• Journal of Environmental Science International
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• v.18 no.11
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• pp.1225-1234
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• 2009

The aim of this research was to apply experimental design methodology in the optimization condition of electrochemical oxidation of Rhodamine B(RhB). The reactions of electrochemical oxidation were mathematically described as a function of parameters amounts of current, NaCl dosage, pH and time being modeled by the use of the central composite design, which was used for fitting quadratic response surface model. The application of response surface methodology using central composite design(CCD) technique yielded the following regression equation, which is an empirical relationship between the removal efficiency of RhB and test variable in actual variables: RhB removal (%) = 3.977 + 23.279$\cdot$Current + 49.124$\cdot$NaCI - 5.539$\cdot$pH - 8.863$\cdot$time - 22.710$\cdot$Current$\cdot$NaCl + 5.409$\cdot$Current$\cdot$time + 2.390$\cdot$NaCl$\cdot$time + 1.061$\cdot$pH$\cdot$time - $0.570{\cdot}time^2$. The model predicted also agree with the experimentally observed result($R^2$ = 91.9%).

• Journal of the Korean Society for Precision Engineering
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• v.32 no.9
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• pp.815-824
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• 2015

In this study, we conducted the approximate multi-objective optimization of gap sizes of pressurized-water reactor (PWR) annular fuels. To determine the contacting tendency of the inner-outer gaps between the annular fuel pellets and cladding, thermoelastic-plastic-creep (TEPC)analysis of PWR annular fuels was performed, using in-house FE code. For the efficient heat transfer at certain levels of stress, we investigated the tensile, compressive hoop stress and temperature, and optimized the gap sizes using the non-dominant sorting genetic algorithm (NSGA-II). For this, response surface models of objective and constraint functions were generated, using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by NSGA-II were verified through the TEPC analysis, and we compared the obtained optimum solutions and generated errors from the CCD and D-optimal design. We observed that optimum solutions differ, according to design of experiments (DOE) method.

• Journal of Welding and Joining
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• v.34 no.3
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• pp.23-30
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• 2016

This paper discusses the optimization of friction stir spot welding (FSSW) process parameters for joining Aluminum alloy (AA6061-T6) with Magnesium alloy (AZ31B) sheets. Prior to optimization an empirical relationship was developed to predict the Tensile Shear Fracture Load (TSFL) incorporating the four most important FSSW parameters, i.e., tool rotational speed, plunge rate, dwell time and tool diameter ratio, using response surface methodology (RSM). The experiments were conducted based on four factor, five levels central composite rotatable design (CCD) matrix. The maximum TSFL obtained was 3.61kN, with the tool rotation of 1000 rpm, plunge rate of 16 mm/min, dwell time of 5 sec and tool diameter ratio of 2.5.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1055-1056
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• 2011

This paper deals with optimum design criteria for maximum torque density & minimum current density of a single phase line-start permanent-magnet motor (LSPMM) using RSM (Response Surface Methodology) & FEM (Finite Element Method). The focus of this paper is to find a design solution through the comparison of torque density and minimum current density resulting from rotor shape variations. And then, a central composite design (CCD) mixed resolution is introduced, and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.211-216
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• 2015

Recently, because of the growth in the leisure industry and interest in health, the demand for bicycles has increased. In this research, considering the vertical load on a bike frame under static state conditions, the deflection and mass of the bike frame were minimized by satisfying the service condition and performing optimization. The thickness of the bicycle-frame tube was set to a design variable, and its sensitivity was confirmed by an analysis of means (ANOM). To optimize the solution, a response-surface-method (RSM) model was constructed using D-Optimal and central composite design(CCD). The optimization was performed using a non-dominant sorting genetic algorithm (NSGA-II), and the optimal solution was verified by finite-element analysis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.167-170
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• 2000

Recently the sub-micron structured substrates of 0.74 ${mu}ell$ track pitch and 800 $\AA$groove depth are required for DVD-RAM and the track pitch is expected to be narrower as the need for the information storage density is getting higher. For the accurate replication of the land-groove structure in the stamper to the plastic substrates it is important to control the injection -compression molding process such that the integrity of the replication for the land-groove structure is maximized. in the present study polycarbonate substrates were fabricated by injection comression molding and the land-groove structure regarded as one of mold temperature and the compression pressure on the integrity of the replication were examined experimentally. An efficient design methodology using the response surface method (RSM) the central composite design(CCD) technique and the analysis-of-variance (ANOVA) was developed to obtain the optimum processing conditions which maximize the integrity of the replication with a limited number of experiments.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.582-588
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• 2010

This paper presents the Application of Response Surface Method for Optimal Transfer Conditions of MLCC Alignment System. his paper is composed of two parts: (1) Testing performance verification of MLCC alignment system, compared with manual operation; (2) Applying response surface method to figuring out the optimal transfer conditions of MLCC transfer system. Based on the successfully developed MLCC alignment system, the optimal transfer conditions have been explored by using RSM. The simulations using $ADAMS^{(R)}$ has been performed according to the cube model of CCD. By using $MiniTAB^{(R)}$, we have established the model of response surface based on the simulation results. The optimal conditions resulted from the response optimization tool of $MiniTAB^{(R)}$ has been verified by being assigned to the prototype of MLCC alignment system.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.215-223
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• 2012

Response surface methodology(RSM) is a very useful statistical techniques for improving and optimizing the product process. By this reason, RSM has been utilized extensively in the industrial world, particularly in the circumstances where several product variables potentially influence some quality characteristic of the product. In order to estimate the optimal condition of product variables, an experiment is being conducted defining appropriate experimental region. However, this experimental region can vary with the experimental circumstances and choice of a researcher. Response surface designs can be classified, according to the shape of the experimental region, into spherical and cuboidal. In the spherical case, the design is either rotatable or very near-rotatable. The central composite design(CCD)s widely used in RSM is an example of 5-level and spherical design. The cuboidal CCDs(CCDs with ${\alpha}=1$) is appropriate when an experimental region is cuboidal but this design dose not satisfy the rotatability as it is not spherical. Practically, a 3-level spherical design is often required in the industrial world where various level of experiments are not available. Box-Behnken design(BBD)s are a most popular 3-level spherical designs for fitting second-order response surfaces and satisfy the rotatability but the experimental region does not vary with the number of variables. The new experimental design with expanded experimental region can be considered if the predicting response at the extremes are interested. This paper proposes a new 3-level spherical RSM which are constructed to expand the experimental region together with number of product variables.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.10
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• pp.568-574
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• 2017

The purpose of this study was to optimize experimental conditions (time ($X_1$) (ranging of 26.36 - 93.64 min), concentration of sulfuric acid ($X_2$) (ranging of 0-2.5%) and temperature ($X_3$) (ranging of $136.4-203.6^{\circ}C$) for an organosolv pretreatment process to extract lignin from waste wood. The resulting quadratic model equation using RSM (response surface methodology) represented y (lignin yield) = $-79.89+0.91X_1+9.8X_2-2.54{\times}10^{-3}X_1{^2}-2.11X_2{^2}$. The $R^2$ (coefficient of determination) value of 0.8531 for a model indicates this model has statistically significant predictors at the 10% levels. The predictive results optimized by quadratic model produced a lignin yield of 12.46 g/100 g of dry wood under conditions of $178.2^{\circ}C$ and 2.32% $H_2SO_4$. The lignin yield was more affected by the acid catalyst concentrations than the reaction temperature, but the reaction time was not an influential factor for improving lignin extraction from waste wood in this organosolv pretreatment. According to ANOVA (analysis of variance), the significance probability (p-value) of model was smaller than 0.001 and simulation of obtained model equations showed a good reproducibility based on actual organosolv tests under optimal conditions.

• Journal of the Korean GEO-environmental Society
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• v.12 no.4
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• pp.25-31
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• 2011

In this study, the experimental design methodology was applied to optimize 1,4-dioxane treatment in E-beam process. Main factor was mathematically described as a function of parameters 1,4-dioxane removal efficiencies(%), TOC removal efficiencies(%) modeled by the use of the central composite design(CCD) method among the response surface methodology(RSM). Concentration of 1,4-dioxane is designated as "$x_1$" and Irradiation intensity is designated as "$x_2$". The regression equation in coded unit between the 1,4-dioxane concentration and removal efficiencies(%) was $y=71.00-10.85x_1+20.67x_2+{1.53x_1}^2-{7.92x_2}^2-1.23x_1x_2$. The regression equation in coded unit between the 1,4-dioxane concentration and TOC removal efficiencies(%) was $y=44.48-13.25x_1+9.54x_2+{5.43x_1}^2-{1.35x_2}^2+4.45x_1x_2$. The model predictions agreed well with the experimentally observed results $R^2$(Adj) over 90%. Toxicity test using algae Pseudokirchneriella Subcapitata showed that the inhibition was reduced according to increasing an E-beam irradiation.