Failure Probability Estimation using Fuzzy Fault Tree Analysis (FFTA) with PDM Data in Process Plants

The Reliability Centred Maintenance strategy aims at deciding predictive maintenance tasks on process equipments. The approaches such as FMEA, HAZOP and FTA are most widely used analytical tools for identifying the predominant failure modes, failure causes and possible remedial measures thereof. The success of predictive maintenance program lies in raising an appropriate ‘Early Warning’ with the help of monitoring the condition of parameters of interest. Randomness of degradation, dependency of the failure causes, uncertain and insufficient data further complicate the estimation of failure probabilities. Process plant engineers always look for a practical and approximate solutions rather than an exact one that uses rigorous analytical models. In the present paper, to estimate the top event failure probability, the ‘Interval of Confidence’ of failure probabilities using fault tree analysis and simulation is proposed. The approach uses fuzzy theory, hence the failure probability may be called as Fuzzy Top Event Probability. Ease and robustness of the approach is demonstrated with condition monitoring data collected on large Electric Motors in an Integrated Steel Plant. This paper also highlights use of the results from the proposed approach to review the maintenance requirements of the equipment to strengthen the implementation of the RCM.