Computer algorithms are proposed for the estimation of wear appearing in artificial hip joints using finite element analysis based on the modified Archard's wear law, contact features and an analogue wear process. A pin-on-disk plate experiment is reconstructed to assess the efficiency and validity of the algorithms proposed here. Through the successful verification of wear depth and volume loss of the pin-on-disk plate as well as the artificial hip joint, the current algorithms provide significant agreement with experiments, clinical measurements and numerical calculations and are shown to be both valid and feasible. Further investigation into the effect of femoral heads with various sizes suggests that the larger femoral head may induce larger wear volume but gives a smaller wear depth and that wear depth and volume loss are apparently nonlinearly related to the femoral head diameter. It is shown that the current algorithms are useful and helpful in understanding wear behavior for alternative or new designs of artificial hip joints and even for other analogous structures.

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This study presents surface roughness modeling for machined parts based on cutting parameters (spindle speed, cutting depth, and feed rate) and machining vibration in the end milling process. Prediction models were developed using multiple regression analysis and an artificial neural network (ANN) modeling approach. To reduce the effect of chatter, machining tests were conducted under varying cutting parameters as defined in the stable regions of the milling tool. The surface roughness and machining vibration level are modeled with nonlinear quadratic forms based on the cutting parameters and their interactions through multiple regression analysis methods, respectively. Analysis of variance was employed to determine the significance of cutting parameters on surface roughness. The results show that the combined effects of spindle speed and cutting depth significantly influence surface roughness. The comparison between the prediction performance of the multiple regression and neural network-based models reveal that the ANN models achieve higher prediction accuracy for all training data with R = 0.96 and root mean square error (RMSE) = 3.0% compared with regression models with R = 0.82 and RMSE = 7.57%. Independent machining tests were conducted to validate the predictive models; the results conclude that the ANN model based on cutting parameters with machining vibration has a higher average prediction accuracy (93.14%) than those of models with three cutting parameters. Finally, the feasibility of the predictive model as the base to develop an online surface roughness recognition system has been successfully demonstrated based on contour surface milling test. This study reveals that the predictive models derived on the cutting conditions with consideration of machining stability can ensure the prediction accuracy for application in milling process.

Artificial granite material has been used for construction of the high-precision machine due to superior damping ability. However, its lower material stiffness also lessens the application in fabrication of the machine tool. The purpose of this study was therefore aimed to verify the structure performance of the machine tool reformed with artificial granite material, instead of the casting iron. To gain insight into the optimized configuration of the vertical columns and spindle head stock, the static and dynamic characteristics of the machine models with cast iron and granite composites were predicted for comparison. With this, evaluations of the machine with different design were made to examine the experimental measurements on the prototype machine. According to the simulation results and experimental measurements, the static stiffness of the machine tool reformed with granite material is comparable to the original casting machine, differed by 8% approximately. However, granite machine shows superior dynamic stiffness, about 0.5-1.3 times of the conventional casting machine. This study verifies the feasibility and effectiveness in fabrication of the machine tool with the artificial composite material and provides the improvements for further fabrications.

In this project, nonlinear characteristics on the rolling interface of a linear guide were studied by the finite element analysis and experimental verification. Contact of the ball/surface rolling interface in the rolling guides was simulated as a three-dimensional membrane element without thickness. By introducing Hertzian contact theory and applying proper normal/shear stiffness to such contact elements in the overall finite element model, dynamic behaviors of linear guides affected by preload were thus investigated. In the finite element procedure, three contact models, 1D point-to-point, 2D point-to-point and 3D surface-to-surface, were sequentially introduced for purpose of verification with experiments. As a validation in this project, vibrational experiments on linear guides with different preloads were conducted and related frequency spectrums were derived. Both the finite element and the experimental results reveal that the natural frequency of a linear guide increases with the increment of the preload. In addition, the dynamic characteristics predicted by finite element analysis agree well with those measured from instrumental experiments. The proposal of current study may provide an alternate and reliable way for understanding of the dynamic characteristic of the rolling contact components in machine design field.

A numerical approach was proposed to investigate the wear behavior occurred in the artificial hip joints in this paper. In the numerical simulations, the wear coefficients taken from pin-on-disk tests were introduced into the wear analysis model to assess the wear rates of polyethylene acetabular cups against metallic or ceramic femoral heads. For the established material combinations, different values of polyethylene wear rates were obtained respectively, which were not necessarily the realistic one as expected in vivo but could be confirmed after further discussion on the wear mechanism involved in wear tests. Current results indicated that the polyethylene/ceramic couples represented better wear performances than the polyethylene/metal couples. Furthermore, the ratio of wear rates for polyethylene cups against alumina and the metallic femoral heads was 0.5, which agreed well with that deduced from clinical studies or laboratory hip simulators. It is obvious that these comparable wear behaviors observed from clinics or laboratory studies also can be found by means of the numerical simulation.

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