Korean Institute of Surface Engineering

pISSN : 1225-8024 | eISSN : 3399-8403

공학

한국표면공학회지 (36권3호 284-289)

Prediction on the Efficiency of Coated Tool Using Taguchi Design and Neural Network

다꾸지 기법 및 신경망을 이용하여 코팅공구의 성능예측 연구

최광진;이위로;최석우;백영남;
Choi Gwang Jin;Lee Wi Ro;Choi Suk Woo;Paik Young Nam;

경희대학교 기계공학부;경희대학교 대학원, 기술표준원;
Agency for Technology & Standards, MOCIE;KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering;

Abstract

In this study, the prediction on the quality of tools after coating process has been investigated. Under different coating conditions, cutting resistances have been obtained and analyzed with a tool dynamometer to provide optimized coating conditions. The optimized coating conditions Lhave been computed with the most effective factors found by S/N ratio of Taguchi method. To evaluate the influence of the factors on cutting efficiency through the minimum of number of experiment times, the way of neural network design using Taguchi method has been employed.

Keywords

Cutting Resistance;Tool Dynamometer;Neural Network;Taguchi Method;