The Cloud, IoT and Big Data are Shaking Up the Preventive Maintenance Sector

July 20, 2016 By Carl Weinschenk

motors“What’s shaking?” is an informal greeting between friends. “Good Vibrations” is a Beach Boys classic. Both phrases also can be used to describe the predictive maintenance sector.

Motors and other machines have specific and distinctive signatures created by the vibration of their moving parts. A change in these patterns can indicate impending failure or long-term wear and tear that could eventually take the device off line. Assessing these signatures for signs of trouble is a long-established discipline.

The advent of the Internet of Things (IoT), the cloud and big data have dramatically changed the equation. It now is possible to use sensors to collect the telltale signatures and send them to big data analytic engines in off-site datacenters for analysis. Proponents say that the results are more easily generated and are far more accurate.

Predictive maintenance is a big business. Global Market Insights says that the value of the market was $1.5 billion in 2014. It will, the report says, to exceed $3 billion in 2023. Another report – this one from Tech Navio – pegs the compound annual growth rate (CAGR) at 4.02 percent from this year until 2020. Some big names are among the vendors identified in one or both of the reports. These include Emerson Electric, General Electric, Honeywell, Rockwell Automation and Parker-Hannifin.

There are less familiar companies on the list as well. In April, Energy Manager Today posted on ABB Motors and Generators. The company offers what it describes as “fitbits for motors.” The idea is that a sensor is attached to the exterior of a device. The data it collects is sent into the cloud for analysis.

Writing earlier this month at AutomationWorld, Concept System CEO Michael Gurney identified “vibration analysis, thermography, motor testing, tribology and laser shift alignment” as elements of a preventive maintenance program. He also provide a good example of the benefits of such a program:

Let’s look at a cylinder. An operator would never notice any lag between the moment a signal is sent to the cylinder to start and when it actually starts. However, it is possible that the cylinder actually took 50 ms to start; knowing that piece of information could reveal a developing problem. By monitoring that data, you identify a pattern that indicates an impending failure. Once the pattern is identified, the component would be scheduled for repair and be replaced prior to failure, during a “planned maintenance event.”

The bottom line is that tiny abnormalities, if left unchecked, sooner or later lead to big problems. Tools made possible by new IT and telecommunications technologies can do a far better job of identifying these abnormalities.

Another newcomer to the predictive maintenance category is Augury. CEO and Co-Founder Saar Yoskovitz says that the company uses vibration and ultrasound to track performance. One of the first targets is HVAC. The keys, he said, are that Augury replaces expensive hardware with an Android or iOS app and, by using big data analytics, reduces the reliance on insight that human vibration analysts develop over the course of years.

Yoskovitz told Energy Manager Today that the vibration and ultrasound data transmitted by a pump or motor is compared against benchmarks for that type of machine. In the future, the data base will grow to the point at which specific brands and models will be compared,” Yosokvitz said.

There three levels of warnings. “The system lets the operator know what needs to be fixed immediately and what can wait,” Yoskovitz said. “We give the severity level. For instance, we tell you the bearings are in ‘danger,’ which means [it is important to] fix it as soon as you can. Suppose there also is a misalignment. That may be put in ‘monitor,’ meaning we will keep an eye on it. If it changes it will be in ‘alarm,’ which is the third level.”

Yoskowitz said that U.S. Department of Energy says that only 12 percent of commercial facilities use preventive maintenance. If that’s the case, it seems as if a lot of organizations are missing a relatively easy way to avoid significant problems. Yoskovitz offered a simple example that illustrates the benefits: “The core essence of it is that, let’s say, a bolt has become loose,” he said. “You can go in and tighten it today and it will cost you next to nothing – or if you wait six months the whole motor will be torn off the shaft.”

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