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Predictive maintenance policy based on process data
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DOI：10.1016/j.chemolab.2010.06.009.png)
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For the 'under maintained' and 'over maintained' problems of traditional preventive maintenance, a new predictive maintenance policy is developed based on process data in this article to overcome these disadvantages. This predictive maintenance method utilizes results of probabilistic fault prediction, which reveals evolvement of the system's degradation for a gradually deteriorating system caused by incipient fault. Reliability is calculated through the fault probability deduced from the probabilistic fault prediction method, but not through prior failure rate function which is difficult to be obtained. Moreover, the deterioration mode of the system is determined by the change rate of the calculated reliability, and several predictive maintenance rules are introduced. The superiority of the proposed method is illustrated by applying it to the Tennessee Eastman process. Compared with traditional preventive maintenance strategies, the presented predictive maintenance strategy shows its adaptability and effectiveness to the gradually deteriorating system. (C) 2010 Elsevier B.V. All rights reserved.
Keyword:
Predictive maintenance
Multiple degradation mode
Probabilistic fault prediction
Reliability
Principle component analysis
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