A Hybrid Approach to Failure Analysis Using Stochastic Petri Nets and Ranking Generalized Fuzzy Numbers

We present a novel failure analysis approach combining structural properties of stochastic Petri Nets and flexibility of fuzzy logic. Firstly, we develop a powerful fuzzy ranking technique. We analyze major drawbacks of existing ranking techniques. Then we demonstrate the capabilities of the presented algorithm to overcome such drawbacks. The approach considers weight, spread, and difference of coordinate of the center of gravity (COG) point of each fuzzy number and is able to deal with a wide variety of fuzzy numbers. Using this technique, we utilize isomorphism between stochastic Petri Nets and their corresponding Markov chains and present a failure analysis algorithm incorporating some critical factors. This algorithm can be implemented in diverse industrial applications