• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.700-703
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• 2004

A reliability analysis and design procedure based on the design of experiment (DOE) is combined with the response surface method (RSM) for numerical efficiency. The procedure established is based on a 3$^n$ full factorial DOE for numerical quadrature using explicit formula of optimum levels and weights derived for general distributions. The full factorial moment method (FFMM) shows good performance in terms of accuracy and ability to treat non-normally distributed random variables. But, the FFMM becomes very inefficient because the number of function evaluation required increases exponentially as the number of random variables considered increases. To enhance the efficiency, the response surface moment method (RSMM) is proposed. In RSMM, experiments only with high probability are conducted and the rest of data are complemented by a quadratic response surface approximation without mixed terms. The response surface is updated by conducting experiments one by one until the value of failure probability is converged. It is calculated using the Pearson system and the four statistical moments obtained from the experimental data. A measure for checking the relative importance of an experimental point is proposed and named as influence index. During the update of response surface, mixed terms can be added into the formulation.

• Tribology and Lubricants
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• v.23 no.4
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• pp.175-179
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• 2007

The effect of manufacturing parameters on friction characteristics of motorcycle break system was studied using a design of experiment. Such parameters conditions have an effect on the frictional factor such as applied load, sliding speed, and number of ventilated disk hole. However, it is difficult to know the mutual relation of these factors. In this study, the friction characteristics using design of experiment containing 3 elements were investigated for an optimal condition for the best motorcycle break system employing full factorial design. From this study, the result was shown that the applied load in frictional factors was the most important, next to sliding speed, number of ventilated disk hole.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.570-573
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• 2003

Wheels for passenger car support the car weight with tires. and they transmit rolling and braking power into the ground. Whittliing away at wheel weight is more effective to boost fuel economy that lighting vehicle body structure. A shape of hole in disk is optimized for minimizing the weight of steel wheel. Pro/ENGINEER program is used for formulating the design model. and ANSYS package is selected for analyzing the design model. It has difficulties 10 interface these commercial software directly. For combining both programs. response surface methodology is applied to construct approximation functions for maximum stresses and maximum displacements are obtained by full factorial design of five levels. This steel wheel is modeled in 14-inch diameter of rim. and wide parameter of hole in disk is only selected as design variable for reducing the weight of steel wheel. PLBA(Pshenichny·Lim-Belegundu_arora) algorithm. which uses the second-order information in the direction finding problem and uses the active set strategy. is used for solving optimization problems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.215-216
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• 2006

The effect of manufacturing parameters on friction characteristics of motorcycle break system was studied using a disk-on-pad type friction tester. Such parameters conditions have an effect on the frictional factor such as applied load, sliding speed, and number of ventilated disk hole. However, it is difficult to know the mutual relation of these factors. In this study, the friction characteristics using design of experiment containing 3 elements were investigated for an optimal condition for the best motorcycle break system employing Full factorial design. From this study, the result was shown that the applied load in frictional factors was the most important, next to sliding speed, number of ventilated disk hole.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.993-996
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• 2005

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, which has many advantages such as good quality, low cost and rapid machining time. but it also has problems like tool break, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is effected by the milling conditions whose evaluated parameters are spindle, feedrate, and width of cut. The experiments are carried out by full factorial design of experiments using and orthogonal array. This paper shows optimal combination and mathematical model for tool life, and the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.2 s.179
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• pp.73-80
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• 2006

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, because it has many advantages such as good quality, low cost and rapid machining time. But it also has problems such as tool breakage, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is affected by the milling conditions whose selected parameters are spindle speed, feedrate, and width of cut. The experiments were carried out by full factorial design of experiments using an orthogonal array. This paper shows optimal combination and mathematical model for tool life, Therefore, the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.E2
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• pp.83-91
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• 2008

This work investigated the methodology to simultaneously optimize the ozone and relative humidity composition for the $NO_x$ degradation using soil biofilter. Experiments were made as a function of inlet ozone concentration ($0{\sim}1,770\;ppb$) and relative humidity ($38{\sim}81%$). Factorial design ($2^2+3$) and response surface methodology by central composite designs were used to examine the role of two factors and optimal response condition on $NO_x$ degradation. It was found that a second-order response surface model can properly interpret the experimental data with an $R^2$-value of 0.9730 and F-value of 71.83, based on which the maximum $NO_x$ degradation was predicted up to 92.8% within our experimental conditions.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.230-230
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• 2009

가스절연 개폐장치 (Gas Insulated Switchgear : GIS)의 고체 스페이서에 경사 기능성 재료 (Functionally Graded Material : FGM)가 적용될 때, 절연성능이 크게 향상된다. 본 논문에서는 FGM 스페이서가 적용된 GIS의 전극 및 스페이서의 형상을 변경하여 최대전계를 완화시켰다. 이를 위해 완전요인실험 (Full Factorial Design : FFD)과 결합된 반응표면법 (Response Surface Methodology : RSM)의 최적화기법을 이용하여, 전극 및 스페이서의 최적 형상을 설계하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.395-396
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• 2006

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.503-506
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• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables without jeopardizing the product. This paper presents a system design for an evolutionary operation software called 'evolutionary optimizer'. The system design is based primarily on data flow diagram. Evolutionary optimizer consists of four modules: factorial design module, many variables module, mixture Production module, and mean/dispersion module.