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7:09 pm
April 11, 2016
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IIoT Maturation Coming?

By on April 11, 2016 in Condition Monitoring, IIoT, Maintenance, Predictive Maintenance, Reliability 0

grant gerkeBy Grant Gerke, Contributing Editor

February’s inaugural “Industrial Internet of Things” (IIoT) column discussed how the massive move to more sensors and analytics in manufacturing isn’t just a passing fad: It’s transformative. How do companies implement a data strategy with current production systems in place?

Each company needs a starting point in the IIoT journey, but a fully realized data strategy is hard to wrap your arms around today—and was even harder in 2012. That’s when Southern Company, Atlanta, an energy producer and transmission line supplier, decided to tackle the problem. The company is a large energy player in the deep-South region, with 27,000 miles of transmission lines that run through Georgia, Florida, Alabama, and Mississippi, in addition to operating several natural-gas and generation assets.

In a recent manufacturing webinar, Elizabeth Bray, principal engineer at Southern Company, discussed some newly enacted pilot projects involving the corporation’s transmission businesses and the move toward condition-based monitoring for its transformers at more than 3,700 substations.

Before the recent pilot, Southern Company began to add sensors and monitoring capabilities to make a future business case for a centralized program. Southern Company uses the eDNA data historian and PRiSM modeling from Schneider Electric for its transformers. These tools allow operations and maintenance teams to organize data into easy-to-read charts on monitoring screens and identify rates of changes or current deviations for its assets.

One example of success in the recent pilot program alerted a maintenance engineer to capacitor issues with a particular transformer. The eDNA trend tool and PRiSM modeling allowed centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

The eDNA trend tool and PRiSM modeling allowed Southern’s centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

The eDNA trend tool and PRiSM modeling allowed Southern’s centralized monitoring teams to identify a rate-of-change alert and allow maintenance to be performed before a peak period could cause downtime.

This is a great example of software and platform analytic delivering on a large sensing development. In Maintenance Technology’s “Final Thought” column, guest columnist Rene G. Gonzalez noted that this type of trend is quite pervasive in the energy industry. As an example, he cited a typical refinery as increasing its number of sensors from 20,000 five years ago, to 100,000 today.

Some industry observers, such as Joe Barkai, former VP of Research at IDC, Framingham, MA, are pushing for standardization of instrumentation and devices to reduce costs for manufacturers. According to Barkai, “There aren’t enough standards for the industrial IoT space, and the robust use of standards is critical to accelerate innovation and scalable IoT ecosystems.”

While Barkai is right, most enterprises need solutions now to visualize trapped machine and system data for maintenance teams. With the increasing number of mergers and acquisitions added to the mix, large manufacturers are now assimilating disparate platforms and control architectures to the current plant-production systems.

John Rinaldi, president of Real Time Automation, Pewaukee, WI, spells out specific problems for manufacturers using older controllers in a recent article, titled, “Mining Manufacturing Data | Leveraging Trapped Data for Results” (automation.com, Aug. 21 2015). “Many controllers,” he wrote, “do not have the software and hardware to communicate data to asset-management and information systems using current computing methods.”

Beside the exceptional computing power of the cloud, industrial networking is another huge component of IIoT. Rinaldi pointed to the advantages of intelligent network gateways, which can “extract information residing in PLCs and communicate data to maintenance-management or asset-management systems.” This allows disparate networks or systems to communicate and even perform math functions on process data and send email alarms to maintenance technicians on changes-of-states.

Operations and maintenance now can measure machine cycles, runtime, and other data to perform predictive maintenance without disrupting control architectures and plant performance. Also, a minimal capital investment solution holds water with management. MT

Grant Gerke is a business writer and content marketer in the manufacturing, power, and renewable-energy space. He has 15 years of experience covering the industrial and field-automation industries.

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912

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

By on February 8, 2016 in Reliability, Reliability Engineering 0

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.

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.

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.

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:

$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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1388

8:18 pm
August 6, 2015
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Ultrasound: Aural Intelligence

By on August 6, 2015 in 2015, Featured, Reliability, Ultrasound Analysis 0

A recent three-day conference that connected ultrasound experts with maintenance professionals delivered some key points about this predictive technology.

By Rick Carter, Executive Editor

The ranks of those who use ultrasound for predictive-maintenance purposes are growing. The trend is evident on factory floors and at conferences devoted to the technology, such as UE Systems’ (uesystems.com) recent 11th annual Ultrasound World/Reliable Asset World event. Held in June 2015, in Clearwater Beach, FL, a record number of attendees was treated to presentations that blended detailed information about ultrasound usage with practical perspectives on how ultrasound fits with efforts to build and maintain reliability-based cultures.

Two standout presentations—“Using Ultrasound for Effective Slow-Speed Bearing Monitoring” by Ron Tangen, maintenance engineering specialist, Dakota Gasification Co., Beulah, ND; and “Utilizing Ultrasound as a Foundational Technology When Embarking on a Reliability Transformation” by Mike Casey, reliability engineer, Mueller Co., Chattanooga, TN—were excellent examples of the experienced-based information Ultrasound World promised and provided.

A UE Systems Ultraprobe 15000 Touch ultrasound gun is used to monitor an internal bearing. This unit includes an on-board camera, infrared thermometer, laser pointer, and the ability to store data, sounds, and images.

Ultrasound for slow-speed applications

Ron Tangen’s presentation focused on how his efforts to predict bearing failures at Dakota Gasification Co.—owner and operator of the Great Plains Synfuels Plant in Beulah, the only commercial-scale facility in the U.S. that manufactures natural gas from coal—led him to ultrasound for slow-speed applications. Though his team now uses ultrasound for many applications in the plant, before its widespread use, ongoing failure issues with the plant’s many slow-speed bearings on coal-handling conveyors had been a problem.

“Operators would walk around on a weekly basis and listen and look at these bearings,” said Tangen. “If they felt there was a problem they would also touch them and maybe use a hand-held, infrared pyrometer to check temperature. But this predictive-maintenance strategy is at the bottom of the PF curve [a designator of the interval between “P—potential failure” and “F—failure”]. And, while they did find problems and got some bearings out of the system before they catastrophically failed, being so close to the end of the PF curve, they would often get done with a route and a few days later have a catastrophic failure.”

Tangen discussed the issue with the plant’s rotating-equipment engineers. “They have a robust vibration program,” he said, which worked well on high-speed bearings, but not on slow-speed. With infrared nearly as ineffective, Tangen turned to ultrasound and tested his idea. When the results proved positive, he established routes that took ultrasound-equipped operations team members to the conveyors’ many slow-speed bearings—bearings whose problems had been previously undetectable prior to failure with infrared or vibration due to their slow speeds. “Now that we’ve been doing this for five years, and after listening to a few thousand bearings,” he said, “you start to see the patterns.”

The results of routine ultrasound testing include hard-to-refute sound files of bearing disintegration. “I first thought I could give a two-week or two-month heads-up on catastrophic failures,” said Tangen, “but the ultrasound technology is sensitive enough that you can track a bearing fault through its lifetime.” By plotting the decibel readings for each given bearing and, as they accumulate, drawing a straight line through the points, he can “normalize” the data to provide an overall direction for the readings. “This enables me to project where I can potentially expect that bearing to be over time,” he said. “Right now I’m beginning to look at bearings we’ll need to pull in 2016.”

Tangen has reluctantly accepted that he’s viewed by some colleagues as having crystal-ball talents. “If you tell a lot of people that you’re predicting slow-speed bearing failures a year in advance, they might think you’re a little crazy,” he said. But they clearly like his information. In a recent meeting with operations and maintenance leaders, Tangen said “the only thing they wanted more of was my predictive report.” They asked if his standard 12-month view of predicted bearing failures could be shortened to quarterly to allow for better planning. “I’m not quite at that point yet,” said Tangen, “but I thought it was a positive note that they have seen enough value in the program to where they want more data more often.”

Ultrasound audio files show the difference in sound emitted by a good bearing (top), and a bearing that is failing.

Ultrasound audio files show the difference in sound emitted by a good bearing (top), and a bearing that is failing.

Ultrasound and reliability

For presenter Mike Casey, who came to Mueller Co. in 2012 from Allied Reliability Group, Charleston, SC, ultrasound was a key part of his task to establish a reliability-based culture at his new company, a maker of water-distribution products. “It was difficult knowing where to start,” he said. “When I got here we had an ultrasound gun that was used, maybe not correctly, and it needed to be upgraded. So I had two elements to work with: I had to get the funds for an upgraded model and I needed to have the people ready to use it and want to use it. I had to have more than a work order that said ‘listen.’ I needed them to go find things.”

His plan involved getting multiple members of his maintenance crew trained to use the company’s existing ultrasound gun. “Any win we could get with that would be beneficial in my request for a new unit,” he said.

Casey built on an earlier approach undertaken at the plant that had used an outside service to identify and tag compressed-air-system leaks. He trained his team to detect those types of leaks, and distinguish them from other sounds in the plant, particularly those of intentional “leaks” where compressed air is used to blow off or move material.

“I felt comfortable training them,” said Casey, who is also a Level 3 vibration analyst, “but it’s worth every penny to send that person to the OEM [for training]. It also depends on finding the right person. You can put an ultrasound gun in anyone’s hands and they can use it, but you really need that person who is interested and wants to do it. This is not necessarily the most senior guy,” he added. “The process can be grueling. It’s hot, walking, climbing. You need someone who is willing to do all of that. I would caution against randomly picking somebody and hoping for the best. You have to roll it out correctly and get the training. There will be missed calls—these aren’t crystal balls—but if you can minimize those, the technology and the program has a chance.”

It also helps that ultrasound (like infrared) comes with a powerful sensory impact. While vibration plots can “make some people’s eyes glaze over,” said Casey, “if I can show someone a colored picture that shows a temperature differential or have them listen to a sound file and actually take them to the equipment and have them put on the headphones and listen to this and demonstrate what’s going on, that’s where these technologies allow for faster buy-in. It’s more tangible, and I can make the point a lot quicker.”

Casey’s efforts to convince his management of the need to upgrade its ultrasound equipment were successful and not as difficult to achieve as he had expected them to be. “I did go with my guns loaded—I had those findings in my back pocket—but I probably could have sold it without them because the company knew they had to spend some money to get a program going. Like most companies, though, I think they didn’t know how much they had to spend or what they had to do. There was a corporate openness to getting these tools in the house, but you had to maybe put someone like me in there to make it work.”

Casey offered other suggestions for those looking to start or expand an ultrasound program. “Don’t be afraid to experiment,” he said. “Get the training and let that person go. That’s how I found some of the unique applications I did, just going out there and asking, ‘What is this supposed to sound like?’ It’s about identifying issues. The whole idea behind ultrasound is to identify problems ahead of time and come up with ways to eliminate them forever. You need to capture that data, learn how that failure was caused, and eliminate it.”

Casey’s ultrasound program has improved his company’s uptime and maintenance success. “But we still have to make product, which still produces emergency work, so it’s a juggling act,” he said. “That’s why these programs take time to mature. But when management sticks by them, and they give it time, we get our wins and we brag about them. And that’s another important piece of programs like this. You have to brag. You have to advertise those gains. You have to let them know.”

The 2016 UE Systems Ultrasound World/Reliable Asset World event is scheduled for May 10 to 13 in Clearwater Beach, FL. MT

0815ultrasound4If ultrasound is new to you, visit the Resource section of the UE Systems Inc. website at uesystems.com to learn the basics. Pay particular attention to the Sound Recording Library in which you can hear the sounds made by various devices in good and/or failing condition.

Ultrasound: A Multi-Use Industrial Technology

Ultrasound—literally “beyond sound”—refers to acoustic (sound) energy in the form of waves with frequencies above 20,000 Hz, the highest frequency to which the human ear can respond. In addition to its use for predictive-maintenance purposes, ultrasound has many other industrial uses, especially in processing applications. These include:

  • Cleaning of equipment and process material
  • Cutting
  • De-foaming
  • De-gassing
  • De-scaling of plant equipment, evaporators, or pipework
  • De-watering/drying
  • Extrusion
  • Fermentation
  • Filtration
  • High-shear mixing
  • Liquid/solid separation and dispersion
  • Nanotechnology
  • Particle de-agglomeration
  • Sieving
  • Spraying/spray drying/atomization
  • Waste/sludge effluent treatment
  • Welding.

Source: innovativeultrasonics.com

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1906

5:27 am
April 1, 2015
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Are You Ready? Preparing For Reliability Improvement

By on April 1, 2015 in Featured, Reliability, Reliability Engineering 1

Improvement initiatives backed by effective practices and policies can enhance profitability. Careful preparation is key, says this industry veteran.

By Wayne Vaughn, CMRP, PCA Consulting

It’s a fact of life across industry: Many organizations need to upgrade their basic maintenance practices. Even when good ones are in place—such as preventive and predictive programs, effective planning, scheduling and MRO-purchasing/storeroom policies—some plants still need to strengthen elements like equipment availability and cost-reduction efforts. Improving availability and reducing costs (from both maintenance and operational standpoints) can best be approached by implementing an equipment-reliability-improvement program. While these efforts may require significant time and resources to implement, they can generate enormous returns.

Getting the biggest reliability-improvement bang for your buck calls for careful, upfront planning: Success involves more than simply hiring engineers and telling them to go out and “fix reliability.”

Start with your data
While the fact that data drives reliability improvement may seem obvious, it’s not uncommon for companies to either 1) not have data; or 2) have data that’s not easily mined from their CMMS/EAM systems. The following activities are crucial to undertake prior to embarking on a reliability-improvement initiative:

  • Ensure you have best-practice work processes that collect data and appropriate policies in place.
  • Ensure that you classify work in a way that it can be mined to understand problems.
  • Identify key performance indicators (KPIs) that can point to potential opportunities.
  • Establish KPIs to gauge how well your preventive (PM) and predictive (PdM) programs perform.

Best-practice work processes
The work-order work process is the most fundamental element of successful maintenance. All work must be captured. This must include labor, materials, contractors and other expenses that go into maintaining plant equipment. This information must be accurate, and the type of work being done must be coded carefully.

A second key area is ensuring that all work goes through a planning and scheduling process so that needed work is agreed to by operations and executed systematically. This means all PM and PdM work will go through this process. (KPIs and effective management-review procedures must be in place to make sure these important processes are accomplished effectively.) While an entire book could be written about these basics, this article focuses on PM and PdM work orders. Companies spend time to write PM instructions and create PM programs, but often don’t manage the process effectively.

It is important that PM efforts find and repair things that will prevent operational outages or other emergency situations. A good way to do this is to ensure that when something is found, a work order is created to do that corrective work. Too often, companies allow technicians to repair found defects and charge their time and materials to PM work orders. This is a big mistake, and indicative of an area where a policy must be in place. Although this can seem a pragmatic way to perform work that might involve only a few minutes of a technician’s time, it’s one that could potentially mask a problem.

A good policy is to establish a timeframe for such work, say 15 minutes. Work that can’t be performed within the specified time would require a follow-up work order. It’s also important that the follow-up work order be appropriately coded as work identified by a PM activity. An additional recommended policy element is that, regardless of time, if a part is required for the repair, a corrective-action work order must be created to capture the labor and materials used.

Classifying work
There are many ways to classify or “type” the forms or reasons behind why any given work is needed. Each company has to determine what makes sense for its particular situation. For starters, consider the following two methods:

Whatever designations or codes your operation chooses, they must be accompanied by clear definitions on their use, including by whom and under what circumstance. This leads to granularity and standardization of data that eventually provides useful diagnostic information.

KPIs for opportunities
There are several KPIs that can indicate opportunities. An excellent one is a report that shows the mean time between failure (MTBF) for equipment. Again, a policy may be established that if a piece of equipment falls below a selected value, that equipment must receive a formal review. It may be that the equipment will be placed in the capital replacement plan, put into a rebuild schedule, placed on a list of equipment that will undergo an improvement process or simply be lived with as is. This review must be done in coordination with operations.

Often, a piece of equipment that does not appear on the MTBF list may be identified by operations as needing improvement. This may be because of the schedule production load, lengthy repair time when a failure occurs, the lack of a back-up process, support of an important customer or the high cost of replacement processes. Another good KPI to create is a report of high-maintenance-cost equipment. These may offer significant cost-reduction opportunities.

Once a list of opportunities has been identified, some are selected for equipment improvement. A joint, maintenance-and-operations, equipment-improvement process can be effective, and should be considered. Such groups should be facilitated by a reliability engineering expert. This will leverage engineering resources and create greater buy-in when solutions are presented for approval.

Data must then be gathered from the selected equipment to support the problem-solving process. This is where good coding and the creation of corrective-action work orders provides a substantial payback. If corrective labor and materials are charged to PMs when defects are found, data-mining becomes very difficult. That’s because with possibly thousands of PMs done in a facility over the course of a year, perhaps only hundreds capture faults. Since those hundreds will be hard to find, the data will need to be sorted and classified manually—a frustrating process for any site.

KPIs for PM effectiveness
An excellent KPI for monitoring PM effectiveness is to create a report and chart of how many faults are detected per 100 PM activities. An effective program will likely find between 5 and 20 faults for each 100 PMs performed. The report should show PMs that do not detect any faults, and also highlight those PMs with a large number of findings. Too few may indicate that the PM frequency is too often or that the PM tasks are the wrong ones. Too many may indicate that PM frequency is not often enough or that there is a problem that needs a reliability-engineering review.

It is important to regularly review PMs to keep them current. Annually is a good practice. Not only do technicians become aware of things that need to be checked over time, they see things that do not need to be checked. Changing operational conditions can also induce different failure modes or necessitate a different PM.

Regular reviews can also help determine if a PM can be moved to a PdM, add more objectivity to the work process, and identify the most appropriately skilled person(s) to perform the work. A KPI here might be the average age of PMs since their last review, with special reports on PMs that exceed the company’s policy on review frequency.

Of course MTBF and mean time to repair (MTTR) will also indicate how effectively a PM effort is being planned and performed. However, since the absolute value of these measures may not be the best indicator, look carefully at the trend line to verify continuous improvement.

The bottom line
Implementing a successful equipment-reliability-improvement program may require a significant investment in terms of time and resources, but payoff can be enormous: Incorporating best practices, good practices and well-defined policies, these initiatives help companies become and remain profitable. Don’t let inadequate preparation come back to haunt your organization’s efforts. MT

Wayne Vaughn recently retired as Director of Maintenance for Harley-Davidson. He currently is a Senior Reliability Consultant with Performance Consulting Associates, Inc. (PCA), of Duluth, GA. Contact him at Vaughn@pcaconsulting.com.

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2416

3:08 pm
January 13, 2015
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All in a Day’s Work

By on January 13, 2015 in Electrical Test, Maintenance, Management, Power Transmission, Reliability, Uncategorized 0

Two Schneider Electric facility engineers share their tips for ensuring the safety, efficiency and reliability of a site’s electrical system.

By Jane Alexander, Managing Editor

The infrastructure of a typical commercial or industrial facility is a complex network of electrical, electronic, process and control, automation and building-management systems. Some facilities include critical power and cooling systems as part of that infrastructure. And when something goes wrong, there’s typically one go-to person. Whether his/her title is facility engineer (as used in this article), manager or director, this individual has a full plate. For example, following is a partial list of job responsibilities listed in a recent online job posting for a Lead Facility Engineer:

  • Ensure adherence to safety policies and procedures
  • Monitor buildings, grounds and equipment for safety and functionality
  • Maintain data center systems
  • Perform routine maintenance tasks
  • Troubleshoot, evaluate and recommend system upgrades
  • Order parts for maintenance and repairs
  • Request proposals for work that is to be outsourced
  • Supervise shift personnel; support training initiatives
  • Oversee maintenance reporting activities
  • Supervise and audit contractors
  • Ensure accurate and timely completion of work order requests
  • Serve as on-call facility manager, as needed

As Facility Engineers for Schneider Electric with more than 20 years of combined service, Kirk Morton and Keith Smith perform many of the functions listed above. Morton is responsible for the daily operations of a 100,000-sq.-ft. office building with 400+ employees, while Smith oversees operations at one of Schneider Electric’s manufacturing facilities. While many of their day-to-day tasks are similar, Smith’s industrial facility naturally has more systems and requirements to address than Morton’s office building. These include compressed air systems, crane and hoist inspections and load tests, processed water/wastewater treatment and site storm- water prevention plans.

Morton and Smith also are responsible for outsourcing various services, for managing outsourced/contracted employees, and for ensuring contractors follow safety standards in place at the worksite (facility managers, not contractors, retain ultimate responsibility for plant safety). While the traditional reason for outsourcing is to enable an organization to focus on its core competency, there can be others, as reflected in the following four models:

  • The company needs contractors to help meet operational/productivity requirements.
  • Contractors with a specific skill set are needed to perform specific tasks.
  • A company uses contractors for projects.
  • A company uses contractors to act as consultants, i.e., Managed Services.

Reliable power is paramount

Morton and Smith agree that a reliable power system is at the heart of safe and efficient operations. Per Schneider Electric requirements for all of its locations, both have implemented preventive maintenance programs at their individual sites. Their programs follow the recommendations of NFPA 70B and requirements of NFPA 70E:

A well-administered Electrical Preventive Maintenance program: reduces accidents, saves lives and minimizes costly breakdowns and unplanned outages. Impending troubles can be identified, and solutions applied, before they become major problems requiring more expensive, time-consuming solutions.

Source: NFPA 70B-2013 Ed., Section 4.2.1

When it comes to their sites’ respective electrical infrastructures, Morton and Smith may deal with different systems, but their overall focus is on reliability. “We really don’t have any issues in our commercial office space,” says Morton. “The meters and monitoring equipment are our own and very reliable, as is our switchboard. In addition, we have a reliable back-up source for our data room.”

Smith’s manufacturing operation doesn’t have issues with its electrical systems either, thanks to its robust generator and battery backup capable of providing redundant power. Still, he emphasizes, any maintenance and repair activities must be scheduled and performed to accommodate work schedules. “And departmental workloads must be considered.”

Unfortunately, some facility personnel may not be knowledgeable or adequately trained in the specific equipment or power distribution systems that comprise the electrical infrastructure at their sites. With regard to preventive maintenance of an operation’s electrical system, special skills and knowledge are required, which is why this work is often outsourced. Based on their own responsibilities with regard to electrical work, Morton and Smith offer the following tips for other facility managers:

1. Qualifying electrical workers

Due to the increasing complexity and interconnectivity of today’s electrical systems, few companies have the in-house experience to service all of a facility’s electrical components. Facility management needs to ensure that electrical workers are qualified, as defined by OSHA and NFPA 70E, to work on the specific equipment that is to be maintained. This applies to in-house staff, as well as third-party contractors. Fundamental require-
ments include:

  • A complete understanding of equipment, the required work scope and electrical hazards present.
  • Proper use of personal protective equipment (PPE), tools, shielding and test equipment as well as precautionary techniques.
  • Discipline and decision-making skills to determine risk and ability to maintain a safe work environment.

For maintenance and testing activities, an in-depth interview of potential electrical service providers is suggested, and applicable references should be obtained. Ask questions up front relative to Field Personnel Competency Training to determine product knowledge. Morton and Smith say it’s important to learn about the service provider’s safety training program. As noted, the company that outsources the work is responsible for workplace safety, whether the maintenance worker is an employee or a contractor.

2. Outsourcing electrical work

Morton and Smith point out that if a site elects to outsource its electrical work, its facility engineer(s) still have several crucial responsibilities:

Facility engineers should obtain and maintain all of the operations and maintenance manuals that accompanied the original electrical equipment. If any have been discarded, misplaced or lost, the original equipment manufacturer (or their representative) should be contacted and replacement copies requested. These documents are often available online and can be searched by the manufacturer’s name and electrical equipment identification.

Facility engineers must be clear regarding the specific equipment they desire to have cleaned, inspected, maintained, serviced and tested, as well as be clear regarding each piece of electrical equipment that is to be removed from service for inspection, maintenance or testing.

Before any electrical maintenance program is initiated or contracted, facility management should provide exact, detailed and up-to-date one-line diagrams of the entire electrical-power-distribution system. These records should also indicate the specific location, room number, floor or area location where each piece of electrical power distribution equipment can be found. If this documentation is not available or is out of date, the services of a licensed professional electrical engineer should be contracted and commissioned to create and maintain current electrical one-line diagrams and equipment name-plate data.

The facility’s needs for temporary electrical power must be met during a scheduled maintenance interruption. Facility engineers should ensure the availability of a temporary power source.

3. Ensuring safe, efficient, reliable electricity

Both Morton and Smith agree that having a preventive maintenance program in place helps mitigate the risk of unplanned downtime. They also recommend a battery back-up as well as back-up generator capabilities, because even with regularly scheduled preventive maintenance, all facilities will experience unplanned electrical outages from time to time. MT

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2:59 pm
January 13, 2015
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Viewpoint: A House Divided — Reliability or Cost Control?

By on January 13, 2015 in Reliability 0

0115viewpoint-dudleyBy Jeff Dudley, Solomon Associates

“A house divided against itself cannot stand.”—Abraham Lincoln

“As every divided kingdom falls, so every mind divided between many studies confounds and saps itself.” —Leonardo da Vinci

Who could have guessed that the words of these two historical giants might one day apply to the world of reliability? Incongruous as it may seem, Lincoln and da Vinci have a lot to teach us about reliability. These two quotations reflect the internal battle being waged in many of today’s most dynamic, forward-thinking organizations. It involves the two paths that can be followed regarding how to operate a facility. One leads to a reliability culture with long-term growth, the other leads to a cost-control culture with short-term profits. You can only choose one.

Most organizations see themselves as exemplary in the area of reliability. But there is usually room for improvement. Too many settle for wasted resources and less than optimal individual and group performance, sometimes because the organization has never defined “reliability.” What’s your definition? If it involves how assets operate and how well they run, you may be incrementally improving your reliability. But there is much more to capture. If we expand the definition to mean “constantly and consistently meets commitments,” this forces you to focus on your organization rather than your assets. It involves people, not things. Look closer at reliability and you’ll see that it’s about people and cultural behaviors, not just about how our assets operate. Your goal should be to develop a culture where the entire organization becomes reliable. Every single person must create it.

Why shouldn’t your focus be exclusively on cost control? Because cost control tends to blind people. Some cultures have already developed a mindset that views reliability as a cost, not an investment. If cost control is what’s needed, reliability will have to take a back seat. Experience says this thinking is not only flawed, but false. Organizations that perform most reliably are not the ones with low maintenance costs. In fact, many organizations with low maintenance costs have unwittingly positioned themselves to be less reliable than they should be.

A culture of reliability is impossible to create if maintenance cost controls are continuously implemented to improve short-term profits. As our quotes suggest, the two cannot exist together, and constant cost control eliminates reliability.

Why is reliability important? In my book LeadeReliability, I attempt to answer that question. Simply stated, reliability is not what is done but how it’s done. The activities performed in an organization are what is done. But it’s how they’re done that is the measure of success. Every activity and behavior can be done reliably or unreliably. Choosing the latter will cost more and take more time, but if you are performing in a reliability culture you will deliver consistently in three important areas:

  • Increased customer loyalty
  • Improved employee satisfaction
  • Long-term maximum profitability

The time it takes to achieve a reliability culture depends on your starting point. The important thing is that you start, and keep moving steadily toward your goal. Making the decision to become reliable is a brave choice. It takes strong resolve to stay the course, especially early in the journey. The enticement to take profits (sacrificing long-term reliability) rather than make profits (which will sustain long-term reliability) is often so strong that the wrong path is chosen.

So when you’re tempted to go down the primrose path of cost control, remember the words of Abraham Lincoln and Leonardo da Vinci—and take the profitable path toward reliability. MT

Jeff.Dudley@SolomonOnline.com

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7:29 pm
December 1, 2014
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A Contrarian View: What Being Proactive Really Means

By on December 1, 2014 in Reliability, Reliability Engineering, Uncategorized 0

By Heinz Bloch, P.E.

A company I choose to call NTBO (“Not-To-Be-Offended”) will long remember a string of expensive pump failures that jeopardized the continuity of boiler feed water supplied to its power generation turbines. When all components were carefully measured, it was determined that the oil-slinger concentricity exceeded maximum allowable by a factor of 30. Oil slingers (cone-shaped collars on revolving shafts designed to return passing oil outward to the point of origin) are critically important components, but I don’t know if NTBO implemented the specification and inspection routines needed to capitalize on this costly experience.

Capitalizing on an event means not doing the same dumb things all over again. In NTBO’s case, bringing 30- or 40-year-old rotating machinery back to original tolerances should be one of this company’s priority tasks. In fact, the next shutdown might include retrofitting fluid machinery with more efficient blades, impellers, vanes, improved lube delivery, superior filtration and the like.

The time to be thoroughly proactive is NOW. Today is the best time to communicate with competent upgrade shops; or to write an oil-slinger-ring specification requiring stress-relieving (annealing) before finish-machining; or to find out if better reciprocating-compressor valves are available and cost-justified; or to determine if excessive pipe stress on the discharge nozzle of P-207 warrants pre-fabricating a spool piece for insertion between points A and B during the plant shutdown scheduled for later in the year.

Repeat failures in a plant should be thought of as management failures, plain and simple. Someone in management needs to hire, nurture or groom people who know that the above activities are among the hundreds of proactive tasks that fit under various subheadings in role statements for responsible reliability professionals. One such task is to keep current a list of actions that could be carried out if an unanticipated downtime event were to occur.

Say, for instance, the reliability manager tells you that one of your plant’s process units has just shut down because of a pipe rupture. He tells his engineers and technicians that unit restart is scheduled in 30 hours. A proactive reliability employee might, for example, immediately look at his/her two-day-opportunity list that prioritizes coupling replacement in P-207 B, followed by the addition of 24 pre-fabricated hydraulic tubing lines to 12 electric motors on pre-defined process pumps already hooked up to the plant-wide oil mist system.

But it’s a two-way street. A competent manager creates role statements and training plans for his employees. For their part, the reliability professionals reporting to this manager make sure they arrive at work knowing what tasks they will perform (on a “normal” day) in harmony with their defined roles. As they then return home at the end of the day, these professionals should ask themselves if they have added value and if—should they ever leave their current jobs—the present manager or employer would notice they were no longer there.

Granted, if you work for a multi-billion-dollar enterprise, the corporation’s end-of-year profit statement probably wouldn’t be directly affected by your presence or departure. But your group or section or department should notice if or when you’re no longer around.

So make a difference. Whether you’re a manager or a junior contributor, strive to be above average. Be self-motivated and proactive. Offer facts that comport with common sense and the laws of science. As I’ve mentioned before, anecdotes add nothing but wasted time. Factual information translated into cost-justified actions adds value. MT

heinzbloch@gmail.com

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4:54 pm
December 1, 2014
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Speeding Up the Manufacturing Connection

By on December 1, 2014 in Automation Strategies, Condition Monitoring, Management, Reliability 0

MT1412_F1art

Researchers say the Internet of Things may have its strongest influence on the manufacturing sector because of its heavy reliance on well-applied data. Getting up to speed is the challenge.

By Rick Carter, Executive Editor

Manufacturing can be like professional sports in the way it churns out statistics. In both cases, the better those stats are understood and applied, the better the outcome.

In manufacturing, precise data application means assets last longer, less energy is used and product quality rises, along with company profits. But while it has long been a mission of most manufacturing operations to apply data to these ends, a challenge to getting there has been having the ability to gather data accurately enough and regularly enough (often by hand, on paper) to make it useful. The Internet of Things (IoT) makes this much less of a challenge and more of a conscious business decision/strategy to buy, install and use IoT-enabled devices that do the gathering automatically. These devices can now overwhelm manufacturers with good production and maintenance data—on equipment temperature, alignment, vibration, energy usage, and a host of others—that, properly interpreted, can help take operations to new levels of efficiency.

In the next six to eight years, expect about 50 billion devices worldwide to be connected to the Internet, says IT solutions provider Cisco Systems, Inc. Of these, about one-fourth will be used by manufacturers. Similarly elevated numbers exist in many places on the Internet regarding anticipated purchases of IoT devices, the savings they’ll provide and the production they’ll stimulate. It’s clearly the coming thing.

But there are some growing pains. While it may be automatic for your young son or daughter to believe that smartphone ownership (one step toward IoT integration) is as natural as breathing, manufacturers are not so easily swayed. Though there seems little doubt that the manufacturing world is headed in this direction, research suggests business in general is doing so slowly. In a recent (Sept. 2014) finding from LNS Research, for example, 250 executives (from manufacturing and other sectors) were asked how the IoT was impacting their business, and nearly half—43%—said they “didn’t understand or know about” the IoT. About a fourth of the group also said they were pursuing IoT investments for various reasons, and the rest were in the middle, either “investigating” IoT or aware of it, but still unable to detect its impact.

To learn more precisely the extent to which the above attitudes do or do not exist in the world of industrial maintenance and reliability, Maintenance Technology prepared its own study on the Internet of Things, and distributed it to our subscriber base by email. Based on 299 qualified responses, it reveals the following highlights:

40% currently have at least one to 10 or more IoT-enabled solutions for maintenance, and have plans to buy more.

37% have no IoT-enabled solutions for maintenance in their operation, and their plans to purchase them are uncertain.

The most common IoT-enabled maintenance solution, used by almost half (49%) of those with such devices, is for remote temperature detection.

Among both users and non-users of IoT-enabled solutions, the majority (84%) say they believe such devices will have either a “moderate” or “strong” impact on industrial maintenance in the next five years.

What is the Internet of Things?

Following are two definitions. The first is a high-level view that addresses both the manufacturing impact of the IoT and its vast social impact that will come through devices that can help us control or monitor various aspects of our lives and homes. The second is more technical, and describes the IoT in terms familiar to those in the manufacturing environment. For the best interpretation of what the IoT is, keep both in mind.

“The Internet of Things is a growing network of everyday objects—from industrial machines to consumer goods—that can share information and complete tasks while you are busy with other activities, like work, sleep or exercise.”

SAS Institute, Inc., a North Carolina-based data-management software firm

“The Internet of Things is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure. IoT is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine communications (M2M) and covers a variety of protocols, domains and applications. The interconnection of these embedded devices (including smart objects) is expected to usher in automation in nearly all fields, while also enabling advanced applications like a Smart Grid.”

Wikipedia

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In this snapshot of IoT-enabled manufacturing, responses suggest a nearly even split among respondents who use IoT-enabled devices and those who don’t. By a slim majority, most (40%) of respondents are IoT-enabled, and have plans to invest in more. But more than a third (37%) do not currently have IoT-enabled devices and are uncertain about plans to invest in them. Among the remaining 23% who say they “don’t know” if they have IoT-enabled devices or not, such usage in their operations may be split along the same lines.

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Are facility managers leading the charge on integrating IoT-enabled devices in manufacturing operations? The above responses suggest this possibility, but the fact that development of IoT-enabled building controls has a slight jump on that of maintenance devices may explain the strong showing for facility control solutions. For the same reason, the nearly-as-strong integration of remote monitoring solutions for temperature and vibration detection suggests especially rapid (current and, likely, ongoing) acceptance among maintenance pros for these particular devices.

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As expected, IoT-enabled devices clearly simplify the job of gathering data for maintenance pros. A clear majority of survey respondents (83%) who have IoT-enabled devices say they’ve made their jobs either “significantly” or “somewhat” easier. The devices also have a perfect record in this survey for not making anyone’s day more difficult.

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These responses indicate that IoT are also generally easy to master. Most (80%) who have them rate learning how to use them “somewhat easy” or “easy.” Another 20%, however, rate the learning process “somewhat difficult” or just plain “difficult.”

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Training, or the lack thereof, may be the reason for the levels of difficulty reflected in the percentages shown in Chart 4. Less than half (48%) of respondents with IoT-enabled devices say they received specialized training in their use, while the remainder did not. With the wide range of available functionality and complexity in IoT-enabled devices, it’s evident that training should be included in the investment.

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Future purchase plans for IoT-enabled equipment basically parallel current-ownership levels, but with more than a third (39%) who say they either have no plans to buy more IoT-enabled equipment in the next six months or don’t know what those plans are. The good news: Nearly two-thirds of those surveyed who currently own at least one IoT-enabled device will purchase another device of some type before mid-2015.

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Whether a current user of IoT-enabled devices or not, most survey respondents (84%) believe that these types of devices will have a “moderate” or “strong” impact on manufacturing in the next five years. Regardless of individual company budgets, cultures or other concerns that might impact the spread of IoT-enabled devices within their own firms right now, respondents clearly see the growing use of such devices as inevitable. MT

Our Survey Respondents

An overview of those who took our survey, based on the top responses to questions about the type of operation where they work, their age and title:

  • 38% work in a process-manufacturing operation with fewer than 1000 employees
  • 55% are over age 55
  • The most common title among respondents is Maintenance Manager (28%), with Maintenance Team Leader (17%) and Plant Engineer (14%) in the next closest positions.
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