Availability optimization of refining system of Sugar Industry by Markov process and Genetic Algorithm

In this paper, the availability optimization of refining system of Sugar Industry is done. Sugar industry is a complex repairable system having various subsystems including Feeding, Refining and Crystallization systems etc. Refining system of a Sugar Industry has four subsystems connected in series and parallel configuration. The system is modelled by considering Markov process with the probabilistic approach and then the steady state availability is obtained by using normalizing condition. To find the optimum steady state availability, Genetic Algorithm, a meta-heuristic optimization technique, is executed with the help of MATLAB Toolbox. The objective of this paper is to optimize failure rates and repair rates of all subsystems of the refining system so that the system steady state availability maximizes. The resultant design parameters provide system analyst a decision to how to design failure and repair policies so that the system becomes highly reliable and efficient.