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information from the vibration sensors and temperature ported out so I could watch for changes in the bearing temperature. “We wrote a program to watch and chart it. In the fi rst month, I was notifi ed that bearing temperatures were beyond our parameters. I called the machinist. He said he was monitoring the situation and that the rear bearing was 10° hotter than it should be. Our machinist was moni- toring the situation and said that the rear bearing was 10° hotter than it should be. Upon further exploration, we found the lubrication pump had failed. It was a $300– $500 item but, left unchecked, the repair would have cost tenfold to fi x. Instead, we were monitoring those temper- ature points. We actually caught and prevented the failure with sensors on the machine.” These improvements mean manufacturers that have
already evolved from reactive maintenance to preventive maintenance can now save money by moving to predictive maintenance. “With sensors and the data you harvest from machines,
you can move yourself into more condition-based main- tenance,” Weihl said. “It saves the company money and prevents downed assets.” “Predictive maintenance saves time and money in almost all sequences of the maintenance cycle,” Newton said. Opto 22 recently worked with a customer that was
automating a chain of convenience stores and looking to make its maintenance department more effi cient, he said. “Traditionally when something at a store broke down—
for example, a refrigeration system component—a main- tenance technician had to drive hundreds of miles to the site,” Newton said. “Then the technician had to debug the refrigeration system, identify the failed component and wait for a replacement component to be sent to their loca- tion for installation and calibration. Combining today’s con- nected and intelligent sensors with cloud-based predictive analytics software off ers 24×7×365 autonomous monitor- ing of all system components.” “After moving to a predictive maintenance model, now
the customer knows which system components are begin- ning to wear out before they fail,” he said. “They’re monitor- ing things like compressor temperature, oil temperatures and levels, all remotely and in real time. This gives them the abil- ity to know which system components need to be replaced before a failure occurs. Even better, fi eld technicians know exactly which system component to bring to the store be- fore they leave their shops. This decreases downtime during maintenance cycles and makes each store more profi table.”
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March 2017
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