실험계획법 및 신경망을 이용한 코팅공구의 성능예측에 관한 연구

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

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 condition has 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.