Robert C. Baldwin, CMRP, Editor

I related his comment to the predictive maintenance technicians in each audience, asking: How does that make you feel? What is a guru, anyway? Do you really want to be one? Is that good or bad? For the second question, I had a ready dictionary answer:

gu·ru Hinduism. A personal spiritual teacher. 1. A teacher and guide in spiritual and philosophical matters. 2. A trusted counselor and adviser; a mentor.

Some of my remarks, I hope, contained an idea or two that would help members of the audience to answer the other questions for themselves.

I wish I would have had the foresight to discuss the issue further with the maintenance manager who made the guru comment. What did he mean by guru? And did he think a guru was good or bad? From his tone, I assumed he equated guru to an expert with an attitude.

There are a number of functions or roles in an effective condition monitoring or predictive maintenance program. Guru is just one. Others that come to mind are champion, user, analyst, and field technician.
The field technician makes the inspections and collects the data and samples to be studied by the analyst, who makes recommendations to the user, who will cause the maintenance organization to take appropriate action on the information. The champion is the person who may have introduced the concept and currently supports it with enough strength to keep it going. The participants' knowledge is derived from the teacher, expert, or guru.

These functions may be fulfilled by a team or a single person, by in-house personnel or an outside service organization, but they must be fulfilled and be part of a rational process if condition monitoring is to be successful. Some valuable guidance on how to make the process work is covered by Jack Nicholas and his associates in the article on Strengthening Your Predictive Condition Monitoring Program (page 12).
In my mind, to become a guru is a worthy goal. The true guru is wise enough to know that all the functions must be fulfilled, even if they have to be done by the guru himself. MT

Bob Williamson

When lean gets interpreted as downsizing by many of today's business leaders, they make the mistake of reducing headcount in their organizations to make them leaner from a staffing perspective. Well, that is not the intent of lean.

A fundamental characteristic of a lean organization or lean manufacturing is the systematic identification and elimination of waste to reduce manufacturing or operating costs. Targeted forms of wastes are associated with overproduction, transportation, motion, inventory, processing, defects, and waiting.

Unreliable equipment also represents a significant waste--extra inventory to compensate for breakdowns; extra backup equipment; processing delays due to unplanned downtime or inefficient performance; defective materials produced due to breakdowns; waiting for information, parts, and materials to make needed repairs; or waiting caused by inefficient equipment operation. Eliminating equipment-related wastes (or losses) is fundamental in achieving the goals of lean.

If the organization's leadership assumes that lean means fewer people and begins reducing headcount without eliminating, or at least reducing, equipment-related waste, an upward cost spiral begins. With fewer people to respond to equipment problems, or to perform required preventive maintenance, equipment performance levels and reliability suffer even more. This approach can actually increase manufacturing or operating costs rather than reduce them.
Downsizing and lean are not the same! Downsizing, without eliminating waste, is typically not sustainable. Rather, it is a one-time, short-term cost reduction strategy that if left alone will likely lead to increased costs.

So, what are the correct methods for becoming lean in a sustainable manner? Begin by identifying the types, reasons, and root causes of waste that have a direct and immediate impact on business performance. For equipment-related wastes be sure to involve the people closest to the problems--maintenance and reliability (repairs and prevention), operations/production, purchasing/stores (repair parts), and engineering/technical (design and modification). Identify and eliminate the causes of poor performance using formal problem identification and root cause analysis methods.

This takes data. Some organizations have excellent data, which makes this step easier; with very sketchy data, this step is difficult. In the absence of data go with what you know. Baseline the targeted equipment performance measures and then begin collecting data to measure equipment performance and if improvements are actually being made.

Identify action items to correct and eliminate the root causes of poor equipment performance. Look at equipment conditions and data. Look at work processes and procedures used to operate, maintain, and document changes, control quality, communicate, and schedule anything to do with the targeted equipment. Consider the people who directly, and indirectly, affect the performance of the equipment--their qualifications, training, and numbers.

What then are the essential elements of becoming lean in a manner that is sustainable?

• There must be a clear and compelling, and urgent, reason to change.
  
• Cross-functional leadership must proactively and visibly lead the organization through the change process.
  
• Leaders must continually communicate, and role model, the new vision and strategies.
  
• Leaders must break down barriers to making necessary improvements.
• Leaders must engage the people closest to the top priority problems or opportunities to identify, design, develop, plan, and implement improvements.
• Leaders must leverage the successes and key learnings for making improvements by eliminating waste in other areas.
• Leaders help everyone in the organization understand the connection between the improvement activitires and results with the vision of the organization so the new behaviors become part of the "way we engage our prople and run our business."

Those of us in maintenance and reliability roles can help organizations become lean by targeting equipment-related wastes and keeping our business and labor leaders informed of the results. MT

Robert Williamson of Strategic Work Systems, Inc., Mill Spring, NC, is an author, workplace educator, and consultant with more than 27 years' experience in improving the prople side of manufacturing and maintenance with many fortune 500 companies.

Condition monitoring (CM) and computerized maintenance management systems (CMMS) have evolved and coexisted as separate disciplines. Many efforts have been made to integrate CM and CMMS with nominal success.

Conceptually, CM and CMMS have different functions and their applications yield different results. Understanding these roles provides significant insight into the benefits of an integrated system. In general, the role of CM is to implement a maintenance strategy and the role of CMMS is to manage the execution of maintenance. These separate disciplines have been successfully practiced for years, each on its own merits with relatively little knowledge or interaction with the other. When considered as an integrated whole, it becomes clear there are exciting possibilities for greater benefits.

Benefits of integration
The integration of CM and CMMS provides clear opportunities including:

• More effective and automated implementation of maintenance strategy. Research has shown that condition-based maintenance provides the lowest maintenance cost and highest availability for many plant assets. In practice, these benefits can be elusive. Effective communication of CM recommendations and tracking the results provides a powerful tool to support complete realization of the CM benefits. Meaningful communication between CM and CMMS provides automatic, paperless execution of CM, minimizing man-hours and increasing effectiveness. This connection between the systems allows a maintenance strategy based on machinery health to be institutionalized as a part of the user's business.
• Improved accuracy of CM analysis. Communication of information between CM and CMMS improves CM analysis in two important ways. First, it allows the analyst to observe the work history of the machine being analyzed. Armed with this knowledge, the analyst can recognize the difference between a new bearing that may produce high readings as it wears in and an older bearing that will produce high readings as it degrades. Most maintenance actions will impact CM measurements, and understanding this work history results in dramatic improvements in CM analysis.

The second improvement in CM analysis is from systematic feedback on CM recommendations. The two most important outputs from CM are diagnosis and prognosis. Diagnosis identifies what is wrong with the machinery, and prognosis estimates how bad the condition is or, ideally, answers the question, How long will it last? With an integrated approach to CM and CMMS, CM recommendations are tracked and the actual findings documented. This provides a tool to confirm the diagnosis and prognosis that CM generates. Prognosis based on CM information is not an exact science and it will depend on the site-specific application of the machinery. Tracking CM recommendations and supporting them with factory floor or shop observations is a powerful tool for improvement.

• Identification of repetitive failures for root cause analysis. At many plants, the biggest savings opportunity is designing out repetitive failures. In most cases, this doesn't happen because these repetitive failures either are not noticed or are tolerated by an adaptive maintenance philosophy "Oh yeah, that machine breaks every six months." CM alone can be very effective at identifying this problem and CMMS can make fixing it efficient. When the two work together, the repetitive nature of the problem and the associated costs become apparent. The measurement tools used for CM also often can be applied to study a repetitive failure and identify its root cause for design-out consideration.
• Effective communication of machinery health throughout the enterprise. Availability of machinery health information from the CM system throughout the enterprise creates the opportunity for significant benefits in production, engineering, and other business segments. When this understanding of machinery health becomes institutionalized, production schedules can be optimized, selection and design of plant machinery improved, and maintenance practices fine tuned. Providing the tools for continuous improvement of plant operations, generally, and the maintenance function, specifically, is the biggest benefit to integrating CM with CMMS.

How these systems work together
The premise of CM is that carefully selected measurements made on a regular basis can show machine condition accurately. With this understanding of machine condition, specific maintenance actions can be carefully planned. Maintenance interval and machine availability are optimized, driving maintenance costs down and production up. The CM domain has evolved in a technical fashion wrapped around measurement technology. Measurements can range from simple parameters such as temperature, pressure, or flow to complex data such as vibration spectra or infrared images. In all of these cases, the objective is to determine what is normal for the machine, how much change is allowable, and what the changes indicate. In practice, CM has a well-developed vocabulary and data set including:

• Plant machinery hierarchy
• Criticality
• Measurement locations
• Measurement definitions
• Measurement interval
• Severity
• Alarm status or exception
• Trend
• Spectrum
• Time waveform
  
• Thermographic image
• Frequency component
  
• Diagnosis
  
• Prognosis CMMS

CMMS also has been practiced for decades. It is an information-intensive application offering significant benefits through gathering and distributing information about the maintenance function. Managing maintenance information has been a driving force in this development. CMMS also has a well-developed vocabulary and data set that includes:

• Plant machinery hierarchy
• Work requests/orders
• Work plans
  
• Work schedules
• Labor resources/costs
  
• Parts inventories/costs
  
• Storage locations
• Preventive maintenance actions
• Purchase requests/orders
  
• Safety procedures

Creating an intelligent connection
It is ironic that two disciplines such as CM and CMMS that are practiced, in many cases, by the same people fulfilling their assigned duties, have such little overlap in the data they handle. In fact, the biggest overlap is probably plant assets, represented within both systems as a machinery hierarchy. Unfortunately, these hierarchies usually develop at different times to fulfill different purposes and they have little direct connection. The challenge in achieving greater efficiencies through connecting these systems begins to emerge. Although there are visible synergies to pursue, in most cases there is no inherent commonality between the systems. Each of these tools operates in a different domain with different data of interest and vocabularies.

Failure to recognize this challenge has been one of the root causes for the limited success of many efforts to integrate CM and CMMS. In order to address this effectively, it is necessary to effectively connect the shared data between these systems and establish new methods for the systems to exchange other information that will allow users to realize the potential benefits. The approach presented here establishes these new types of information and relationships between the systems:

• Connection between the machinery or asset hierarchies of CM and CMMS
  
• Creation of a new CM result known as Advisory
  
• Creation of work requests based on Advisories
• A gateway to automate communication between the systems
  
• Tracking work requests within the CM system
• Display of equipment histories and work plans within the CM system

The role of people
The integration of the business processes needs to be driven by the organization and its business requirements, not the software. The organization should, however, take into consideration the functionality within the software and database platforms in order to achieve integration as simply and straightforwardly as possible. Although it is a common objective to minimize the human effort required, integration does not necessarily mean without human intervention.

The integration presented here recognizes the expertise of the CM analyst and CMMS maintenance planner. It provides meaningful automation of the work request process for the CM practitioner, but it in no way attempts to create work orders automatically from gathered data without human intervention. The CM systems available today provide useful diagnostic tools to assist in the recognition of machinery faults and specific defects. Armed with that information, it is a straightforward task for the analyst to confirm the diagnosis and submit the work order using the gateway to CMMS. This gateway then offers a view of this work request as it is processed and the maintenance is executed. This makes the work process visible to the CM practitioner, ensuring follow through on his recommendations and feedback on the entire maintenance process. MT

Then why is the wind often ignored when performing thermographic surveys? Most thermographers simply do not know how important wind is in cooling down a hot spot. Also, how should they compensate for convective cooling effects? This article presents some interesting data using a simple experiment of blowing air on a hot spot simulated on a fuse cutout.

The sun also can be a strong influence on outdoor thermographic surveys from both reflective and warming standpoints. Solar reflective effects have been widely discussed. Use of long-wave cameras (8-12 mm) is the optimal solution for solar reflection problems. With short-wave cameras (3-5 mm), thermographers have had good success by changing position with respect to the target, surveying at night, and learning to interpret reflections.

Solar warming can be a more subtle effect, especially for hot spots that are thermally isolated from the surfaces the IR camera sees. For these indirect targets, temperature rises of a few degrees Fahrenheit can indicate significant problems. Transient solar loading can wipe out these small temperature rises and they will not be seen.

One utility found that great care must be taken when performing thermographic surveys on underground equipment that is heavily electrically insulated. The electrical insulation also serves well as a thermal insulator, making these underground components indirect targets. Just a few minutes of exposure to sunlight made thermography impossible on these underground components. It is possible that by waiting long enough for thermal equilibrium, perhaps several hours, that the rise due to the internal problem would be re-established on top of the solar loading. But most thermographers do not have that kind of time. It is simpler and quicker just to shield the components from direct sunlight.

For indirect targets that soak in sunlight such as oil filled circuit breakers (OCBs), thermographers need to compare apples to apples--that is, be sure when comparing OCBs that they are equally solar loaded and have been for some time. More work needs to be done in this area, but thermographers have had success in documenting major problems indicated by small temperature rises for equipment in full sunlight.

Wind effects We set up an experiment in our student laboratory that allowed students to vary and measure wind speed blowing on a simulated hot spot on an actual fuse cutout. We recognized the possibility of deriving some good data from this experiment. We were able to control wind speed from 1 mph to more than 30 mph. A squirrel cage blower provided the wind onto a Type XS 14.4 kV 100 A fuse cutout. The wind was aimed at the top of the cutout, nominally centered on the knurled brass piece. We taped Scotch Brand 88 black vinyl electrical tape to this piece to increase the emissivity to 0.95 and to attach a type K thermocouple.

Regulated 18 V dc variable power supplies provided power to both the squirrel cage blower and the heat source mounted internally near the top of the fuse cutout. We used a pocket wind meter to measure wind speed. We first heated the cutout without any wind, allowing 1 hr to attain thermal stability.

We did experiments with initial temperature rises varying from 130 F down to 45 F by varying the power to the heat source. We then applied power to the squirrel cage blower to achieve various wind speeds ranging from 1 mph to 25 mph. Temperatures were measured with both an IR camera and a dual thermocouple setup.

The experiments show for several power inputs that the influence of wind is quite strong, even for low wind speeds. The temperature rise was cut in half with just a little over a 3 mph breeze. The stronger the wind, the cooler the hot spot, up to a point. As the curves show, the largest changes occur at lower wind speeds. Our data show that between 50 and 55 mph, the wind has cooled the hot spot to ambient for the power levels we used.

Cooling by convection depends on many factors, not the least of which is shape. The size, shape, orientation to the wind, and surrounding structures all affect convective cooling. Whether the hot spot is emanating from a recessed area in the component as is often the case with hinges, for example, could make a tremendous difference in interpretation. Such a region may be shielded from the wind, and largely unaffected by it.

What does all this mean for thermographers? Here are our recommendations for dealing with wind, whether from natural sources or generated within your facility:

• Buy an anemometer. Pocket size units are quite accurate and cost about $100. Use it on surveys. Note that getting the actual wind speed on the hot spot can be difficult. Do not place the anemometer within inches of energized equipment. Try to get enough measurements to ensure confidence of the range of wind speeds the hot spot sees. Recognize the shape and orientation of the hot spot component relative to any surrounding structures. These factors strongly affect wind effects.
• Within a facility, blowing air can affect measurement on components inside normally closed cabinets. Opening the door can allow cooling air to enter. We have found some hot spots can be significantly cooled this way. If there is air blowing on cabinet doors, we recommend shooting them just after opening, before cooling can take place.
• If possible, measure component temperatures on the leeward (downwind) side of the hot spot. There will be a temperature difference from the windward to the leeward side of the hot component. Measuring out of the wind gets you closer to the no-wind condition.
• "f you are using severity criteria, find out if they are for no wind or light breeze. If they are for no wind, even a slight breeze can throw you off by a factor of two on temperature rise. " The higher the DT for a given wind speed, the higher the power dissipation in the hot spot. For a 100 A current to generate 30 W of power, the resistance would be 3000 micro-ohms.This resistance level would be a problem in medium- to high-voltage circuitry.
• We did all measurements under steady-state conditions. Steady state means the heat capacity (thermal mass) of the component does not enter into the physics of what is happening. When making measurements in a variable wind, or if the wind changes from high to low or vice versa, this is nonsteady state; the heat capacity of the component must be considered. This complicates matters considerably. High heat capacity components will be slower to heat up after the wind dies down and slower to cool down when the wind picks up.

Solar effects The sun can be a great help to thermographers in transient heating/cooling applications such as roof moisture surveys. For steady-state heat flow applications, the sun can cause problems in measurement. The effect of solar reflection creating false indications or masking true hot spots has been widely discussed. In this article, we will concentrate on the effects of solar loading on indirect measurements, particularly those underground components that the sun illuminates only when the thermographer opens a door or cover.

When normally closed compartments are opened, environmental effects such as airflow mentioned above and the sun if outside may cause problems. Underground switchgear is normally heavily insulated. A hot spot simulated in a high voltage elbow, a typical component, with an internal temperature rise of 133 F as measured by thermocouple, has an external hot spot temperature rise of only 17 F.

Heating was simulated with an internal source under laboratory conditions. In this condition, a thermographer aware of indirect measurement criteria would easily determine a problem condition.

But what happens if we allow the part to be warmed by the sun? We did not calibrate the lamp to deliver exactly equivalent solar radiance to the elbow. Rather we wanted to show that the effects of solar warming as the variation in ambient solar radiance can be considerable. The lamp delivered more energy than would the sun. However, we have observed this effect under actual solar loading conditions.

To compare our results of solar warming of both a good and bad elbow, we added a good elbow to the setup. The good elbow is at an angle and slightly above the bad elbow. With the sun shining on the elbow, there is considerable glint or reflection, as a 3-5 mm bandpass camera was used. After warming, we shielded the elbows from the lamp. In both cases, we could not tell the good elbow from the bad elbow. The heating by the lamp with or without the glint masked the problem. The lamp was on only for a few minutes. Lamp intensity was greater than that of the sun, but our experience has shown it takes only a few minutes for actual solar effects to produce similar effects.

The bottom line is that for normally shaded components where the problems are indirect thus low temperature rise, the sun should not shine on them.

Indirect measurements where the hot spot is thermally isolated from the surface viewed by the camera are more susceptible to wind and sun than direct measurements. They have a much lower temperature rise and can be masked more easily. Attempting to quantify these effects can result in some degree of frustration. Even under controlled conditions there are many variables to consider. Documenting electrical load, wind, and sun conditions can go a long way to help trend problems over time. MT

This article is based on a paper presented at the Predictive Maintenance Technology National Conference, November 15-18, 1999, Atlanta, GA.

Robert Madding is manager and Bernard R. Lyon, Jr. is thermography course moderator, at the Infrared Training Center, North Billerica, MA, telephone (978) 901-8405; Internet www.infraredtraining.com; email michelle.mcdonough@flir.com

How does your income match up with others in the maintenance and reliability community? It may be hard to find out where you stand because income figures vary so widely almost any way the data are tabulated. That is what MAINTENANCE TECHNOLOGY Magazine found out in its first two surveys of reader income. This year, respondents' income ranged from $22,500 to $112,000.

Average income of all readers responding to the survey was $63,365, somewhat more than the $58,748 registered last year. Salaried readers averaged $67,354, while readers paid on an hourly basis (22 percent of the respondents, the same as last year) averaged $49,182.

The survey was conducted over a random sample of magazine readers (except for subscribers affiliated with consultants and contract services), and we believe the data are representative of maintenance and reliability leadership.

Salaried personnel often have worked in the maintenance crafts or trades, as is the case with 44 percent of this year's respondents. Overall, 63 percent of survey respondents have worked in the maintenance trades or crafts: 50 percent as electricians, 65 percent as mechanics, and 36 percent in more than one trade, including HVAC/R technician, millwright, pipe fitter, and stationary engineer.

Age and income profile
The first of the accompanying charts are histograms of age and income of survey respondents. The age chart, with frequencies displayed in 5-year increments, shows about half the respondents were between 45 and 55 years old, with the midpoint and average close to 46. The income chart shows that about half the respondents received between $50,000 and $75,000 in annual income. The midpoint was $61,300, slightly lower than the average of $63,365.

The scatter chart that plots income versus age grouped by decades shows the wide variance of income within each of the groupings. Average income rose with age from about $43,000 for respondents in their 20s and then leveled out at slightly more than $66,000 when respondents reached their 50s.

How do respondents feel about their level of compensation in relation to their job responsibilities? More than half believe their pay is about right (53 percent), and a few felt it was generous (4 percent). The rest thought their pay was too low. Compensation policies Several survey questions dealt with compensation policies. First, respondents were asked if any of their pay was based on performance and, if so, in what sectors. Personal or individual performance led the list at 51 percent, followed by company performance at 41 percent, department performance at 27 percent, and team performance at 13 percent. (In most cases, percentages have been rounded to whole numbers, and they may total more than 100 in some categories where multiple answers were possible.)

Nearly 46 percent of respondents received a bonus last year. (Total income, including bonus income, was the income figure used throughout the study.) Of those receiving bonuses, 62 percent had some amount of their income at risk and subject to reduction if certain conditions were not met.

Education and registration
As expected, average income rose with the level of education. More than 63 percent of the respondents indicated they had some type of college degree. Average income rose from $54,232 for respondents with associate degrees, to $69,267 for respondents with bachelor degrees, and to $74,063 for respondents with advanced degrees. Average income for respondents not reporting their education level was $58,526, slightly above those with associate degrees. The chart showing income by education level shows that although the trend of the average is upward with increased formal education, there is a wide spread within each grouping. Slightly more than 17 percent of respondents were registered professional engineers (17 respondents) or certified plant engineers (18 respondents). Average income of this group was higher than the average income of all respondents. Professional engineers received an average income of $73,254 while certified plant engineers received an average income of $59,862.

Involvement and responsibility
All respondents were involved in or responsible for plant equipment maintenance and reliability. That is the basic qualifying question on the application to receive MAINTENANCE TECHNOLOGY, and all respondents receive the magazine. However, they work at different levels and have varying responsibilities within the enterprise.

Respondents were asked to choose their level of involvement. Average income was $84,055 for corporate or multiplant involvement, $56,023 for plant management level, $66,013 for maintenance or reliability manager level, $65,049 for supervisor level, and $55,624 for maintenance engineer or technician level. The chart shows a wide spread of income within each involvement sector.
Respondents also were asked about their job responsibility in three broad sectors (12 separate categories):

• Managing responsibilities sector: Department performance, hiring maintenance personnel, budgeting, and time management/supervision of others.
• Designing/buying responsibilities sector: Engineering/design, management of contract services, ordering or specifying plant equipment, and ordering or specifying tools or supplies.
• Hands-on responsibilities sector: Hands-on planning of maintenance work orders, hands-on predictive maintenance analysis, hands-on troubleshooting of equipment, and hands-on maintenance or repair of equipment.

The average respondent had job responsibilities in six of the 12 categories, with 59 percent having responsibilities in all three sectors. When grouped by sectors, 81 percent of respondents had some responsibility in the managing sector, 91 percent had some responsibilities in the designing/buying sector, and 80 percent had some responsibilities in the hands-on sector. Average income for persons having some responsibility in the sectors was $65,407 in managing, $62,621 in designing/buying, and $59,269 in hands-on.

Income by industry
The industry classifications on the MAINTENANCE TECHNOLOGY Magazine qualification form were used to learn which industries were represented in the study. Results were combined into four general sectors (processing, manufacturing, utilities, and facilities) to facilitate analysis. Average income for industry sectors was $70,360 for process industries, $63,267 for manufacturing industries, $68,887 for utilities (electricity, gas, water), and $55,837 for facilities (government, hospitals, colleges, office buildings, etc.).

Apparent satisfaction People involved in or responsible for equipment maintenance and reliability tended to be satisfied with this profession and their employer. Their average tenure is 20 years with their present employer and 17 years in the reliability and maintenance field. When asked if, when looking to the future, they would recommend maintenance and reliability work as a career choice, the answer was yes by nearly a 10 to 1 margin. MT

Questionnaires were sent to a random sample of MAINTENANCE TECHNOLOGY Magazine's 53,000 readers, minus those involved in consulting and contract services. A total of 216 responses were received and processed. No monetary incentives were used (however, respondents who faxed or sent their name and address separately will be provided a copy of the results). Averages and other indicators were based on a sample size that varied because all respondents did not answer all questions.