Optimization of Machining Time in Milling Process using Genetic Algorithm Method - abdullah, haslina; Isa, Norshafinaz (Research Progress in Mechanical and Manufacturing Engineering, 2023)
The machining time in the milling process is one of the most important factors that affect the performance of machining in milling process. In this study, the genetic algorithm (GA) is being applied to optimize the parameters such as depth of cut, feed per tooth, and cutting speed. In addition, this study also investigates the effect of the population sizes, selection method, and reproduction options in Genetic Algorithm Toolbox (GAT) on machining times in milling processes using the GA method. In this study, the work piece of pocket milling develop by Solidwork software and the fitness function develop by Matlab software. The population sizes are being used in observing the effect towards the parameters and the most significantly is the machining time. Based on the result obtained, the optimized machining time is 8.66007 minutes. The optimize value for depth of cut, feed per tooth and cutting speed are 1mm, 0.127mm/tooth, and 30m/min, respectively were achieved together with the optimize machining time. As a conclusion, Genetic Algorithm is capable to minimize the machining time by determine the optimum machining parameters.