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

Choi Gwang Jin (Agency for Technology & Standards, MOCIE)
Lee Wi Ro (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering)
Choi Suk Woo (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering)
Paik Young Nam (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering)
Publication Information
Journal of the Korean institute of surface engineering / v.36, no.3, 2003 , pp. 284-289 More about this Journal
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;
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