Papers by Author: Wen T. Chien

Abstract: An investigation into the compression forming of cylinder using the commercial code SUPERFORM is developed. The cylinder billet compressed between the upper and lower dies is meshed by a quadrangle elastic-plastic element. The numerical simulation based on the FEM also compares with the slab method established by us. In the slab method analysis, the stress distributions are estimated by considering the coulomb friction between the dies and the cylinder. Throughout this study, the effects of frictional coefficient, rotating angular speed, reduction and aspect ratio etc upon the compression force, the effective stress and the effective strain, and velocity field are discussed systematically. For verifying the validity of two models, comparisons of compression forces based both modes are carried out to prove the feasibility of both models.

Abstract: The purpose of this study is to develop two predictive models for burr height in cutting titanium alloy plates by using Nd:YAG laser. Firstly, Taguchi method has been used to arrange the experimental scheme and analyze the results via analysis of mean . The important laser cutting parameters affecting burr height can be found. It shows that the pressure of assistant gas, the focusing position and the pulsed frequency are the most important cutting parameters in order. Then they have been chosen as the input variables for response surface methodology and used to construct a mathematical equation for predicting burr height. Secondly, the laser cutting parameters and experimental results obtained from conducting the schematic arrangement using Taguchi method and response surface methodology have been treated as training patterns and recalling patterns for the back-propagation neural network. As a result, a predictive model for burr height prediction in laser cutting titanium alloy has been established. To verify the accuracy of above two prediction models, there are 9 sets of experiment have been performed. It shows that the average error for predicting burr height by the mathematical equation derived from response surface methodology is 5.52% and by the predictive model established by back-propagation neural network is 4.51%, respectively. Obviously, both predictive models are good enough for the relational research and practical applications. It can be concluded that the procedure used in this research and the obtaining predictive models can be used practically in correlate industry.

Abstract: A predictive model is presented for the prediction of shear strength in laser welding AISI304 stainless steel. Welding experiments conducted using a pulsed Nd:YAG laser machine while the laser welding parameters and their levels have been arranged according to design of experiments of Taguchi method. The tensile tests are performed after welding and the measurements of tensile strength are further calculated for shear strength. The data can be analyzed using the principles of Taguchi method for determining the optimal laser welding parameters and for investigating the most significant laser welding parameter on shear strength. Furthermore, the results are treated as the training and recalling patterns for constructing a predictive model using back-propagation neuron network to predict shear strength for the range of laser welding operation tested. It is indicated that welding speed is the most significant affecting parameters on shear strength. In addition, an increase in welding speed causes a decrease in shear strength is found. An average error 5.75％for shear strength can be found by comparing the experimental results obtained from conducting verification tests with the predicting values obtained from the established predictive model. It shows that the predictive model is capable of good predicting behavior of laser welding AISI304 stainless steel.