Predictive maintenance techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. This maintenance technique offers cost savings typical time based preventive maintenance.

The main value of Predicted Maintenance is to prevent unexpected equipment failures while maximizing resources. The key is “the right information at the right time”. By knowing which equipment needs maintenance, maintenance work can be better planned (spare parts, people etc.) and what would have been “emergency maintenance” are transformed to shorter “planned maintenance”. Other advantages include increased equipment lifetime, increased plant safety, fewer accidents with negative impact on environment, and optimised spare parts handling.

Predictive maintenance utilizes nondestructive testing technologies such as infrared, acoustic (partial discharge and airborne ultrasonic), corona detection, vibration analysis, sound level measurements, oil analysis, and other specific tests. New methods like Predictive Analytics use actual meter and indicator readings from the machinery to predict failures. Predictive Analytics is the type of statistical methods used by Predikto to help maintenance teams perform preventive maintenance and avoid a failure.

The chart below came from a Predictive Maintenance paper. You can find the entire write up at: http://www1.eere.energy.gov/femp/pdfs/OM_6.pdf

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