An efficient approach for availability analysis through fuzzy differential equations and particle swarm optimization

This article formulates a new technique for behavior analysis of systems through fuzzy Kolmogorov's differential equations and Particle Swarm Optimization. For handling the uncertainty in data, differential equations have been formulated by Markov modeling of system in fuzzy environment. First solution of these derived fuzzy Kolmogorov's differential equations has been found by Runge-Kutta fourth order method and thereafter the solution has been improved by Particle Swarm Optimization. Fuzzy availability is estimated in its transient as well as steady states. Sensitivity analysis has also been done to find the relative importance of a particular component of the system. Butter oil processing plant as an industrial system has been studied as a case for application of the proposed approach.

Keywords:

Availability , Markov Model , Fuzzy numbers , Optimization , Particle Swarm Optimization (PSO) , Kolmogorov's differential equations