Optimization Cutting Parameters on Turning Process to Increasing Surface Roughness Quality SKT4 Material with Taguchi Method

Martinus Chorda; Henry Nasution; Edi Sofyan; Albertus Aan Dian Nugroho; Yohanes P Agung P

Martinus Chorda Polman Astra
Henry Nasution Swiss German University
Edi Sofyan Swiss German University
Albertus Aan Dian Nugroho Polman Astra
Yohanes P Agung P Polman Astra

Keywords: Turning process, Roughness Average, Taguchi Method, Backpropagation Neural Network, Genetic Algorithm

Abstract

In this paper, Taguchi Method is used to identify the optimal combination of turning parameters to minimize surface roughness quality. Turning experiments are carried out following to Taguchi Orthogonal Array L27 (3⁴) for the data input and various combinations of four parameters: Cutting speed, feeding, depth of cut and nose radius. The combination of parameters done with experiment on turning machine with the output is Roughness Average (Ra). The Results of the experiment were analyzed with Backpropagation Neural Network to determine the pattern of the relationship between process parameters and response, while Genetic Algorithm method was used for parameter optimization. Combination of the recommended parameters, are cutting speed 131.62 m/min, feeding 0.04 mm/rev, depth of cut 0.3 mm and nose radius is 0.39. As a result, the optimization process can achieve 301.03% from previous experiment. With the result of surface roughness is 1.5 µm.