• Journal of Magnetics
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• v.15 no.2
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• pp.74-77
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• 2010

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of a Flux Switching Motor (FSM) using response surface methodology (RSM) & finite element method (FEM). The focus of this paper is to find a design solution through the comparison of torque density and torque ripple which vary with rotor shape. And then, a central composite design (CCD) mixed resolution was introduced and analysis of variance (ANOVA) was conducted to determine the significance of the fitted regression model. The proposed procedure allows one to define the rotor dimensions, starting from an existing motor or a preliminary design.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.65-71
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• 2006

This paper presents the robust design of gripper part for a high-speed LCD(Liquid Crystal Display) transfer system. In this paper, the $1^{st}$ DOE(Design of Experiment) is conducted to find out main-effect factors for the design of gripper part. Thirty-six analysis are performed using $ANSYS^{(R)}$ and their results are statistically analyzed using $MINITAB^{(R)}$, which shows that the factors, i.e., First-width, Second-width, Rec-width, and thickness of gripper part, are more important than other factors. The main effect plots shows that the maximum deflection and mass of gripper part are minimized by increasing First-width, Second-width, Rec-width and thickness. The $2^{nd}$ DOE is conducted to obtain RSM(Response Surface Method) equation. The CCD(Central Composite Design) technique with four factors is used. Optimum design is conducted using the RSM equation. Genetic algorithm is used for optimal design. Six sigma robust design is conducted to find out a guideline for control range of design parameter. To obtain six sigma level quality, the standard deviations of design parameters are shown to be controlled within 5% of average design value.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.414.1_415.1
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• 2009

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of Flux Switching Motor (FSM) using RSM & FEM. The focus of this paper is to find a design solution through the comparison of torque density and torque ripple according to 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 Magnetics Society
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• v.20 no.6
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• pp.239-243
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• 2010

This paper deals with the optimum design criteria for the premium efficiency of 250 kW traction induction motor, using response surface methodology (RSM) and finite element method (FEM). The focus of this paper is found firstly a design solution through the comparison of torque according to rotor bar shape, rotor dimensions variations. And secondly a mixed resolution with central composite design (CCD) is introduced and analysis of variance (ANOVA) is conducted to determine the significance of the fitted regression model. The proposed procedure allows to be optimized the rotor copper bar shape, rotor slot, rotor dimensions starting from an existing motor or a preliminary design.

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.316-320
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• 2024

To optimize the emulsion stability and antibacterial activity against Escherichia coli (E. coli) of cosmeceuticals using Scutellaria baicalensis extracts and olive wax as natural emulsifiers, we conducted a study. The independent variables were the amounts of Scutellaria baicalensis extracts and olive wax added. The response variables included the emulsion stability index (ESI) of the cosmeceuticals product and the inhibition diameter against E. coli. Through central composite design-response surface methodology (CCD-RSM), we obtained a statistically significant and reliable regression equation within a 95% confidence interval. By optimizing multiple responses, we determined that the optimal emulsification conditions that satisfied both ESI and E. coli inhibition diameter were 3.7 wt% of Scutellaria baicalensis extracts and 2.7 wt% of olive wax. The predicted ESI and E. coli inhibition diameter were 97.9% and 9.7 mm, respectively. When actual experiments were conducted under the optimal conditions, the measured ESI and E. coli inhibition diameter were 95.0% and 9.4 mm, respectively, with an average error rate of 3.2 ± 0.4%.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• Advances in Energy Research
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• v.4 no.3
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• pp.189-202
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• 2016

This work emphasized optimum production of biodiesel using non-edible Prunus armeniaca (Bitter Apricot) oil via transesterification collected from the high altitude areas of Himachal Pradesh, India. In this study the author produced biodiesel through the process of transesterification by using an alkali catalyst with alcohol (methanol and ethanol), under the varying molar ratio (1:6, 1:9, 1:12), variable catalyst percentage (1% and 2%) and temperature ($70^{\circ}C$, $75^{\circ}C$, $80^{\circ}C$, $85^{\circ}C$). Furthermore, a few strong base catalysts were used that includes sodium hydroxide, potassium hydroxide, sodium metal and freshly prepared sodium methoxide. After screening the catalyst, response surface methodology (RSM) in connection with the central composite design (CCD) was used to statistically evaluate and optimize the biodiesel production operation using NaOH as catalyst. It was found that the production of biodiesel achieved an optimum level biodiesel yield with 97.30% FAME conversion under the following reaction conditions: 1) Methanol/oil molar ratio: 1:6, 2) Reaction time: 3h, 3) Catalyst amount: NaOH 2 wt. %, and 4) Reaction temperature: $85^{\circ}C$. The experimental results showed that the optimum production and conversion of biodiesel through the process of transesterification could be achieved under an optimal set of reaction conditions. The biodiesel obtained showed appropriate fuel properties as specified in ASTM, BIS and En- standards.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.535-541
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• 2015

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM 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 non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

• Advances in environmental research
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• v.9 no.1
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• pp.65-84
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• 2020

The potential use of Sargassum boveanum algae for the removal of uranium from aqueous solution has been studied by varying three independent parameters (pH, initial uranium ion concentration, S. boveanum dosage) using a central composite design (CCD) under response surface methodology (RSM). Batch mode experiments were performed in 20 experimental runs to determine the maximum metal adsorption capacity. In CCD design, the quantitative relationship between different levels of these parameters and heavy metal uptake (q) were used to work out the optimized levels of these parameters. The analysis of variance (ANOVA) of the proposed quadratic model revealed that this model was highly significant (R² = 0.9940). The best set required 2.81 as initial pH(on the base of design of experiments method), 1.01 g/L S. boveanum and 418.92 mg/L uranium ion concentration within 180 min of contact time to show an optimum uranium uptake of 255 mg/g biomass. The biosorption process was also evaluated by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models represented that the experimental data fitted to the Langmuir isotherm model of a suitable degree and showed the maximum uptake capacity of 500 mg/g. FTIR and scanning electron microscopy were used to characterize the biosorbent and implied that the functional groups (carboxyl, sulfate, carbonyl and amine) were responsible for the biosorption of uranium from aqueous solution. In conclusion, the present study showed that S. boveanum could be a promising biosorbent for the removal of uranium pollutants from aqueous solutions.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.359-368
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• 2014

The aim of our research was to apply experimental design methodology in the optimization of N, N-Dimethyl-4-nitrosoaniline (RNO, which is indictor of OH radical formation) degradation using gas mixing-circulation plasma process. The reaction was mathematically described as a function of four independent variables [voltage ($X_1$), gas flow rate ($X_2$), liquid flow rate ($X_3$) and time ($X_4$)] being modeled by the use of the central composite design (CCD). RNO removal efficiency was evaluated using a second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination ($R^2$) value of 0.9111, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the experimental data. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the RNO removal efficiency and independent variables in a coded unit: RNO removal efficiency (%) = $77.71+10.04X_1+10.72X_2+1.78X_3+17.66X_4+5.91X_1X_2+3.64X_2X_3-8.72X_2X_4-7.80X{_1}^2-6.49X{_2}^2-5.67X{_4}^2$. Maximum RNO removal efficiency was predicted and experimentally validated. The optimum voltage, air flow rate, liquid flow rate and time were obtained for the highest desirability at 117.99 V, 4.88 L/min, 6.27 L/min and 24.65 min, respectively. Under optimal value of process parameters, high removal(> 97 %) was obtained for RNO.