predictive maintenance

They’re doctors for machines – predicting when bearings or other parts in motors and pumps are starting to go bad so they can be replaced or fixed before the larger piece of equipment fails.

Tucson Electric Power’s Plant Maintenance Optimization Group at the Springerville Generating Station, or SGS, saved the company more than $1 million in 2012 using technology to monitor equipment and catch problems on the front-end, before larger damage could be done.

The work of Gary Gardner, Latigo Pate, Troy Burk and Kevin Lee attracted international attention. TEP won the Emerson Process Experts 2013 Reliability Program of the Year award for its predictive maintenance program at SGS, an honor for which 64 programs around the world were nominated.

Established in 1989, the award recognizes companies that apply the best reliability and maintenance practices worldwide. General Motors, E.I. DuPont and the National Security Agency are among the past winners.

“It is a huge honor to receive this recognition,” said Gardner, PMO Coordinator II, who gave a presentation about the program at the Emerson Global Users Exchange Technical & Management Conference in Grapevine, Texas.

Gardner and his colleagues have specialized equipment and training in fields such as vibration analysis, infrared thermography, oil analysis and electrical motor testing. They use these tools to proactively maintain equipment at SGS.

Predictive maintenance is commonly referred to as condition monitoring or predicting whether equipment is “healthy,” Gardner said. “Because we are able to predict failures before they happen, the company is only paying the cost to replace parts instead of having to spend hundreds of thousands of dollars, or more, for new equipment.”

The company installed a wireless vibration system throughout the SGS coal yard. The system automatically collects vibration data on equipment while it’s running and wirelessly sends it back for analysis. “This is fairly new technology, so I was extremely happy to utilize it to our benefit,” Gardner said.

TEP started predictive maintenance in the late 1990s. With solid support from management, the program grew over the years, expanding at SGS and to the H. Wilson Sundt Generating Station in Tucson.

Gardner and his colleagues have a schedule that determines when it’s time to proactively check each piece of equipment. “Then we load up our vibration data collectors and go check it out,” he said. In addition to vibration data, they collect oil samples and examine parts with an infrared camera. If anything looks suspect after analysis, the part in question is fixed or changed out.

For example, SGS recently purchased a gear box for a 14A conveyor, which transports coal up to the boiler. A predictive maintenance analysis indicated that a part inside of the gear box was loose. The unit was returned to the manufacturer, which took it apart and discovered that some of the bearings were damaged. The unit was still under warranty and was fixed for free. If the gear box had failed, the company would have had to purchase a new one – at a price of about $250,000.

Predictive maintenance personnel seek to have a world-class program by utilizing the latest technology and attending specialized training and through good communication with the mechanics they work with.

“Our program is unique because we’re up to date with the latest technology and training, and we have a management team that supports our program,” Gardner said. “If TEP had not given us the opportunity to go to training or the ability to implement our vibration systems, we would not have won this award, which truly is a great honor.”