Archive | Reliability Engineering

109

4:47 pm
May 15, 2017
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Beware Self-Inflicted Reliability Problems

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Think of this expert advice as a reality check for your operations and take action accordingly.

By Jane Alexander, Managing Editor

The root cause of poor reliability can come from many sources, including aging plant assets, poor design decisions, even disregard for reliability by those who built and/or installed the equipment. Then, there are the many other reasons outside of your control that could be contributing to the reliability problems your site is experiencing today. While any reliability-improvement initiative will require that all of those issues be addressed, according to Jason Tranter of Mobius Institute (mobiusinstitute.com, Bainbridge Island, WA), operations must first deal with those of the “self-inflicted” variety.

Don’t think you have self-inflicted reliability problems? Tranter begs to differ. It’s a bitter pill to swallow, but yes, you do,” he said. “That’s good news, though, since it is much easier to deal with the self-inflicted root causes than the inherent reliability problems you adopted.”

What does Tranter mean by self-inflicted? To determine why equipment fails prematurely and/or why you experience slowdowns, safety incidences, or quality problems, he explained that personnel could go through a detailed reliability-centered maintenance (RCM) analysis process, or perform root-cause failure analysis (RCFA) after each failure occurs. “Better yet”, he said, “they can learn from the experience gained at thousands of plants around the world and consider some of the most common root causes of equipment failure.”

Focusing on rotating equipment, Tranter outlined those types of problems as follows, starting with the most obvious and working backward to their root causes.

#3. Cause of Reliability Problems: Imperfect operating and maintenance practices

Most of the equipment in a plant or facility, i.e. motors, pumps, fans, compressors, and turbines, is designed to run for many, many years without unplanned downtime. While those types of assets may incorporate some components that wear out, many items, such as bearings and gears, are designed to provide years of trouble-free operation. This, however, assumes that all of the parts were installed correctly, the components are precision aligned, the bearings and gears are correctly lubricated, all fasteners are tightened to the correct torque, there is no resonance, belts are tightened to the correct tension, and the rotors are precision balanced.

It also assumes that the equipment is operated as designed. Pumps, for example, should be operated at their best efficiency points (BEPs). “If you are unsure these types of situations are occurring,” Tranter cautioned, “then they almost certainly are.” He pointed to several areas where seemingly minor issues could be causing serious problems:

1705fvibration2

Just 5/60th of a degree of angular misalignment can cut bearing life in half. (Reference: Harris, Tedric A., A Rolling Bearing Analysis, John Wiley & Sons, New York, 1984.)

Shaft alignment. When two shafts are “collinear” (no angle or offset between their centerlines) it reduces stress on the bearings, couplings, shafts, and the rest of the machine components. Research has revealed that just 5/60th of a degree of angular misalignment can cut bearing life in half (see Fig. 1).

If you use laser alignment with appropriate tolerances, and you remove soft foot, then this will not be a source of poor reliability. By the way, just because your vibration analyst does not detect misalignment does not mean that your machines are precision aligned.

The life of a bearing is inversely proportional to the cube of the load.

The life of a bearing is inversely proportional to the cube of the load.

Balancing. When you balance to ISO 1940 grade G 1.0, the cyclical forces on the bearings, shaft, and structure are minimized and you gain reliability. If you do not have a balancing standard, then unbalance will be a root cause of failure. If you wait until the unbalance generates “high” vibration, then you will have reduced the life of the equipment and supporting structure. That’s because the life of a bearing is inversely proportional to the cube of the load (see Fig. 2). Tranter noted that, while this calculation sounds very complicated, it basically means that if you double the load, a bearing’s life will be reduced to an eighth (23).

Tiny 3-µm particles cause more damage than 40-µm and 10-µm particles (Reference: A Study by Dr. P. B. McPherson)

Tiny 3-µm particles cause more damage than 40-µm and 10-µm particles (Reference: A Study by Dr. P. B. McPherson)

Lubrication. When you correctly lubricate bearings and gears, whether with grease or oil, and that lubricant is free of contaminants, you will achieve maximum life. But if bearings are not adequately greased, their life will be reduced. If the oil is contaminated, the viscosity is incorrect, or additives are depleted, then the life of gears and bearings will be greatly reduced.

Research was performed to determine which particles caused the greatest damage. It wasn’t the 40-µm particles or the 10-µm particles, it was the tiny 3-µm particles (see Fig. 3).

By the time you can see water in oil, the life of the bearing has been halved.

By the time you can see water in oil, the life of the bearing has been halved.

According to Tranter, personnel may think that if they can’t see water in oil then the oil must be fine. Sadly, that is not correct (see Fig. 4). By the time water can be seen in the oil, the life of the bearing has been halved. “We could continue the discussion,” he said, “but suffice it to say that there is a great deal we can do to avoid problems that arise due to imperfect maintenance and operating practices.”

#2. Cause of Reliability Problems: Desire and organizational culture

It’s one thing to understand all of the above root causes. “It’s another,” Tranter observed, “to obtain approval to establish standards and purchase all of the tools, such as laser-alignment systems, that enable technicians and operators to do their jobs correctly. But owning the tools and having standard operating procedures won’t solve the problem.” As he put it, the problem will only be solved when technicians and operators want to use those tools properly and are given the time and encouragement to do so.

Thus, the issue of “desire” and its link to organizational culture must be considered as a root cause of self-inflicted reliability problems and addressed accordingly.

#1. Cause of Reliability Problems: Inadequate management support

Tranter believes a strong case could be made that the root cause of all failures derives from lack of senior-management support for a culture of reliability. Without their support it will be impossible to change the culture and thus change behavior.

“Think about initiatives to improve safety at your plant,” he said. “If senior management didn’t support them, would those initiatives have been successful? Senior-management support leads to people being employed in safety roles, investment in training and tools, and posting of signage that provides warning and feedback on progress, among other things. It also keeps sites from cutting corners that would risk safety, and it makes it clear how important safety is to the future of the organization.”

According to Tranter, the type of management support that drives safety at a site needs to be leveraged to drive reliability improvement. “Everyone within the organization,” he said, “needs to understand that reliability is critically important to the organization and that senior management will stand strong when shortcuts that compromise reliability are available.” Without adequate senior management support, he concluded, meaningful culture change won’t occur, and reliability-improvement initiatives won’t be able to eliminate self-inflicted root causes of problems. MT

Jason Tranter, BE (Hons), CMRP, VA-IV is CEO and founder of Mobius Institute (Balnarring, Victoria, Australia, and Bainbridge Island, WA). For more information on this topic and other reliability issues, including vibration monitoring and training and certification of vibration analysts, contact him at jason@mobiusinstitute.com, or visit mobiusinstitute.com.

Where Does Condition Monitoring Fit?

By Jason Tranter, Mobius Institute

Condition monitoring plays several crucial roles in the battle against self-inflicted reliability problems. For example, providing an early warning of impending problems minimizes the impact of premature failure, and detecting and eliminating the root causes ensures that we achieve the greatest life and value from our precious assets.

Many plant personnel, however, believe that if they have a condition-monitoring program in place, equipment reliability will be optimized. That, unfortunately, is not true.

Most detected faults are avoidable. While it is important to get an early warning, it is much more important to avoid the problem in the first place. Condition monitoring can help by detecting the root causes of failure, including misalignment, unbalance, lubrication issues, and looseness, among others. If those problems are cost-effectively nipped in the bud, then we avoid future failures.

Another way condition monitoring plays a role in plants is in acceptance testing. As part of the purchase agreement, condition-monitoring specialists can perform tests to ensure the new or overhauled equipment is “fit for purpose.”

You may be surprised at how many problems you actually bring into your plant.

143

2:22 pm
May 15, 2017
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Facilities vs. Factory Maintenance: Is There a Difference?

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The common denominators boil down to assurance of reliable equipment assets and successful delivery of product.

By Jeffrey S. Nevenhoven, Life Cycle Engineering (LCE)

Among reliability and maintenance (R&M) professionals, there are many opinions about the universal or, more precisely, not-so-universal nature of maintenance practices. We’ve all heard statements along the lines of “this organization is different,” “we’re not like them,” or “those best practices won’t work or fit here.” One perception shared by many working in the R&M trenches is that maintenance in a batch-processing manufacturing environment is considerably different from maintenance in a continuous-flow operation. Another common perception is that maintenance principles and practices within the world of non-manufacturing facilities differ greatly from those in a manufacturing organization. But do they really?

At first glance, those strongly held beliefs might seem justifiable. Below the surface, however, the inner workings of any organization are quite similar when it comes to R&M requirements. Why, then, do so many people contend that reliability and maintenance are handled differently within distinct organization types? A number of factors drive those beliefs, including operating environment, regulatory requirements, organizational structure, leadership style, business priorities, expectations, and past practice. On top of that, many influences figure into the perception that something will or will not work within a specific organization.

In reality, physical assets are void of emotion and thought. Regardless of location or organization type, such assets need to be operated and maintained appropriately and, in turn, be available to deliver reliable service, as required. Without reliability, business risks increase, asset-performance levels decrease, and costs escalate.

So different, but so similar

Assets, systems, procedures, departments, and workers exist to produce a product or service, regardless of organization type. In the healthcare sector, the product is patient experience. Within amusement, entertainment, and sports markets, it is fan/customer experience. Within the travel industry, it’s passenger experience. Within the education system, the deliverable is student experience. And, within manufacturing, the product is ultimately consumer experience.

Consider, for example, two starkly different environments: a healthcare operation and a refinery. On the exterior, a healthcare organization, such as a hospital, looks very different from an oil-and-gas refinery. Hospitals consist, primarily, of aesthetically appealing buildings and grounds while oil refineries consist of tanks, piping, and other industrial-looking structures. As we enter these operations, noticeable differences still exist.

Inside the hospital, we observe doctors, nurses, patients, and other healthcare professionals at work. At the refinery, we see operators, crafts, engineers, and other industry specialists performing their duties. One facility encompasses exam, emergency, and operating rooms, labs, registration desks, and waiting areas, while the other encompasses control rooms, repair facilities, material storage areas, and production equipment and environments.

Once we look beyond the exterior differences, though, similarities become more noticeable. Despite one organization focusing on patient health and the other on refining crude oil, both share a long list of common business practices, have comparable organizational structures, and utilize physical assets. Both are delivering a product, and both require reliable, well-maintained equipment to do it.

Healthcare operations, such as hospitals, fall under the category of facilities maintenance, or facility management, while refineries in the oil-and-gas industry fall under the factory-maintenance category. Despite the differences in form, fit, and function, these operations are very much alike when it comes to sustaining maintenance requirements. After all, the maintenance processes and practices to ensure that the HVAC system in a hospital is operational and reliable are similar to the efforts required to ensure the reliability and operation of a refinery’s cooling system.

The HVAC system in a hospital’s operating room requires the utmost care and reliability. Temperatures and airflow must be regulated within specific parameters throughout the entire surgical procedure to help prevent infection and promote healing of a patient. If the HVAC system is not working reliably, entire operating suites can be shut down, resulting in canceled surgeries, reallocation of patients to other hospitals, and even possible litigation and damage to reputation.

The process of refining crude oil into consumer fuels and other products entails several chemical-process steps that generate enormous amounts of heat and pressure. The cooling-water system, which is associated with a cooling tower, helps control these extreme temperatures and pressures by transferring heat from hot process fluids to the cooling system. Much like the HVAC system, the cooling tower is a critical asset that requires reliable operation. Unless it performs reliably, product delivery, product quality, energy consumption, the environment, and employee safety can be severely compromised.

Have the parallels between these different types of organizations become clearer?

Maintenance 101

A hospital HVAC system and a refinery cooling tower incorporate mechanical, electronic-control, transmission, and power systems, all of which need to be maintained properly. To achieve this, facility-maintenance departments and their factory-maintenance counterparts need to ensure that the following foundational methods are established and functioning well. Think of these methods as “focusing on the fundamentals” or “the blocking and tackling” of maintenance:

Asset-care program. Most assets within any organization require some level of preventive care. This includes routine cleaning, lubrication, inspection, and adjustment to maintain reliable operation which invariably includes time-based and condition-based maintenance. This should all be documented and monitored through the maintenance strategy program.

Work-management system. The work-management system encompasses the framework, infrastructure, processes, and resources needed to manage asset-care activities, reactive or proactive. It provides the means to identify, prioritize, perform, document, and report work.

Planning and scheduling function. The planning and scheduling function defines the what, how, who, and when for proactive-maintenance work activities. The collective effort of planning and scheduling aims to minimize asset downtime, improve workforce efficiency and, reduce maintenance-induced failures.

Stores (MRO) inventory-management function. To effectively fulfill its mission, the maintenance function requires reliable and prompt material support. A proficiently managed MRO (maintenance, repair, and operations) inventory storeroom contributes to improved equipment reliability, workforce efficiency, and cost control.

Reliability engineering. The reliability engineering function is responsible for driving out sources of repetitive failure. Its mission is to provide leadership and technical expertise required to achieve and sustain optimum reliability, maintainability, useful life, and life-cycle cost for an organization’s assets.

Computerized maintenance-management system (CMMS). Proactive-maintenance organizations use data to effectively handle work activities, report performance, track costs, and enable continuous improvement efforts. The CMMS automates these processes, captures data, and provides information required to enable resource productivity and asset reliability.

Universal application

Regardless of where an asset resides, reliability depends on core reliability and maintenance fundamentals that span all industries and organizational types. Whatever the assets may be, i.e., motors, pumps, compressors, robots, conveyors, boilers, elevators, escalators, pelletizers, utilities, mobile equipment, fire-suppression systems, rotary-tablet presses, chillers, rolling mills, roadways, buildings, you name it, all require specific amounts of downtime for proactive preventive- and predictive-maintenance activities, including, but not limited to, replacement of wear parts, rebuilds, upgrades, and other improvements. Levels of maintenance may vary by organization type, but the fundamental requirement for it is universal. MT

A senior consultant with Life Cycle Engineering, Charleston, SC, Jeff Nevenhoven helps clients align organizational systems, structures, and leadership styles with business goals. Contact him at jnevenhoven@LCE.com.


learnmore2“Alignment Connects Individuals to Organization Objectives”

“Managing Your Value Stream”

“Get to the Root of the Cause”

“Profiles Reveal Reliability Trends”

314

3:54 pm
April 13, 2017
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Add Electrical Motor Testing to Your PdM Toolkit

This predictive approach offers reliability benefits that time-based maintenance can’t.

Left. A 700-hp, high-voltage stator is being tested after undergoing rewind and the vacuum-pressure-impregnation process.

Left. A 700-hp, high-voltage stator is being tested after undergoing rewind and the vacuum-pressure-impregnation process.

Numerous studies have tried to establish guidelines for creating plant reliability and efficiency. Depending on which research is cited, the bottom line is that between 65% and 75% of all motor failures are mechanical in nature. For that reason, vibration analysis, a cornerstone of any predictive-maintenance (PdM) program, would appear to provide the “biggest bang for the buck” in pinpointing possible problems. Still, while an aggressive vibration-analysis program may accurately predict most mechanical issues, it can’t diagnose the 25% to 35% of motor failures that are due to electrical weaknesses and faults. That’s why electrical testing is so important.

To put it simply, the insulation system within a motor is the unit’s “heart”—and nothing but a series of electrical tests can fully evaluate the health and integrity of that heart. Comprehensive evaluation involves the use of static-testing and dynamic- monitoring technologies. To understand the benefits, it’s important to know why and how motors degrade.

Motor degradation

Various factors, including the initial quality of a motor’s insulation, affect the pace at which it degrades. Since heat is the main enemy of all insulation materials, maintaining a cool, dry environment will increase motor life.

Many things contribute to excessive heat. Typically, the situation is acerbated by a combination of issues that individually wouldn’t create a problem. High ambient temperature, numerous restarts, starting under heavy loads, slight misalignment, some unbalance with the supply voltage, and contamination, all contribute to the heat a motor experiences.

Another issue affecting the life of a motor’s insulation system is starting and stopping. In fact, most plant-floor personnel have, at some point in their careers, heard the old saying that “if you don’t want your motor to fail, don’t start it, and if it’s running, don’t stop it.”

Startup and, to some extent, shutdown of a motor, are generally the most stressful times in the unit’s life. Contactor and breaker “bounce” at startup can generate voltage spiking four or five times greater than the operating voltage. The initial in-rush of AC voltage, pushed by as much as eight or 10 times the nameplate current, “attacks” the insulation and greatly affects the early turns. This startup current causes the motor’s windings to flex or breathe and allows the copper magnet wire to rub and abrade. Because there are only about 1 1/2 mils of insulation baked on the magnet wire, over time it will deteriorate, resulting in arcing during starting and stopping. The appearance of arc is a sign that the insulation is basically at the end of its life. The wearing away of that thin insulation film, in turn, is the beginning of the end for many motors.

Screen Shot 2017-04-13 at 10.37.56 AMOnce arcing has begun, it occurs during every startup, and often during shutdown. It may continue for weeks or even months before it creates a failure. Eventually, though, it will create a carbon path and short out a portion of the windings. These shorted turns will then act as the secondary side of a transformer with voltage and current being induced by the rest of the circuit.

Keep in mind that the ratio of good turns to shorted turns will dictate how severe and how quickly a failure will occur. When shorted turns occur, however, a motor will fail within minutes. Thus, it’s imperative to find weak turn insulation before it becomes a hard-welded fault. If not detected in time, a few weak turns will carry an exponential amount of current that is induced by the transformer effect and quickly burns through the slot-cell liner to ground in the laminations. The result is often a damaged core with a large hole that will always make the rewound motor less efficient and run hotter.

Finding the weak turn insulation and taking the motor out of service before a short occurs provides two valuable benefits:

• Plant-floor personnel are in control of the motor. They decide when a unit is to be removed from service, which minimizes or eliminates unscheduled downtime, emergency repairs, and lost production.

• Since the motor in question still has a good core, a reputable repair shop can rewind it using better materials and parts and tighter balance specifications than when it was first installed.

In practical terms, the site gets a “new” motor back from the shop (not a patched-up one).

The predictive route

A strong PdM strategy can allow personnel to make realistic predictions regarding the useful life expectancy of their motors. The unfortunate fact is that a motor begins (and continues) to weaken and deteriorate from the moment of its very first startup. If it operates in high ambient temperatures, with some misalignment and voltage imbalance, and experiences numerous starts under a heavy load, its life will be short. Given these conditions, a motor that should last, say 20 years, will probably fail in two or three. While correcting some of those issues could prolong the life of the unit, keeping tabs on the health of its insulation could provide greater payback.

Preventive maintenance (PM) efforts are clearly important when it comes to a plant’s motor fleet. For example, in facilities where contamination is an issue, PM routines to reduce its effect on motor life are a must. Whenever possible, however, a PdM strategy that leverages as many proven predictive tools as possible should replace preventive activities. After all, to develop a complete picture of a patient’s health, a physician will typically perform a battery of tests. Your site’s motors deserve similar treatment.

Fortunately, state-of-the-art equipment and methodologies are available to identify early issues before they lead to catastrophic failure(s). Routine testing and trending will detect weaknesses long before they can propagate into an insulation failure. To design this type of PdM program, site personnel need to identify the motors that are most critical to the operation and, in turn, those that are the most problematic. This information will indicate which tests need to be performed and how often.

Many independent testing organizations have detailed specific test parameters, proven to provide sufficient data for the technician to evaluate the immediate health of the insulation. To ensure the capture of accurate data, it’s important that those guidelines be strictly followed. For more information on testing parameters and requirements, refer to IEEE (Institute of Electrical and Electronic Engineers, ieee.org), IEC (International Electrotechnical Commission, iec.ch), EPRI (Electric Power Research Institute, epri.com), and EASA (Electrical Apparatus Service Association, easa.com).

Low-voltage testing, comprised of capacitance, inductance, and resistance tests, provides some useful information, but will not provide early warnings regarding turn insulation. A complete set of tests that will provide the predictive information you need include:

Winding-resistance test: This test will verify that all three phases are similar and all internal connections are tight. It uses a Kelvin bridge and injects about 12 VDC at approximately 7 A into the windings. One poor connection will lead to unbalanced current and uneven heating.

Megohm test: After passing the winding-resistance test, a megohm test is run to measure insulation resistance. The test uses a low-current DC voltage that depends on the nameplate voltage of the motor. A polarization index test (PI), which is an extended megohm test, may provide important information about the insulation if it is old, cracked, or brittle.

High-potential test: If the winding-resistance and megohm tests are acceptable, a high-potential (HiPot), or step-voltage, test may be performed. This test uses increased voltage to create electrical stresses on internal insulation cracks. This can reveal aging or physically damaged insulation. The HiPot test is usually conducted at an elevated level that is at least twice the line voltage plus 1,000 V. EASA and other testing organizations recommend even higher test-voltage levels. The HiPot test may not be appropriate for in-service motors that display low megohms during the megohm test.

Surge test: Once the above tests are satisfactorily completed, a surge test is performed. Since more than 80% of all winding failures begin as a turn-to-turn weakness that can only be detected by a surge test, it is the most important static-testing method. Surge testing applies pulses through a large capacitor at ever-increasing voltage levels and monitors the reaction as the voltage is discharged into a motor’s windings. The purpose is to re-create the spiking that occurs at startup. Doing so requires the capacitor to “fire off” each pulse at a very fast rise time. The intention is to locate weak turn insulation before it has a chance to become a hard-welded fault that leads to a quick failure.

Value proposition

Adding electrical testing of motors to your site’s PdM toolkit puts personnel in the reliability driver’s seat with regard to these units. The value proposition is clear: Routine testing and trending provides sufficient data to make a diagnosis regarding the ability of a motor to remain in operation or to determine if it needs attention. Being in control, i.e., being able to specify when a motor is pulled from service and sent out for repairs, is the essence of predictive maintenance—and an enormous benefit. MT

Information in this article was supplied by Timothy M. Thomas, senior electrical engineer, Hibbs Electromechanical Inc., Madisonville, KY (hibbsinc.com). Email him at TThomas@HibbsInc.com.

294

7:06 pm
July 13, 2016
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Calculate the Impact of Unreliability On Sales

While most acknowledge that unreliable operation is costly at the plant level, the impact, when projected to sales, is enormous.

By Al Poling, CMRP

Generally speaking, manufacturing personnel understand the effect unreliability has on maintenance. Unreliability requires more maintenance resources and materials to repair failed equipment as well as increased maintenance capital spending caused by the need to replace equipment that has reached the end of its useful life. Running equipment to failure causes equipment to reach the end of its useful life prematurely. What many manufacturing personnel do not understand is the effect unreliability has on sales.

Screen Shot 2016-07-13 at 1.35.07 PMMaintenance professionals find it difficult to garner support of corporate executives who do not understand maintenance. However, these same executives have a very clear understanding of profit and loss. If they understand the effect unreliability has on sales and, therefore, profit, they will be much more inclined to support a comprehensive reliability initiative. It might surprise many maintenance professionals to learn that there is a mutual benefit to be derived from reliability: reduced maintenance costs and increased sales and revenue.

To understand this relationship, we must examine the basic business model. All for-profit businesses operate under the same equation:  PROFIT = SALES – COST. Equipment failures affect both sides of this equation.

Calculate the True Cost of Unreliability,” an article published in the February issue of Maintenance Technology examined the impact unreliability has on maintenance costs. In this article we will examine the effect unreliability has on sales.

A hypothetical plant will be used for purposes of calculations. You can apply these calculations to your own operations to develop an order-of-magnitude estimate of the impact unreliability has on sales and profitability.

For the calculation purposes, we will use a hypothetical plant that has a plant-replacement value (PRV) of $1 billion US, with a targeted return on capital employed (ROCE) of 30%. In other words, business stakeholders expect to realize $300 million in earnings before interest and taxes on their $1 billion investment. We will also assume that this plant operates at 70% capacity due to lack of sales.

Raise sales price

Sales revenue is driven by two key levers, price and volume. The higher the sales price per unit the higher the margin, the higher the sales revenue, and the greater the profit. Additionally, the more product you sell (sales volume), the higher the sales revenue and the greater the profit. So both sales price and sales volume determine the revenue garnered by the business. Unreliability has a very profound effect on those two factors. To understand the relationship between asset reliability and sales revenue in this equation we need to examine each component in more detail.

The price of a product is largely set by whatever price the market will bear. However, the market places a premium on quality. The highest sustainable product quality can only be produced through uninterrupted manufacturing. As assets become more reliable, manufacturers are able to produce consistently higher quality product, something customers value. This isn’t new. W. Edwards Deming espoused the virtues of product consistency more than a half century ago.

If a 5% price premium can be garnered from customer willingness to pay more for higher quality product, then the subsequent increase in sales revenue is calculable. Assuming the hypothetical plant had $500 million in sales during the reporting period, the increased revenue from a higher price enabled by higher-quality product would be an additional $25 million in sales revenue.

This increase in sales revenue was made simply by reducing and/or eliminating unplanned equipment failures. No additional capital was required, resulting in a direct increase in the return on capital employed and, more importantly, on profitability.

LINE ITEM: $25 million = The increase in revenue due to higher sales price for higher quality product derived from reducing and/or eliminating unreliability.

Increase capacity

A second sales-revenue benefit derived from the elimination and/or reduction of unreliability is garnered through a lower cost per unit (CPU) of production. By operating in a failure-free mode, manufacturers are able to increase throughput. When there are fewer production interruptions caused by equipment failures, more product is made over the same period of time.

For example, if the average production rate was 80 tons per day, including time lost to equipment failures, then a natural benefit derived by reducing and/or eliminating equipment failures would be an automatic increase in capacity. If one additional hour per day of production was gained, the subsequent increase in capacity would be 4%.

A 4% increase on $525 million in annual sales revenue would be worth an additional $21 million in sales revenue. As was the case with improved product quality, this increase in capacity was derived without any additional capital investment. Companies are always striving for increased sales by whatever means, but they inevitably expect to have to invest significant capital in a new production unit or to expand an existing production unit.

LINE ITEM: $21 million = The incremental sales gained through the incremental increase in production capacity derived from reducing and/or eliminating unreliability.

Increase sales margin

Additionally, a 5% reduction in the cost per unit derived by spreading costs, e.g., operational and energy costs, over a larger volume of product could be significant. This is effectively an increase in the sales margin of the product being sold. Using the aforementioned $500 million in annual sales, the benefit would be 5% of $500 million, or an additional $25 million in profit.

LINE ITEM: $25 million = The increase in profit caused by an increased sales margin gained by reducing the cost per unit derived from reducing and/or eliminating unreliability.

Admittedly, an argument against the aforementioned gain could be made. Just because you produce more product doesn’t mean that you can sell it. But let’s examine the primary means of competition in a capitalistic environment. Companies generally compete on price and/or on quality. By reducing and/or eliminating equipment failures, both of these factors are enhanced. If you have a higher quality product to offer, your competitive position is automatically strengthened. You can increase price to increase sales revenue and/or maintain the same price and increase sales volume by offering a higher quality product for the same price.

The gains illustrated above appear to be reasonable, so we’ll assume that we could potentially increase sales price and sales volume, thereby deriving a dual benefit from the reduction and/or elimination of unreliability.

Reduce maintenance

We must also consider that, with a reduction in unreliability, maintenance costs, typically the highest fixed cost in manufacturing, are substantially lowered. Maintenance costs are distributed across all production in the form of maintenance cost per unit of production. The net result of lower maintenance cost is therefore lower cost per unit of production. In a poorly performing operation, characterized by high unreliability and subsequent high maintenance cost, the benefit derived from reducing the maintenance cost per unit alone can be profound. Benchmark studies have shown that the difference between a best performer and a worst performer, relative to maintenance cost, can be exponential. In other words, a worst performer will spend exponentially more on maintenance per unit of production than a best performer.

In the process industry, the range of performance in maintenance cost as a percent of plant-replacement value (PRV) is from less than 1% for best performers to more than 15% for worst performers. For illustration purposes we will assume a 1% reduction in maintenance cost as a percent of PRV. We will assume maintenance costs were 3% of PRV, but have been reduced to 2% of PRV by implementing a robust condition-monitoring program that facilitates corrective action prior to catastrophic failure. The net increase in profit through reduced maintenance costs based on a PRV of $1 billion would be $10 million.

LINE ITEM: $10 million = The increase in profit gained by a reduction in maintenance cost derived from reducing and/or eliminating unreliability.

Extend turnaround frequency

Although it is not universally recognized, maintenance turnarounds are caused largely by unreliability. The primary driver for turnarounds is typically pressure-equipment inspection. But what if you used non-intrusive condition monitoring such that you eliminated the need to open equipment for visual inspection?

Far too many process plants still take annual turnarounds. In this era of advanced inspection technologies, that is inexcusable. Better-performing process plants have extended the frequency of their turnarounds out to 5 to 7 yr. Let us assume that the hypothetical plant still takes annual turnarounds that cause 21 days of lost production. If the turnaround frequency was extended out to 3 yr., with only a 7-hr. increase in duration, a net annualized increase in production of approximately 12 days would be realized.

If we conservatively calculated the value of each day of production, based on current production rates and sales prices, twelve additional days of production would net an additional $18 million in sales revenue.

LINE ITEM: $18 million = The increased sales revenue gained from 12 additional days of production derived from reducing and/or eliminating unreliability caused by annual turnarounds.

Increase production

The final potential gain we will examine is the 30% of production capacity that is not currently utilized, auspiciously because of a lack of sales. Claiming that no sales were lost due to unreliability is a self-fulfilling prophecy. As long as the manufacturer is not a sole source producer, additional sales were lost to competitors. If we go back to the benefits of the highest sustainable product quality and lowest sustainable unit cost of production, there would be no valid reason for not selling every unit of production. That additional 30% of production and subsequent sales is a game changer for the business. Using the original assumption of $500 million in annual sales, adding in the additional sales revenue from continuous production, and ignoring the quality premium, the net gain in sales revenue is an astounding $215 million.

LINE ITEM: $215 million = The increased sales revenue gained by running continuously, derived directly and indirectly through the reduction and/or elimination of unreliability.

There are arguably additional sales and revenue gains that can be derived through the reduction and/or elimination of unreliability. However, using the examples above we can see that a significant increase in sales and related revenue can be gained through reliable operation.

This is not an insignificant amount of sales revenue for any size organization. The business case for reliability is compelling! Although a hypothetical manufacturing site was used to illustrate the effect of unreliability on sales, the same calculations can be used to obtain an order-of-magnitude estimate of the value of lost sales due to unreliability for any plant. Plant management and corporate leaders need to understand the high cost of unreliability. All it takes is for someone to take the initiative and calculate the value for your operation. Once the true cost of unreliability has been exposed, garnering support for improved reliability should be easy! MT

Al Poling has more than 35 years of reliability and maintenance experience and is a Certified Maintenance and Reliability Professional (CMRP). His consultancy, RAM Analytics, is located in Houston. For more information, contact him at al.poling@ramanalytics.net.

Click here to download an ebook pdf containing this article and Al Poling’s February 2016 article “Calculate the True Cost of Unreliability”.

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7:49 pm
April 11, 2016
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Choose The Right Emergency Stop

With today’s number of customizable available options, selecting the right emergency stop (e-stop) for process equipment can be a daunting task, but it’s critical for overall safety. According to human-machine-interface (HMI) experts at EAO Corp., Shelton, CT, fitting equipment with a highly functional e-stop in line with the basic application design concept, versus a lesser-certified safety switch, is key. MT

Determine if your application requires Category 0 or Category 1 shutdown.
This is crucial in the placement, size, electrical specifications, mechanical characteristics, color, and number of required e-stops.

Research international and North American standards, performance ratings, and codes that govern your application (see table below).
Each industry has unique regulatory standards. These restrictions may govern factors such as size, color, and contact terminals.

Select the product.
Choose your e-stop based on design factors to meet industry demands and international compliance. Proper selection involves understanding market and application requirements, environmental conditions, and electrical demands.

Accessorize.
Vendors often provide a variety of unique features to enhance your e-stop and complete virtually any application. It’s important to research these additions as some accessories may be mandated by industry standards.

Consult an expert.
Many suppliers offer consultative services to assist customers throughout the process of selecting and integrating their HMI needs, from individual e-stops to completely designed and produced ‘mixed technology’ solutions.

For more information on e-stops and other HMI components and systems, visit www.eao.com.

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8:26 pm
February 8, 2016
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Calculate the True Cost of Unreliability

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The economic impact on manufacturers that haven’t bought into the idea of failure-free operation is easy to determine and, more important, enormous.

By Al Poling, CMRP

Although experts have espoused the virtues of equipment reliability for decades, countless manufacturing operations still suffer significant and unnecessary downtime due to equipment failure. Apparently these manufacturers haven’t bought into the benefits of failure-free operation. What will it take to get them to accept the time-proven benefits of reliability? Perhaps they will never be convinced by examples of other manufacturing operations, believing that they are somehow unique. If the benefits derived through reliable operation won’t lead them to change, perhaps an examination of the true cost of unreliability will.

The big picture

Businesses operate under the basic equation of: profit = sales minus cost. Although equipment failures affect both sides of the equation, this article focuses on the impact of unreliability on maintenance costs—typically the largest fixed costs in a process-industry manufacturing facility. End users can apply the following calculations from a hypothetical plant to their own business and develop an order-of-magnitude estimate of the impact of unreliability on maintenance costs at their site(s).

For purposes of these calculations, let’s assume our hypothetical operation has a plant replacement value (PRV) of US$1 billion and a resident maintenance workforce of 150 craft-level employees.

Maintenance-labor cost

Maintenance costs in a plant include those for skilled craft labor to repair and restore equipment to good operating condition following a failure. The current average U.S. Gulf Coast, fully loaded, maintenance skilled-craft wage rate is approximately $45/hr. Using the U.S. standard of 2,080 hr./man-year, with an estimated overtime rate of 5%, the cost/year/skilled craft worker is approximately $100,000. Consequently, 150 skilled craft workers will cost approximately $15 million/year. In terms of man-hours, including overtime, the number is about 300,000 man-hour/year.

Benchmarking studies have confirmed that best-performing plants average 1% downtime due to unreliability/year, while average performers suffer 7% downtime due to unreliability. These numbers include annualized downtime for turnarounds. To calculate the annualized downtime for turnarounds, simply take the total downtime for your last turnaround and divide it by the number of years between turnarounds. A 30-day turnaround taken every three years equals 10 days of annualized downtime due to the turnaround alone.

Best performers average less than four days of downtime/year due to unreliability, including annualized downtime for turnarounds. Average performers endure more than 25 days of downtime/year due to unreliability.

There is a direct correlation between the number of equipment failures and the number of craft workers required to effect repairs. In theory, the average-performing manufacturer would have seven times more maintenance craft workers than the best performer. That, however, is in theory only. Achieving and sustaining failure-free operation requires truly skilled craft workers and, even they have to focus their efforts on failure avoidance instead of repair.

Work sampling studies have revealed that the efficiency of maintenance-craft workers is extremely high in highly reliable operations, as their work is well defined and scheduled in advance. In comparison to reactive maintenance, schedule interruptions happen on an exception basis in a failure-free environment. Instead of seven-times as many skilled craft workers needed in an average-performing plant, we’ll estimate (conservatively) that the number is half that (or three and a half times).

With regard to maintenance labor, the cost of unreliability is the difference between the number and associated cost of skilled craft workers required to support a reliable operation versus an unreliable one. Assuming that the aforementioned 150 such workers, costing $15 million/year, are working in an operation suffering average unreliability, the additional maintenance labor costs are 70% of the total—$10.5 million/year. In this example the true cost of unreliability in skilled craft workers is an additional 105 such workers costing an additional $10.5 million/year, whereas a reliable operation would only need 45 skilled craft workers. This calculation does not factor in the elimination of overtime that would be found in a failure-free environment. While equipment still fails, the impending failure is discerned well in advance so repairs can be made during normal maintenance work hours.

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Maintenance-material cost

Repair material is another major element of maintenance costs. Unfortunately, the ratio of maintenance-material cost to maintenance-labor cost varies by region due to differences in the prevailing wage and the availability (or lack) of repair materials. Equipment’s material of construction also factors into material-to-labor ratios.Maintenance-material cost

A reasonable hypothesis is to use a one-to-one ratio of maintenance material to maintenance labor. Applying this ratio to our hypothetical plant with 150 maintenance craft workers at a cost of $10.5 million/year means the site spends another $15 million on maintenance-repair material annually. Using the same approximation as we used with maintenance labor, 70% of these material costs would be avoidable if the plant were operating in a failure-free mode. In monetary terms, this represents yet another $10.5 million attributable to unreliability.

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Equipment-replacement cost

In consequential failures, equipment cannot be repaired and, thus, must be replaced. Benchmarking studies have shown that manufacturing operations running their equipment to failure spend exponentially more than best performers spend on maintenance capital, i.e., equipment replacement.Equipment-
replacement cost

Manufacturers that take care of their equipment and embrace failure-free operation derive extraordinary service-life from that equipment. Conversely, those who operate in a run-to-failure mode wear out equipment quickly.

Run-to-failure is a particularly costly maintenance strategy. Best performers will spend 1% or less of their PRV each year to replace equipment that has reached the end of its useful life. In contrast, average performers will spend 3% to 5% annually on replacement equipment. Determining the true cost of unreliability, therefore, requires factoring in the price tag for equipment replacement.

A reasonable assumption is that best performers spend 0.5% of PRV and average performers spend 4% of PRV on annual equipment replacement. That means, based on our hypothetical plant, with a PRV of US$1 billion, a best performer would be spending approximately $5 million annually on equipment replacement due to unreliability, and an average performer would be spending approximately $40 million annually. Thus, in our hypothetical example, the true cost of unreliability reflects an additional $35 million/year for equipment replacement.

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Additional costs

Another significant maintenance cost involves maintenance administration and staff. Granted, there is not a direct correlation between the number of maintenance salaried personnel and maintenance wage personnel. Still, there are common ratios of salaried to hourly wage personnel—and they differ dramatically between better and poorer performers. Merely reducing numbers of skilled craft workers, though, doesn’t translate to an equal percentage reduction in staff. For example, in average-performing operations, there may be more maintenance supervisors, but the ratio of craft to supervisor positions is higher. In best-performing operations, the ratio of maintenance supervisors to craft personnel is lower. This situation results from recognition of the value of maintenance supervisors as facilitators who can greatly enhance the efficiency of a maintenance workforce.Additional costs

A similar condition exists with maintenance planners. Poor performers have larger numbers of skilled craft workers/maintenance planners—with some of the worst performers in the range of 60:1. An individual maintenance planner can’t effectively serve such a large number of skilled craft workers—and is likely operating in a reactive mode, expediting materials or performing other duties required to support reactive maintenance.

In contrast, the ratio of skilled craft workers to planners at a best-performing site is more apt to be in the 20:1 range. With this type of ratio, a planner can prepare detailed job plans, procure materials, and efficiently perform other planning functions. The net result is that there will be no appreciable administration and staff cost savings in moving from a run-to-failure to failure-free environment. This is due to changes in ratios of craft to staff positions and the redeployment of some personnel from reactive work to proactive functions that are needed to support failure-free operations.

Additional maintenance costs affected by unreliability involve facilities, including offices, shops, break rooms, restrooms, and related infrastructure costs. Rolling-stock requirements can also be affected, as can various support staff outside of the maintenance function, such as human resources, training, and safety. Generally speaking, though, there is no substantive reduction in administration, staffing, and related cost categories as a result of reducing and/or eliminating unreliability.

The bottom line

As discussed here (and shown in the accompanying sidebar), the true cost of unreliability is enormous. By adding up the previously noted line-item maintenance costs for our hypothetical plant, we can see that unreliability amounted to a staggering $56 million (or 80%) of unnecessary spending for maintenance labor, materials, and equipment replacement costs.

Given this type of economic impact of unreliability, why don’t all manufacturing operations transition from failure-prone to failure-free environments? Unfortunately, there’s no single root cause. Many factors contribute to the situation. Among them:

The constant distraction of equipment failures is akin to putting out fires. Consequently, everyone is so focused on reacting that they believe they can’t take the time to implement measures to avoid the failure. A fairly simple solution here would be to devote a small number of employees to developing and implementing plans to avoid equipment failures. For this approach to be effective, however, those proactive resources can’t be dragged back into firefighting mode. Otherwise, nothing will improve.

Poorer-performing operations rarely have a strategic plan or, if they do, it’s typically mere window-dressing written to satisfy corporate management. Without a well-thought-out vision or mission, plant personnel will naturally accept the status quo as the normal mode of operation.

There is a lack of leadership in poorer-performing manufacturing operations. Either the current management lacks the requisite leadership skills or there are no incentives positive or negative to change the status quo. Humans respond to stimulus. If there are no consequences for being unreliable, nothing will change. Conversely, if there are no rewards for becoming reliable, or if the existing reward system somehow perversely rewards unreliable behavior, nothing will change. Better-performing manufacturing operations typically share the benefits of failure-free operation with all employees. As a result, everybody has a stake in improved reliability. 

While this discussion used a hypothetical manufacturing site to illustrate the true cost of unreliability, the same ratios can be applied to obtain an order-of-magnitude estimate of the cost of unreliability for your operations. Remember, though, that someone needs to take the initiative before improvement can begin. MT

Al Poling has more than 35 years of reliability and maintenance experience in the process industries, many of them spent in engineering and corporate-leadership roles with several companies. A Certified Maintenance and Reliability Professional (CMRP) through the Society for Maintenance and Reliability Professionals (SMRP), he served as technical director of the organization from 2008 to 2010. Prior to starting his own consultancy, Poling served as the project manager for Dallas-based Solomon Associates’ International Study of Plant Reliability and Maintenance (RAM) Effectiveness, during which he worked with clients to identify performance improvement opportunities through benchmarking. For more information, contact al.poling@ramanalytics.net.

Unreliability: A Very Expensive Proposition

The three largest maintenance-cost categories affected by unreliability are maintenance labor, maintenance material, and maintenance capital, i.e., equipment replacement. In our hypothetical manufacturing operation with a plant replacement value (PRV) of US$1 billion and resident workforce of 150 skilled craft workers, we can calculate the cost of unreliability individually and collectively as follows:

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$70,000,000 = Total current annual maintenance cost for labor, material, and maintenance capital, i.e., equipment replacement.

80% = Percentage of the total maintenance labor, maintenance material, and maintenance capital spent unnecessarily due to unreliability.

At first glance, these figures may appear unrealistic. They’re not. The harsh reality is that unreliable operation is very expensive for any manufacturer, regardless of size.

learnmore“The Business Case for Asset Reliability”

“Choose Reliability or Cost Control”

“The Risk Is In The Management”

“Reliability Business Case: Conversion Costs”

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