Production Optimization Of A Flexible Manufacturing Cell Using Genetic Algorithms And Simulation

Genetic Algorithms have demonstrated their good performance in combinational search processes. They have been widely used in the field of production programming for manufacturing systems, but not yet for closed loop manufacturing cells. In addition, simulation has become an important tool in order to obtain the necessary information about the capacities and functioning of complex systems quickly and without risking production. This work attempts to combine these two approaches in order to develop an alternative process and an own structure for the design and production programming of a flexible manufacturing cell. We also aim to demonstrate the efficiency of our method in comparison with some of the traditional processes, and hope that it will serve as a reference for future research within the field of production optimization for flexible manufacturing cells.