In order to predict vibrations occurred during end-milling processes, the cutting dynamics was modelled by using neural network and combined with structural dynamics by considering dynamic cutting state. Specific cutting force constants of the cutting dynamics model were obtained by averaging cutting forces. Tool diameter, cutting speed, fled, axial and radial depth of cut were considered as machining factors in neural network model of cutting dynamics. Cutting farces by test and by neural network simulation were compared and the vibration displacement during end-milling was simulated.

The characteristics of grinding and wear behavior of diamond wheel for grinding ceramic materials was investigated in this study. In case of $Si_3N_4$, the wear of wheel was large, the finding force was relatively stable and the fluctuation of surface roughness n small. On the other hand in case of $Al_2O_3$ and $ZrO_2$, the wear of wheel and surface roughness were decreasing, the grinding force was increasing. During grinding with vitrified bond wheel, $Si_3N_4$ shows renewal of cutting edge while $Al_2O_3$ and $ZrO_2$ show glazing phenomenon of cutting grains. We have found that it possible to observe the behavior of grinding wheel by grinding ratio, grinding resistance, surface roughness and cutting edge ratio. Through the grinding experiments, it was found that grinding life of diamond wheel is 20 times for $Si_3N_4$, and 40 times fir $Al_2O_3$ and $ZrO_2$.

A feature-based inspection planning system is proposed in this research to develop more efficient measuring methodology for the OMM(On-Machine Measurement) or CMM(coordinate Measuring Machine) for complicated workpiece having many primitive form features. This paper is proposed solution that optimum inspection sequence of the objective features. The sequences are determined by analyzing the feature information such as the nearest relationship and the possible probe-approach direction(PAD) of the features, and forming feature groups. A series of heuristic rules are developed to accomplish it. Also, each feature is decomposed into its constituent geometric elements for inspection process, and then the number of sampling points, location of the measuring points, optimum probing path are determined.

This study proposed a technique for inverse problem, linear approximation of contact position and loading in single and double meshing of transmission contact element using 2-dimension model considered near the tooth by root stress. Determination of root stress is carried out far the gear tooth by finite element method and boundary element method. Boundary element discretization near contact point is carefully performed to keep high computational accuracy. The predicted results of boundary element method are good accordance with that of finite element method.

The paper will present chip formation mechanism and surface integrity generation mechanism based on the systematical experimental tests. Some basic factors such as the end milling cutter tooth number, cutting forces, cutting temperature, cutting vibration the chip status, the surface roughness, the hardness distribution and the metallographic texture of the machined surface layer are involved. The chip formation mechanism is typical thermal plastic shear localization at high cutting speed with less number of shear ribbons and bigger shear angle than that at low speed, which means lack of chip deformation. The high cutting speed with much more cutting teeth will be beneficial to the reduction of cutting forces, enlarge machining stability mot depression of temperature increment anti-fatigability as well as surface roughness. The burrs always exist both at low cutting speed and at high cutting speed. So the deburring process should be arranged for milling titanium alloy in my case.

Optical and electronic industries are using lapping and polishing processing as a final finish rather than grinding, because they need more accurate parts of brittles non-metallic materials such as single crystals. Sapphire has been ground by the ultra-precision surface grinder having a glass -ceramic spindle of extremely-low thermal expansion with various cup-type resinoid-bonded diamond wheels of #400-#3000 in grain size. Sapphire can be ground in the ductile mode. And also, the surface roughness and grinding conditions has been clarified. The smooth surface of Sapphire less than 1nm RMS, 1nm Ra can be obtained by the ultra-precision grinding without any polishing process.

End-milling have been used widely in industrial system because it is effective to a material manufacturing with various shape. Recently the end-milling processing is needed the high-precise technique with good surface roughness and rapid time in precision machine part and electronic part. The optimum surface roughness has an effect on end-milling condition such as, cutting direction spindle speed, feed rate and depth of cut, etc. Therefore this study was carried out to presume for mutual relation of end-milling condition to get the optimum surface roughness by regression analysis. The results shown that coefficient of determination($\textrm{R}^2$) of regression equation has a fine reliability of 87.5% and regression equation of surface rough is made by regression analysis.

Wear debris can be collected from the lubricants of operating machinery and its morphology is directly related to the fiction condition of the interacting materials from which the wear particles originated in lubricated machinery. But in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefore, if the shape characteristics of wear debris is identified by computer image analysis and the neural network, The four parameter (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction. It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We resented how the neural network recognize wear debris on driving condition.

This study suggests the new ultraprecision finishing techniques for micro die and mold parts using magnetic field-assisted polishing. Conventional magnetic abrasives have several disadvantages, which are missing of abrasive particle and inequal mixture between magnetic particle and abrasive particle. Therefore, bonded magnetic abrasive particles are fabricated by several method. For example, plasma melting and direct bonding. Carbonyl iron powder is used as magnetic particle there silicon carbide and alumina are abrasive particles. Developed magnetic abrasives are analyzed using SEM. Feasibility of magnetic abrasive and polishing performance of this magnetic abrasive particles also have been investigated. After polishing, surface roughness of workpiece is reduced from 85.4 ㎚ Ra to 9 ㎚ RA.

For the analysis of Kirchhoff plate bending problems, a new meshless method is implemented. For the satisfaction of the $C^1$ continuity condition in which the first derivative is treated an another primary variable, Hermite interpolation is enforced on standard reproducing kernel particle method. In order to impose essential boundary conditions on solving $C^1$ continuity problems, shape function modifications are adopted. Through numerical tests, the characteristics and accuracy of the HRKPM are investigated and compared with the finite element analysis. By this implementatioa it is shown that high accuracy is achieved by using HRKPM for solving Kirchhoff plate bending problems.

In this paper, RKPM is extended for solving moderately thick and thin beams. General Timoshenko beam theory is used for formulation. Shear locking is the main difficulty in analysis of these kinds of structures. Shear relaxation factor, which is formulated using the difference between bending and shear strain energy, and corrected shear rigidity are introduced to overcome shear locking. Analysis results obtained reveal that RKPM using introduced methods is free of locking and very effectively applicable to deep beams as well as shallow beams.

Air partial pressure ratio and inlet air mass flow are influenced by water vapor and gaseous fuel in mixture on Compressed Natural Gas (CNG) engines. In this paper, the effects of the water vapor and the gaseous fuel that change the air mass flow and the air-fuel ratio are studied. Effective air mass ratio is defined as the air mass flow divided by mixture mass flow, and also it is applied to the estimation of the inlet air mass flow and the air-fuel ratio. The presence of the gaseous fuel and the water vapor in the mixture reduces the air partial pressure and the effective air mass ratio of the CNG engines. The experimental results for the CNG engine show that estimation of the air-fuel ratio based upon the effective air mass ratio is more accurate than that of a normal mode.

Buckling behavior of stiffened laminated composite cylindrical panel was studied using linear and nonlinear deformation theory. Various buckling load factors are obtained for stiffened laminated composite cylindrical panels with rectangular type longitudinal stiffeners and various longitudinal length to radius ratio, which made from Carbon/Epoxy USN150 prepreg and are simply-supported on four edges under uniaxial compression. Buckling behavior design analyses are carried out by the nonlinear search optimizer, ADS.

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of detect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode But, in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion own. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.