Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A new approach for ranking fuzzy numbers by distance method
Fuzzy Sets and Systems
Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers
Applied Intelligence
Performance Analysis Using Stochastic Petri Nets
IEEE Transactions on Computers
Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations
Expert Systems with Applications: An International Journal
A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Modeling a flexible manufacturing cell using stochastic Petri nets with fuzzy parameters
Expert Systems with Applications: An International Journal
Analyzing fuzzy risk based on a new fuzzy ranking method between generalized fuzzy numbers
Expert Systems with Applications: An International Journal
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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 x 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.