Performance Evaluation and Optimization for the Stock Preparation System of A Paper Plant Using Genetic Algorithm

This paper deals with the performance evaluation and optimization for the Stock Preparation system of a Paper Plant using Genetic Algorithm. The Stock Preparation system of a Paper Plant has five main subsystems, arranged in series and parallel. Considering exponential distribution for the probable failures and repairs, the mathematical formulation of the problem is done using probabilistic approach and differential equations are developed based on Markov birth-death process. These equations are then solved using normalizing conditions to determine the steady state availability of the Stock Preparation system. The performance of each subsystem of the Stock Preparation system in a Paper Plant has also been optimized using Genetic Algorithm. Therefore, the findings of the present paper will be highly useful to the plant management for the timely execution of proper maintenance decisions and hence to enhance the system performance.