Optimization of Force and Power Imposed on Continuous Tandem Cold Rolling Rollers Using a Multiple-Function Genetic Algorithm

The amount of energy consumed in the production lines such as cold rolled process is one of the fundamental problems in the energy infrastructure of manufacturing sectors. Accordingly, much attention should be directed towards optimizing the power consumption of production lines using reasonable methods. Furthermore, the powers exerted on such equipment must be modified to find an optimized energy consumption level. This study tries to examine the optimization of forces and powers imposed on the continuous tandem cold rolling rollers of metal sheets using MATLAB and genetic algorithm. Firstly, some relationships and calculations of rolled metal sheets are analyzed. Then parameters, such as percentage of thickness reduction, mean pressure, yield stress, power of rollers and exerted torque, are calculated. All the governing relationships are programmed using MATLAB software. Having compared the mentioned two methods, genetic algorithm is used to determine the optimal required power. The results show that the optimized powers generated by genetic algorithm method are in good agreement with experimental observations. Also, the powers of rolling rollers and standard deviations of powers are calculated and, then, the two functions are compared and the optimum point between them is optimized.