Optimization of Machining Time in Milling Process using Genetic Algorithm Method

Abstract

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.