• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.208-213
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• 2001

Objective of this paper is to develop a new approach involving the use of an Artificial Neural Network(ANN) and multiple regression methods in the prediction of process parameters on bead height for GMA welding process. Using a series of robotic are welding, multi-pass butt welds carried out in order to verify the performance of the neural network estimator and multiple regression methods. To verify the developed system, the design parameters of the neural network estimator are selected from an estimation error analysis. The experimental results show that the proposed models can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.903-906
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• 1997

For the net shape manufacturing, grinding is a important process that influences directly the accuracy and the integrity of products. We studied and researched the grinding force, surface roughness, and grinding wheel durability, according to the change of a feed speed of the table and a depth of the cut step by step with experiment that it is used to WA wheel. Workpiece materials were used STDII. The purpose of this study proposes the basic data for design of the machine tool and for controlling the machining parameters to obtain optimum performance of plunge grinding system during operation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.21-26
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• 2003

The well-conditioned observer in a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic issues such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic issues such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_2$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic issues and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.209-214
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• 2003

This study presents the analysis of ball end milling machinability and its application to the determination of the optimum feedrate in the CNC machining process of sculptured surface. The methods which estimate the cutting force system is approached experimentally. The estimation strategy, named technological processor, was applied to the machining process of sculptured surface for finding optimum variable feedrate. From the result of practical implementation for the test model, it is ascertain that the technological processor have brought the dispersion of force profiles. As compared with conventional imposing of cutting conditions, the machining time has reduced by more than 60%.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.65-70
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• 2008

The shape and the material of a reflective sheet affect the amount and the range of retroreflection on incident angle of light, significantly. In this study, the method to determine the shape and the material of the reflective sheet is introduced for the maximum retroreflection. Since the microprism shape with an equilateral triangle base has been used widely, the shape optimization of the microprism shape is carried out. The path of the light within the prism is geometrically calculated to find the relationship between incoming and outgoing light to and from a microprism. The optimal shape of a microprism found by the simulation has almost same figure with the one being used in industry for the maximum retroreflection. It is also found that the refraction index of the reflective sheet is another parameter to control for maximum retroreflection and the range of retroreflection.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1633-1640
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• 2000

The finite element analysis (FEA) is widely used in modem structural dynamics because the performance of structure can be predicted in early stage. However, due to the difficult in determination of various uncertain parameters, it is not be easy to obtain a reliable finite element model. To overcome these difficulties, updating program of FE model is developed by consisting of pretest, correlation and updating. In correlation, it calculates modal assurance criteria, cross orthogonality, mixed orthogonality and coordinate modal assurance criteria. For the model updating, the continuum sensitivity analysis and design optimization tool (DOT) are used. The SENSUP program is developed for model updating to obtain physical parameter sensitivity. The developed program is applied to practical examples such as the base plate of HDD, BLDC spindle motor, and upper housing of induction motor. And the sensor placement for the square plate is compared using several methods.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.45-52
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• 2006

Burrs formed during face milling operations can be very difficult to characterize since there exist several parameters which have complex combined effects that affect the cutting process. Many researchers have attempted to predict burr characteristics including burr size and shape, using various experimental parameters such as cutting speed, feed rate, in-plane exit angle, and number of inserts. However, the results of these studies tend to be limited to a specific process parameter range and to certain materials. In this paper, the Taguchi method, a systematic optimization method for design and analysis of experiments, is introduced to acquire optimum cutting conditions for burr minimization. In addition, an in process monitoring scheme using an artificial neural network is presented for the prediction of burr types.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.6
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• pp.569-575
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• 2014

In this study, the effect of cutting edge geometry, such as helix and rake angles, on surface roughness in ball-end milling is investigated by using the Taguchi method. A set of experiments adopting the $L_{27}(3^{13})$ design with an orthogonal array are conducted with special WC ball-end mills having different helix and rake angles. Analysis of variance (ANOVA) is performed to analyze the effects of tool geometry and machining parameters, such as cutting speed, feed per tooth, and depth of cut, on surface roughness. The ANOVA results reveal that helix and rake angles are critical factors affecting surface roughness; the interaction of helix angle and cutting speed is also important. This research can contribute to novel cutting edge designs of ball-end mills and optimization of cutting parameters.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.1
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• pp.32-39
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• 2000

To optimize the cold start process of a 4-stroke, 8 cylinder Diesel engine, a dynamic simulation model from cranking to idle speed is developed. Physically-based first order starter motor dynamics are used to model the performance of starting process which is very complex. These equations are solved using numerical schemes(Petzold-Gear BDF method) to describe the starting process of diesel engine and to study the effects of starting parameters. The validity of this model is examined by start test. This model can be served as a tool for computer aided control systems design to improve cold improve cold start performance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.8 s.251
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• pp.818-824
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• 2006

The hydrodynamic performance analysis of an axial-flow main coolant pump for the modular nuclear reactor has been carried out using a commercial computational fluid dynamics (CFD) software. The prediction capability of the CFD software adopted in the present study was validated in comparison with the experimental data. Predicted performance curves agree satisfactorily well with the experimental results for the main coolant pump over the normal operating range. π Ie prediction method presented herein can be used effectively as a tool for the hydrodynamic design optimization and assist the understanding of the operational characteristics of general purpose axial-flow pumps.