Abstract

This paper presents the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method and approximation modeling method with Radial Basis Function (RBF) neural network structure. The complex tool holder is used for holding a (milling/drilling) tool of a machine tool. The engineering problem of complex tool holder results from the twisting of spindle of tool holder. For this purpose, we present the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method (specifically a module of iSight^® FD-3.1) and approximation modeling method with Radial Basis Function (RBF) (another module of iSight^® FD-3.1) neural network structure

• Keywords: Optimized Approximation(최적근사화),Finite Element Modeling(유한요소모델링),Complex Tool Holder Spindle(복합툴홀더스핀들),Optimal Latin Hypercube(OLH : 최적라틴하이퍼큐브),Radial Basis Function(RBF) Neural Network(RBF뉴럴네트워크)