Optimization of Paper Making System using Genetic Algorithm

Objectives: In the current work, a paper making system has been under consideration for its availability and optimisation. The objective of this paper is to optimize input variables of the paper making system, to maximize system availability. Methods/Analysis: Paper making system consists of mainly, six subsystems connected in series configuration. For analysis, Repair rates, failure rates, Transition rates and PM rates of each subsystem is taken from maintenance history sheets. Markov process with probabilistic approach is used to model the system for availability with ideal PM and faulty PM. Steady state availability is obtained by using normalizing condition. The optimization of a system availability is executed by genetic algorithms. Findings: Findings present in paper show a significant improvement in the system availability. With ideal PM the availability has been increase upto 93.43% whereas in case of faulty PM the availability has been increase upto 91.89%. Novelty/Improvement: The optimization would help the analysts to design and planning more effective preventive maintenance and repair rate policies.