Prove the value of predictive maintenance (PdM) to senior management

Proof of predictive maintenance benefits can have an astronomical effect.

By Russ Kratowicz, P.E., CMRP, executive editor

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The constellations of the zodiac appear along the path of the sun, in what’s called the ecliptic. More than 2,000 years ago, skywatchers studied these star patterns and predicted how the movement of the planets “through” them affected civilization on Earth.

Many individuals still cling to the promise of these predictions, or horoscopes, based on astrologers’ interpretations of star patterns in the ecliptic, even though most astronomers dismiss it as a bunch of silly cosmic mumbo jumbo.

Plant and maintenance managers might sometimes feel similarly pressed to defend the merits of predictive maintenance (PdM) techniques. A PdM program requires the use of technologies that help industrial personnel to make better decisions on when to performance maintenance. And these technologies cost money.

Predictive maintenance technologies are numerous, but how much of each is best? In other words, what’s the most cost-effective combination? “Applying the RCM concept for determining what maintenance strategy should be appropriate for each failure mode is best,” says Reid Neubauer, reliability engineer at Therma-Tru’s ( manufacturing plant in Butler, Indiana. “I say that because failure-mode maintenance strategies consider, as the first and best option, condition-based maintenance, but only if the means to determine the condition of an asset is technically feasible and worth doing. That might include the use of a specific PdM technology.”

Another take comes from Doug Smithman, P.E., president of EMP Engineering Services (, in Dresher, Pennsylvania. “Anybody involved knows the percentage of failures related to bearings, misalignment, poor installation, insulation and the like,” he says. “They also know that some tests are better at early identification of certain problems than others. The trick is to mix those technologies properly. This is where most programs start off on the wrong foot. Is a program initiated by developing a wish list and then attempting to appropriate the needed funds or by optimizing a budget that has been granted? In most cases, it’s the latter because the program isn’t funded as desired anyway.” In that case, linear programming is the best technique to use to optimize the application of technologies for a host of equipment, he explains.

“Selecting the least expensive combination of PdM technologies usually isn’t your best approach to the highest possible return on investment,” says John Trulli, director of mechanical services at Allied Reliability ( “Regardless of their cost, the application of technologies is what affects the bottom line. The goal is to detect specific failure modes as early as possible so that repairs can be planned, scheduled and corrected early on the failure curve. This strategy for selecting technologies results in the most cost-effective corrective action and therefore proving the best return on your technology investment.”

It’s the focus on the bottom line that can make the difference. This means including the labor content in the equation. “First it must cost less to do the technology than to not do it,” says Jim Taylor, CPE, CPMM, director of operations at Machinery Management Solutions ( in Clarks Hill, Indiana. “Then optimize the cost of the full program over the entire plant. An individual technology might be cost-effective for a few machines, but when we look at the entire operation, it might be too expensive. Of course, consider the various ways to apply the technology — contract out, partial in-house, partial contract or fully in-house. Some are more effective if contracted out, especially if they require extensive training or ongoing experience to maintain skills.”

Appropriate application

Figure 1. The oft-cited traditional version of the P-F curve is a theoretical construct that helps visualize the path of degradation in equipment functionality.
Figure 1. The oft-cited traditional version of the P-F curve is a theoretical construct that helps visualize the path of degradation in equipment functionality. (Green Energy Engineering Services, Inc.)

Once you have a handle on which technologies are optimum for your plant, the next question most people confront is how rigorously and intensely they should be applied to plant assets.

“The process of RCM-based maintenance strategies determine the intensity and frequency of the PdM technology used,” says Therma-Tru’s Neubauer. “The objective would be to mitigate a functional failure before the asset reaches that stage, which means the P-F interval is long enough to allow the management of the potential failure by scheduled corrective action.”

The P-F curve (Figure 1, Figure 2) often is cited as a way to determine periodicity, says Machinery Management’s Taylor. “But it’s rare that we can plot one for actual machines,” he says. “We can, however, form an initial estimate based on experience. Use industry norms as a starting point. Then take into account the machine type, speed, load, operating environment and consequences of the failure mode. After you gain some experience with that periodicity, use a technique like age exploration to see if you can safely extend the interval.”

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