Predicting uncertain behavior of industrial system using FM - A practical case

As such the reliability of system is affected by many factors such as design, manufacturing, installation, commissioning, operation and maintenance. Consequently it may be extremely difficult if not impossible to model, analyze and predict the failure behavior of system. To this effect, the authors presented a structured framework which makes use of fuzzy methodology (FM), an approximate reasoning tool to deal with the imprecise, uncertain and subjective information related to system performance. The component related objective events are modeled with the help of the Petri net model of the system. Various parameters of managerial importance such as repair time, failure rate, mean time between failures, availability and expected number of failures are computed to quantify the uncertain behavior of system. Further, to improve upon the reliability characteristics of the system, in-depth qualitative analysis of unit is carried out using failure mode and effect analysis (FMEA) by listing all possible failure modes and their causes. A decision support system based on fuzzy set theory is developed to counter the limitations of traditional FMEA. The framework has been applied to model and analyze a real complex industrial system from paper mill.