Development of Decision Support System for a Paper Making Unit of a Paper Plant Using Genetic Algorithm Technique

In this paper, decision support system (DSS) for a paper making unit of a paper plant has been developed by using genetic algorithm. Process industries like paper plant, sugar industry, fertilizer, etc., are comprised of various complex engineering units. A paper plant comprises chipping, digesting, washing, bleaching, screening, stock preparation, paper making units, etc. These units are connected in combined configuration. The paper making unit is having four main subsystems. The mathematical model of paper making unit has been developed by using Markov birth–death process. On the basis of probabilistic approach, the differential equations are formed by using of transition diagram. These equations are solved recursively and then reduced to steady-state conditions, mostly required for the paper industry. Normalizing condition has been used to find out the probability of full working state with or without the use of any standby subsystems, and finally performance model has been developed for paper making unit. Finally, the genetic algorithm technique is used for optimum value of the unit performance by coordinating the parameters of all subsystems of paper making unit.