Dynamic management of periodicity between measurements in predictive maintenance

Abstract

In practice, on a large number of machines in industrial plants, predictive maintenance relies on periodic measurements to diagnose the condition of the equipment, rather than continuous monitoring of vibrations. In those cases, choosing an appropriate period between measurements is the key to success. Setting a long period implies taking a serious risk of breakdown, while a very short time interval between measurements can unnecessarily increase the costs of the maintenance plan.This work shows a methodology to determine and manage this Time Interval Between Measurements (TIBeM) dynamically adapted to each machine and situation. Depending on the criticality of each machine and its reliability, more specifically, its present diagnosed functional condition and the history of failures and measurements, the most appropriate TIBeM is recalculated each time a new measurement and diagnostic is performed.The described method has been implemented and validated in a large process plant and has led to a considerable improvement in costs and the management of its predictive maintenance plan.