• Journal of Korean Society of Water and Wastewater
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• v.29 no.2
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• pp.193-202
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• 2015

The determining the appropriate dosage of coagulant is very important, because dosage of coagulant in the coagulation process for wastewater affects removing the amount of pollutants, cost, and producing sludge amount. Accordingly, in this study, in order to determine the optimal PAC dosage in the coagulation process, CCD (Central composite design) was used to proceed experimental design, and the quadratic regression models were constructed between independent variables (pH, influent turbidity, PAC dosage) and each response variable (Total coliform, E.coli, PSD (Particle size distribution) (< $10{\mu}m$), TP, $PO_4$-P, and $COD_{cr}$) by the RSM (Response surface methodology). Also, Considering the various response variables, the optimum PAC dosage and range were derived. As a result, in order to maximize the removal rate of total coliform and E.coli, the values of independent variables are the pH 6-7, the influent turbidity 100-200 NTU, and the PAC dosage 0.07-0.09 ml/L. For maximizing the removal rate of TP, $PO_4$-P, $COD_{cr}$, and PSD(< $10{\mu}m$), it is required for the pH 9, the influent turbidity 200-250 NTU, and the PAC dosage 0.05-0.065 ml/L. In the case of multiple independent variables, when the desirable removal rate for total coliform, E.coli, TP, and $PO_4$-P is 90-100 % and that for $COD_{cr}$ and PSD(< $10{\mu}m$) is 50-100 %, the required PAC dosage is 0.05-0.07 ml/L in the pH 9 and influent turbidity 200-250 NTU. Thus, if the influent turbidity is high, adjusting pH is more effective way in terms of cost since a small amount of PAC dosage is required.

• Journal of the Korean Dietetic Association
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• v.16 no.4
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• pp.332-340
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• 2010

This study was conducted to develop an optimal composite recipe for nutritional cookies containing beet powder. Flour was substituted with whole wheat flour containing germinated brown rice powder. The sensory optimal composite recipe was determined by making cookies containing two levels of beet powder (A) or butter (B) according to Central Composite Design (CCD) and by conducting the sensory evaluation and instrumental analysis according to Response Surface Methodology (RSM). Using CCD, the results of physical measurement for ten conditions with two variables were obtained. The values of lightness (L), redness (a), and yellowness (b) were in the range of 36.65~49.03, 22.15~29.31, and 13.96~19.34, respectively. Lightness decreased significantly (P<0.001) and redness increased significantly (P<0.01) upon an increase in beet powder. The results of sensory evaluation showed very significant values in color (P<0.05), texture (P<0.05), flavor (P<0.01), taste (P<0.05), and overall quality (P<0.05), whereas those of the instrumental analysis showed significant values in lightness (P<0.001), redness (P<0.01), spread ratio (P<0.01), and hardness (P<0.05). As a result, the optimal sensory ratio of beet cookie was calculated for beet powder 7.75 g and butter 77.88 g.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.523-535
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• 2019

Purpose: We research on the efficient response surface methodology(RSM) design to develop a design space in Quality by Design(QbD). We propose practical designs for the successful construction of the design space in QbD by allowing different number of replicates at the box points, star points, and the center point in the rotatable central composite design(CCD). Methods: The fraction of design space(FDS) plot is used to compare designs efficiency. The FDS plot shows the fraction of the design space over which the relative standard error of predicted mean response lies below a given value. We search for practical designs whose minimal half-width of the tolerance interval per a standard deviation is less than 4.5 at 0.8 fraction of the design space. Results: The practical designs for the number of factors between two and five are listed. One of the designs in the list could be chosen depending on the experimental budget restriction. Conclusion: The designs with box points replications are more efficient than those with the star points replication. The sequential method to establish a design space is illustrated with the simulated data based on the two examples in RSM.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.3
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• pp.387-393
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• 2012

It is very difficult to determine suitable cutting conditions in order to obtain accurate cutting profiles because machining errors caused by tool deflection depend upon cutting conditions. In this study the relationship between real cutting profiles (inclined shapes and machining errors) and cutting conditions was modeled in order to fabricate draft angle on micro molds. CCD (Central Composite Design) of DOE (Design Of Experiment) and RSM (Response Surface Method) were applied in order to model the relationship between cutting conditions and machining errors. In order to use CCD the range of radial depth of cut was chosen by $10-90{\mu}m$ and the range of feedrate was chosen by 200-300mm/min, and 9 points of cutting conditions were chosen inside determined ranges. Then, actual cutting processes were carried out as respect to 9 points of cutting conditions, draft angles and real cutting profiles were measured on cutting profiles, each response surface function was determined by conducting response surface analysis and the functions were represented by 3-dimensional graphs, contour lines and $101{\times}101$ matrices. Consequently it is possible to determine suitable cutting conditions in order to obtain arbitrary given draft angles and cutting profiles by using modeling. To validate proposed approach in this study suitable cutting conditions were determined by modeling in order to obtain arbitrary given draft angle and cutting profile, and actual cutting processes were carried out. About 95% of good agreement between predicted and measured values was obtained.

• Food Science and Biotechnology
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• v.18 no.4
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• pp.959-964
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• 2009

Production of the antioxidant substances by Bacillus polyfermenticus SCD was investigated using shake-flask fermentation. The one-factor-at-a-time method was first employed to determine the key ingredients for optimal medium composition, then further investigation of the medium composition was performed using response surface methodology (RSM). The antioxidant activity was measured using 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) assays. After screening various elements, fructose, tryptone, and $MgSO_4\;7H_2O$ were chosen as the main factors for study in the statistical experimental design. Central composite design (CCD) was then used to determine the optimal concentrations of these 3 components. Under the proposed optimized medium containing 2.8% fructose, 1.34% tryptone, 0.015% $MgSO_4\;7H_2O$), 0.5% NaCl, and 0.25% $K_2HPO_4$, the model predicted an antioxidant activity of 80.5% ($R^2=0.9421$. The actual experimental results were in agreement with the prediction.

• Computers and Concrete
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• v.17 no.5
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• pp.629-638
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• 2016

Optimization of the concrete mixture design is a process of search for a mixture for which the sum of the cost of the ingredients is the lowest, yet satisfying the required performance of concrete. In this study, a statistical model was carried out to model a cost effective optimal mix proportioning of high strength self-compacting concrete (HSSCC) using the Response Surface Methodology (RSM). The effect of five key mixture parameters such as water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content on the properties and performance of HSSCC like compressive strength, passing ability, segregation resistance and manufacturing cost were investigated. To demonstrate the responses of model in quadratic manner Central Composite Design (CCD) was chosen. The statistical model showed the adjusted correlation coefficient R2adj values were 92.55%, 93.49%, 92.33%, and 100% for each performance which establish the adequacy of the model. The optimum combination was determined to be $439.4kg/m^3$ cement content, 35.5% W/B ratio, 50.0% fine aggregate, $49.85kg/m^3$ fly ash, and $7.76kg/m^3$ superplasticizer within the interest region using desirability function. Finally, it is concluded that multiobjective optimization method based on desirability function of the proposed response model offers an efficient approach regarding the HSSCC mixture optimization.

• Food Science of Animal Resources
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• v.39 no.1
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• pp.114-120
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• 2019

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. As a design for a response surface experiment, a central composite design (CCD) with multiple runs at the center point is frequently used. However, sometimes there exist situations where some among the responses at the center point are outliers and these outliers are overlooked. Since the responses from center runs are those from the same experimental conditions, there should be no outliers at the center point. Outliers at the center point ruin statistical analysis. Thus, the responses at the center point need to be looked at, and if outliers are observed, they have to be examined. If the reasons for the outliers are not errors in measuring or typing, such outliers need to be deleted. If the outliers are due to such errors, they have to be corrected. Through a re-analysis of a dataset published in the Korean Journal for Food Science of Animal Resources, we have shown that outlier elimination resulted in the increase of the maximum possible R-square that the modeling of the data can obtain, which enables us to improve the quality of response surface analysis.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.199-204
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• 2015

Response surface methodology (RSM) in combination with a 17-run central composite design (CCD) was applied to optimize the non-catalytic hydrolysis of lard using subcritical water to produce fatty acids (FA). The effects of three variables including temperature, molar ratio of water to oil and time, and their relationship on FA content were investigated. A quadratic regression model was employed to predict the FA contents. Optimum reaction conditions for maximizing the FA content were obtained as follows: reaction temperature of $288.5^{\circ}C$, molar ratio of water to oil of 39.5 and reaction time of 29.5 min. Under the optimum conditions, the predicted and experimentally obtained FA contents were 97.06% and 96.99%, respectively.

• Environmental Engineering Research
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• v.25 no.1
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• pp.114-122
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• 2020

This study was aimed at using the Central Composite Design (CCD) and Box-Behnken Design (BBD) to compare the efficiency and to elucidate the main interacting parameters in the upflow anaerobic sludge blanket (UASB) reactor, namely: Organic Loading Rate (OLR), Hydraulic Retention Times (HRT) and pH at a constant temperature of 35℃. Optimum HRT (15 h), OLR (3.5 kg.m^-3.d^-1) and pH (7) resulted in biogas production of 5,800 mL/d and COD removal of 80.8%. BBD produced a higher desirability efficiency of 94% as compared to the CCD which was 92%. The regression quadratic models developed with high R² values of 0.961 and 0.978 for both CCD and BBD, respectively, demonstrated that the interaction models could be used to pilot the design space. BBD model developed was more reliable with a higher prediction of biogas production (5,955.4 ± 225.3 mL/d) and COD removal (81.5 ± 1.014%), much close to the experimental results at a 95% confidence level. CCD model predictions was greater in terms of COD removal (82.6 ± 1.06% > 80.8%) and biogas production (4,636.31 mL/d ± 439.81 < 5,800 mL/d) which was less than the experimental results. Therefore, RSM can be adapted for optimizing various wastewater treatment processes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.455-461
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• 2005

This research studied robust design of composite hand for LTR (LCD glass Transfer Robot). $1^{st}$ DOE (Design of Experiment) was conducted to find out vital few Xs. 108 experiments were performed and their results were statistically analyzed. Pareto chart analysis shows that the geometric parameters (height and width of composite beam) are more important than material parameters $(E_{1},\;E_{2})$ or stacking sequence angle. Also, the stacking sequence of mid-layer is more important than that of outer-layer. The main effect plots shows that the maximum deflection of LTR hand is minimized with increasing height, width of beam and layer thickness. $2^{nd}$ DOE was conducted to obtain RSM (Response Surface Method) equation. 25 experiments were conducted. The CCD (Central Composite Design) technique with four factors was used. The coefficient of determination $(R^{2})$ for the calculated RSM equation was 0.989. Optimum design was conducted using the RSM equation. Multi-island genetic algorithm was used to optimum design. Optimum values for beam height, beam width, layer thickness and beam length were 24.9mm, 186.6mnL 0.15mm and 2402.4mm respectively. An approximate value of 0.77mm in deflection was expected to be a maximum under the optimum conditions. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the standard deviation of design parameter should be con trolled within $2{\%}$ of average design value