

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379

10:07 pm
October 5, 2000
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Infrared Inspection Methods and Data Collection Techniques

As infrared cameras get cheaper and easier to use and become more widely used, there is a risk that some people will buy an infrared camera and call themselves thermographers. Owning an infrared camera does not make a person a thermographer any more than owning a stethoscope makes one a doctor. In addition to the infrared camera and digital camera, there are three essential tools needed for the professional thermographer: training, field experience, and standard methods for conducting infrared inspection.

There are several good training companies that can do a good job of explaining why training is essential for a professional thermographer. Therefore, this article will address infrared inspection methods: what to test, when to test (scheduling), equipment prioritization, additional factors, and data collection methods. The last section will show reports and the analysis that can be derived when standard data collection methods are followed.

What to test and when?
The first question, What to test?, is answered by using or creating an equipment inventory as the cornerstone for infrared inspection accountability. The equipment inventory can be recorded on paper during the inspection and then transcribed into a spreadsheet or database. It can be printed from an existing computerized maintenance management system (CMMS), or it can be entered into an infrared database program while the inspection is being performed. Without an inventory, the thermographer cannot account for what was tested and what was not. A piece of equipment can go for years without being tested if no inspection record is kept. A company hiring a thermographer should receive an inventory report of equipment tested and not tested. It costs very little to build the inventory, and the benefits far outweigh the costs in the long run.

By recording the test status of each piece of equipment in the inventory list during the inspection, the thermographer can answer the question, What did you inspect? To provide full accountability, test status information should include the following points:

  • Current test status
  • Date the equipment was last tested
  • Results of the previous test
  • Reason equipment was not tested during the last inspection (if it was not)
  • When equipment is due to be tested again, if not tested this time.

An example notation currently used in the field for test status of equipment is as follows:

TBT: To be tested. Starting test status for all equipment.
TESTED: Tested.
NTNL: Not tested, no load. Commonly seen, because not all equipment can have a load during the inspection
NTTC: Not tested, time constraint. Scheduled to be tested but time ran out
NTNS: Not tested, not specified. Not scheduled to be inspected this time
NTUR: Not tested, under repair.

Once an inventory has been created, it is advisable to assign a criticality to the operations value of each piece of equipment. This procedure helps prioritize equipment for testing schedules and repair priority when a problem is found.

The following list can serve as a basis for developing a site-specific equipment criticality-to-operations list and the corresponding inspection frequency set for each.

  • Crucial criticality: Inspect every 3 mo
  • Essential criticality: Inspect every 6 mo
  • Nonessential criticality: Inspect once a year
  • Followup on problems or repair: Inspect every 3 mo

Once an inventory has been set up and inspection test statuses have been integrated, the infrared program has accountability. When the criticality to operation criteria have been added, a prioritized inspection schedule and repair list is ready. Bar-code labels on the equipment can be helpful in streamlining equipment inventory management. Without a basic equipment inventory, there is no accountability, no prioritized inspection scheduling, and no reliable infrared program.

What pertinent data should be recorded?
Once an inventory has been set up and the equipment to test has been determined, the next questions are, Besides recording the temperature of the problem and the reference, what other information is pertinent and should be recorded? Other than the emissivity value that the camera stores, what factors could greatly influence temperature measurements?

One factor is the equipment load; whenever possible it is important to measure and record load data. As Bernard Lyon stated in a paper presented at Thermosense XXII, “Temperature is certainly an important factor in evaluating equipment. However, if you follow the guidelines that are based solely on absolute temperature measurement, or on a temperature rise (DT), you run the risk of incorrectly diagnosing your problems. The consequences of such actions can lead to a false sense of security, equipment failure, fire, and even the possibility of personal injury.”

Another factor that should be recorded is wind speed. As shown in the wind effects experiment done by Robert Madding and Bernard Lyon and stated in their paper presented at Thermosense XXII, “The temperature rise was cut in half with just a little over 3 mph breeze.” The options available include buying a $100 anemometer to try to accurately measure wind speed or picking up grass, dropping it, and estimating wind speed. Either way, in most cases, the wind speed will have to be an estimate because even an anemometer will be some distance from the equipment being inspected. This condition is especially true regarding power lines. The important point is to account for wind speed by the best available means and record it. This information is especially crucial if baseline trending is being done on a problem.

Another notable factor is environment. Was it a hot sunny day, rainy, snowing, or clear but freezing? Environmental factors such as solar loading or a cold rain can affect temperature measurements. Again, this information is especially crucial if baseline trending is being done on a piece of equipment located outdoors. What was the weather like the last time the inspection was done? How does this information correlate to the temperatures measured?

Equipment load, wind speed, and environment are not the only factors that are important to note when a problem is documented. Other information that is less important to the thermographer but may be more important to management is the manufacturer and type of fault for each problem found. This information allows reliability to be analyzed by manufacturer or equipment type. By comparing the cost of repairing observed problems, a maintenance manager can look at the impact by manufacturer on the total operating expense of a facility. This information, in turn, can be used to improve future buying decisions.

Data collection techniques
The infrared camera is just a tool, and the thermogram is just the starting point in the data gathering process. The next step is to establish methods to ensure efficient, accurate data collection. These methods should have built-in procedures to guarantee that data quality is consistent from inspection to inspection and from thermographer to thermographer. These methods must not impair the pace of the inspection but should help in expediting the collection of data and aid the thermographer in his ability to diagnose problem conditions in the field.

For many years, the simplest and cheapest way to record data has been manually on paper. If this method is used, preparing preprinted problem write-up sheets with blank data fields will increase consistency and standardize problem write-ups. When used with an inventory list produced by a spreadsheet program or a CMMS, the write-up sheet is the starting point of a standardized infrared inspection system. This method of manual data collection works if labor costs are relatively inexpensive. Another method that has been used for many years is recording problem write-ups with a voice dictation recorder.

Although these methods are convenient, there are pitfalls to using either method. In both instances, there is the risk of losing data and introducing errors from misinterpreting field notes when typing up the reports at the office. Furthermore, the thermographer in the field does not have in his hand the analysis of past problems and other information when it would be of most value to him.

With the advancement of pen computers and database software, a third method of data collection has evolved. Instead of trying to bring field data back to the office and enter it into a database on the computer, the technician brings the computer into the field to enter the data directly into the database during the inspection. This advancement has proved to be the most reliable method of data collection available today, as well as the most cost-effective solution over time.

One efficiency of the mobile database is the instant turnaround time of report generation. Because all of the necessary information is put into the database at the time of the inspection, the reports can be printed immediately at the end of the inspection. Using a pen computer with an infrared database in the field, a thermographer can double the number of problems written up in a day (from 50 to 100) and completely eliminate report generation time.

The following comparison of paper or voice dictation method to pen computer with IR database method lists typical inspection and report generation times. Report generation includes inventory of equipment and associated test statuses, prioritized list of problems, and documentation.

Paper or voice dictation method

  • 50 problems per 8-hr day
  • Report generation takes 6 hr
  • Total: 50 problems in 14 hr

Pen computer with IR database

  • 100 problems per 8-hr day
  • Report generation automatic
  • Total: 100 problems in 8 hr

Another efficiency of a database on a mobile pen computer is its ability to yield more consistent inspection results because testing procedures can be methodically followed. Key information can be selected from drop-down menus. Past problem conditions on a chronic problem are immediately displayed and can be reviewed in the context of the new problem. Furthermore, the redundancy of data collection can be eliminated because information that was stored in the past, such as location, does not need to be re-entered into the database. Maps, work orders, inspection procedures, and other pertinent documents can be brought into the field because the database also can work as an electronic document management system.

Now that the inspection has been completed and the data have been collected, what analyses can be formed from following these methods? The software to ensure write-up consistency is extremely efficient; it eliminates typing and syntax problems while improving data accuracy. This method has many benefits over conventional methods because data are entered only once.

Management reports and analysis
The analysis outlined in “Problem Profile Report: Key Equipment Failure Ratios,” is from data collected for more than 10 years using the Thermal Trend Infrared PdM Inspection Management Database. Actual client and manufacturer names and specific products have been omitted to protect the clients and manufacturers. Data were collected from all over the world on many manufacturers’ equipment and in all kinds of plant environments. The data included in this analysis come from hundreds of thousands of problems and pieces of equipment.

Tracking problems and categorizing them by their temperature rise reveals trends in facilities’ health over time. Average temperature rise using all of the electrical problems documented in the database for electrical inspections as measured phase to phase is 54 deg F.

Problems in the database can be analyzed and ratios can be established for specific faults on key equipment by recording manufacturer and type of failure. This strategy leads to the ability to study the equipment thoroughly and analyze what factors play an important role in their failure, for example corrosion, overloading, or just a substandard piece of equipment. This analysis provides insight into the correct preventive maintenance measures to be taken so future problems will be minimized.

A cost breakeven report can be generated from materials and labor by recording equipment and labor costs before vs. after using an infrared inspection program. For example, 976 problems were documented at 55 industrial manufacturing sites. A cost-benefit analysis on the 976 problems shows a before vs. after failure savings on materials and labor of $408,040. The average cost saving per problem, if it is fixed before it fails works out to $418.07 for material and labor . This figure is very conservative and does not take into consideration the potential loss to revenue or to production, or the risk of financial loss from a major fire.

Analyzing cost savings reveals measurable results from implementing an infrared inspection program. On average, for every $1 spent on hiring a competent professional consultant to perform an infrared electrical inspection, there is a $4 return on investment for materials and labor to fix the problem equipment identified before it failed. This conservative 1:4 ratio clearly identifies the importance of maximizing the return on investment of implementing a comprehensive in-house or outsourced infrared inspection program. Furthermore, because of reduced losses and increased productivity, which in turn increase revenue, the return on investment ratio in some cases is closer to 1:20, depending on the industry.

Whether a thermographer uses a pad of paper or a pen computer, the data and methods followed are important to creating a standardized infrared inspection management program. Sufficient training and field experience cannot be emphasized enough as a basis to build a solid infrared program. Once components are in place, it is important to implement strong data collecting methods to get standardized results across multiple inspections and multiple thermographers. By recording appropriate supplementary information such as load, wind speed, and environment in addition to the thermographic image, a thermographer can better assess the severity of the situation.

By setting up a standardized infrared inspection program, tracking the pertinent information, and recording it consistently, a plant can manage and see the trends in the overall health of the facility. There is a wealth of information to gain by using these methods in a comprehensive infrared inspection management program. MT


Scott Cawlfield is president of Logos Computer Solutions, Inc., 3801 14th Ave. West, Seattle, WA 98119; (206) 217-0577.

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3:13 am
October 2, 2000
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No Excuses

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Robert C. Baldwin, CMRP, Editor

I had the opportunity last month to meet with the Maintenance Excellence Roundtable and tour the plant of this year’s host Dofasco, said to be the most profitable integrated steel maker in North America. The Maintenance Excellence Roundtable is a group of companies that meets once a year at a member plant to network and share best practices. Other members, in addition to Maintenance Technology, are Alcoa, Baxter Healthcare, Conoco, Dupont, Exxon/Mobil, Honeywell, Kodak, Novartis, Sonoco, and the U.S. Postal Service.

One of the more impressive parts of the tour of the Dofasco site in Hamilton, ON, was its electrical repair shop, a 25,000 sq ft facility where approximately 2500 motors and generators, plus 450 electrical breakers, are serviced each year. The operation, which is QS9000 certified and employs a staff of 42 people, has an annual budget of $5 million.

Realizing that equipment reliability was vital to improving product quality, production output, costs, and shareholder return, Dofasco managers initiated a strategic project in the early 1990s to research, develop, and implement the most advanced maintenance practices and information technologies to achieve maximum equipment reliability (the process is outlined in the article “Achieving Maximum Equipment Reliability” on page 28).

The motor repair shop is recognized as a core competency in the Dofasco asset management strategy. It produces an estimated repair work cost saving of $1.5 million per year and directly affects equipment reliability in the mill.

The shop emphasizes comprehensive record keeping. A new system now being rolled out will use a bar coding system driven by handheld data loggers to obtain real time motor data during the repair process. The system contains nameplate data, performance data, test and repair records, and reliability information on motors that affect manufacturing equipment reliability. Such information is a prerequisite for making informed business decisions about motor management.

Yes, most plants don’t have the wherewithal to invest in motor management anywhere near the scope of the Dofasco program. But that is no excuse for not managing electric motors to provide reliable and energy efficient systems. The motor data to begin a program can be downloaded for free over the Internet. The article “Electric Motor Energy and Reliability Analysis” on page 17 provides the details.

If there is a valid excuse for not managing electric motors, I don’t know what it is. It certainly isn’t the expense of obtaining motor reliability and performance data. MT

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3:11 am
October 2, 2000
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The Basic Pillars of Total Productive Maintenance

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Robert M. Williamson, Strategic Work Systems, Inc.

Total Productive Maintenance (TPM) can be defined in many ways to suit the unique needs of a company or industry. But most of the universally accepted definitions of TPM build on the basic five pillars of TPM from the Japan Institute for Plant Maintenance. For TPM to be successful ALL of the pillars, or key elements, must be used to eliminate equipment losses in a sustainable manner.

TPM Key Element 1: Improving equipment effectiveness by targeting the major losses. TPM activities should focus on results. One of the fundamental measures used in TPM is Overall Equipment Effectiveness (OEE) which includes the major losses that TPM seeks to eliminate. OEE = Equipment Availability x Performance Efficiency x Rate of Quality.

TPM Key Element 2: Involving operators in daily maintenance of their equipment. Operator involvement must be defined in ways that make sense in your work culture. There are tasks that operators can do without using any tools: Clean and inspect equipment. In every company that I have studied or visited or worked for, the thing that they get the most return on investment in the early stages of TPM is operators learning how to inspect their equipment and pay attention to key things. It doesn’t take any tools or special skills; you just have to know what to look for. Maintenance people can teach the operators what to look and listen for.

TPM Key Element 3: Improving maintenance efficiency and effectiveness. This means improving all aspects of maintenance including spare parts, computerized maintenance management system, preventive maintenance, predictive maintenance, maintenance tools, work order system, planned and scheduled maintenance, and equipment histories. These are all part of TPM. They can’t be separate or on the side. They must be woven in. For example, production, maintenance, purchasing, and shipping and receiving should use a computerized maintenance management system. It’s not just a maintenance management system anymore; it’s an equipment information management system.

TPM Key Element 4: Training to improve the skills of everyone involved. This means maintenance training, operations training, leadership training, training about root cause analysis of the major losses, reliability training, etc. The training should first address the very basic needs of the people and the equipment targeted for TPM. One of the most important basic training needs for TPM is designed to help the people involved understand what TPM is and why it is so important for the equipment and the business.

TPM Key Element 5: Life-cycle equipment management and maintenance prevention design. If you’re going to design and develop new equipment or a major modification, involve those who are going to operate it and maintain it for the next 5, 10, or 15 years in the process. Use their ideas to make it easier to operate and easier to maintain.

Based on the past ten years’ experience with TPM in America, a sixth key element is needed to truly recognize what is making TPM work. It is:

TPM Key Element 6: Wining with teamwork focused on common goals. Even with all of the emphasis on high-performing equipment the best equipment cannot consistently perform well without teamwork focused on common goals using common processes. In some facilities “Team” is a four-letter word that is often misunderstood. In TPM the sense of teamwork centers around the targeted equipment, then expands through all areas using TPM to improve their performance.

One of the biggest misunderstandings about the pillars of TPM deal with the first pillar–Improving Equipment Effectiveness by Targeting the Major Losses—and its relationship to the other pillars. All TPM activities, including the remaining pillars, are designed and developed to be measured by the first pillar. If a TPM activity does not result in, or contribute to, improved equipment effectiveness then we need to ask “Why are we doing it?”

TPM is a powerful but often misunderstood strategy for eliminating equipment-related losses. In Lean Manufacturing this translates into eliminating equipment-related “wastes.” Go for sustainable bottom line results with TPM and change the culture along the way by using all of the pillars of TPM the way they are intended to be used. MT
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