Using Analysis of Pareto and Fault Tree to Parameters Simulated in Predictive Maintenance policies and Management Methods


The study was take place with statistical analyasis of available data about faults ( downtime DT, mean time between faults MTBF, mean time to repair MTTR) as dependant variables on fault frequency f as independent variables for fault modes of production equipments and operation times in the sudied period of 26 months. Then simulate it for 25 runs in order to obtain its average that makes the desired results to be more signifigant in generation of mathematical models, which represents the relationships between the predective different times and its comulated density functions. Pareto and Fault tree Analysis of the predictive results showed that the critical equipment (Turbine, Boiler, Condencer, and Generator) with its related faults mode will be a main problem which repeat their faults by 85.16% of the total repetition frequencies while three of them (Turbine, Generator, and Boiler) takes 82.43% of total down times.