Laser surface hardening technologies have been used to improve characteristics of wear and to enhance the fatigue resistance for mold parts. The objective of this research work is to investigate the influence of the process parameters, such as power of laser and defocused spot position, on the characteristics of laser surface hardening for the case of SKD61 steel. CW Nd:YAG laser is selected as the heat source. The optical lens with the elliptical profile is designed to obtain a wide surface hardening area with a uniform hardness. From the results of the experiments, it has been shown that the maximum average hardness is approximatly 780 Hv when the power, focal position and the travel of laser are 1,095 W, Omm and 0.3 m/min, respectively. In samples treated with lower scanning speeds, some small carbide particles appear in the interdendritic regions. This region contains fine martensite and carbide in proportions which depend on the local thermal cycle.

In this study, the ultimate goal is to acquire stability when turning around efficiently by using the controller which is applied partial feedback linearization of One-wheel Unicycle Robot. When moving around, linear controller could result in unstable factor according to widening operation range. So in order to reduce instability, I have developed Non-linear Controller using Partial Feedback Linearization. Compared with linear controller, Non-linear Controller guarantees the superiority of Regulating Control and Tracking Control in direct and also revolution motion of Robot. I'm sure of the Non-linear controller performance through many experiments.

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

Aluminum alloy which is one of the light materials has been tried to apply to light weight vehicle body. In order to do that, welding technology is very important. In case of the aluminum laser welding, the strength of welded part is reduced due to porosity, underfill, and magnesium loss. To overcome these problems, laser welding of aluminum with filler wire was suggested. In this study, experiment about laser welding of AA5I82 aluminum alloy with AA5356 filler wire was performed according to process parameters such as laser power, welding speed and wire feed rate. The tensile strength was measured to find the weldability of laser welding with filler wire. The models to estimate tensile strength were suggested using three regression models and one neural network model. For regression models, one was the multiple linear regression model, another was the second order polynomial regression model, and the other was the multiple nonlinear regression model. Neural network model with 2 hidden layers which had 5 and 3 nodes respectively was investigated to find the most suitable model for the system. Estimation performance was evaluated for each model using the average error rate. Among the three regression models, the second order polynomial regression model had the best estimation performance. For all models, neural network model has the best estimation performance.

The characteristic properties of aluminum, high strength stiffness to weight ratio, good formability, good corrosion resistence, and recycling potential make it the ideal candidate to replace heavier materials in the car to respond to the weight reduction demand within the automotive industry. In this paper, FE simulation was carried out to design an appropriate extrusion die for the automobile control arm. Based on the FE simulation result, a new die design has been proposed for uniform material flow in the cross section of extruded product. And then the welding pressure, extrusion load, and the tendency of mandrel deflection were estimated to verify high quality. In the extrusion experiment, it was possible to produce sound product without defects.

The mobility (degree of freedom) of mechanisms can be regarded as independent coordinate to define its position.
This concept is essential for kinematics, and for designing mechanisms in the practical point of view. Gruebler's equation has been applied to estimate the mobility using number of links and joints of a mechanism. In practical case, there are many types of mechanisms, which transfer motion by direct contact between two links. However, no exact kinematic definition has existed for the joint that the contact takes place in a mechanism. In this paper, a new concept of contact joint is defined and modified Gruebler's equation is suggested to calculate mobility of a mechanism with the joint. This concept would be useful in mechanism design because it will be possible to manage many contact mechanisms with kinematic exactness.

Recently, remarkable progress has been made in both technology and production of optical elements including aspheric lens. Especially, requirements for machining glass materials have been increasing in terms of limitation on using environment, flexibility of material selection and surface accuracy. In the past, precision optical glass lenses were produced through multiple processes such as grinding and polishing, but mass production of aspheric lenses requiring high accuracy and having complex profile was rather difficult. In such a background, the high-precision optical GMP process was developed with an eye to mass production of precision optical glass parts by molding press. This GMP process can produce with precision and good repeatability special form lenses such as camera, video camera, aspheric lens for laser pickup, f-B lens for laser printer and prism, and fine glass parts including diffraction grating and V-grooved base. GMP process consist a succession of heating, forming, and cooling stage. In this study, as a fundamental study to develop molds for GMP used in fabrication of glass lens, we conducted a glass lens forming simulation. In prior to, to determine flow characteristics and coefficient of friction, a compression test and a compression forming simulation for PBK40, which is a material of glass lens, were conducted. Finally, using flow stress functions and coefficient of friction, a glass lens forming simulation was conducted.

Recently, a lot of work and interest have been devoted to the development of multiaxial fatigue parameters for fretting fatigue life prediction. In this study, the fretting fatigue life and critical location ware estimated and evaluated through the multiaxial fatigue theories in a cylinder-on-flat contact configuration for Cr-Mo steel, SCM420, the material commonly is used in gears of the automobile and rollers of the conveyor. The strain-life curve was obtained from fatigue test for SCM420. The Fretting fatigue life and critical location were estimated through stress distributions, SWT-parameters and FS-parameters obtained from FEA. This paper showed possibility of applying multi axial fatigue theories to fretting fatigue life prediction comparing predicted life with experimental results.