• 한국환경보건학회지
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• 제36권4호
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• pp.313-322
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• 2010

The aim of this research was to apply experimental design methodology to optimization of conditions of electrochemical oxidation of Rhodamine B (RhB) and N, N-Dimethyl-4-nitrosoaniline (RNO, indicative of the OH radical). The reactions of electrochemical oxidation of RhB degradation were mathematically described as a function of the parameters of current ($X_1$), NaCl dosage ($X_2$) and pH ($X_3$) and modeled by the use of the central composite design. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the removal efficiency of RhB and RNO and test variables in a coded unit: RhB removal efficiency (%) = $94.21+7.02X_1+10.94X_2-16.06X_3+3.70X_1X_3+9.05X_2X_3-{3.46X_1}^2-{4.67X_2}^2-{7.09X_3}^2$; RNO removal efficiency (%) = $54.78+13.33X_1+14.93X_2- 16.90X_3$. The model predictions agreed well with the experimentally observed result. Graphical response surface and contour plots were used to locate the optimum point. The estimated ridge of maximum response and optimal conditions for the RhB degradation using canonical analysis was 100.0%(current, 0.80 A; NaCl dosage, 2.97% and pH 6.37).

• 한국축산식품학회지
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• 제39권1호
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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.

• 한국미생물·생명공학회지
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• 제48권1호
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• pp.48-56
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• 2020

This study aimed to optimize the culture conditions to improve the crude biosurfactant activity of Bacillus pumilus IJ-1, using a 3³ full-factorial design of response surface methodology (RSM). It was found that submerged fermentation of B. pumilus improved the activity of the crude biosurfactant. The factors selected for optimization were NaCl concentration, temperature, and tryptone concentration. Response surface analysis revealed that the fitted quadratic model was statistically significant and produced an adequate R² value (0.9898) and a low probability value (<0.0001). The optimum level for each factor was found to be 0.567% (w/v) NaCl, 21.851℃ and 0.765% (w/v) tryptone, respectively. Crude biosurfactant activity was found to be most affected by tryptone concentration; then temperature, and finally NaCl concentration. Our results may potentially facilitate large-scale biosurfactant production from B. pumilus IJ-1.

• 한국식품영양학회지
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• 제7권2호
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• pp.137-143
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• 1994

To optimize extrusion cooking condition of single screw extuder for production of puffed rice extrudate using response surface methodology (RSM), moisture content, barrel temperature and screw speed were determined from contour maps, showing relationship between dependent (hardness, expansion ratio, water absorption index, water solubility Index, degree of gelatinization) and independent variables. Optimum operational conditions for production of puffed rice extrudate with suitable quality properties were moisture content 17%, barrel temperature 1$25^{\circ}C$ and screw speed 210 rpm, respectively.

• 경영과학
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• 제24권2호
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• pp.73-80
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• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

• 한국식생활문화학회지
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• 제26권6호
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• pp.717-726
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• 2011

Response surface methodology (RSM) was performed in order to determine the optimal mixing conditions of different amounts of egg and sugar for the preparation of soybean pudding. The experiments were designed according to a central composite design by designating whole egg and sugar content as independent variables. Meanwhile, sweetness, Commission Internationale de I'Eclairage (CIE) color parameters (L*, a* and b* values), hardness, cohesiveness, springiness, and gumminess were response variables. Overall optimization, conducted by overlaying the contour plots under investigation, was able to determine the optimal range of dependent variables within which the 14 responses were simultaneously optimized. The point chosen as a representative of this optimal region corresponded to 50.00 g of whole egg and 31.66 g of sugar. Under these conditions, the model predicted L* value=80.03, a* value=-5.44, b* value=27.86, sweetness=21.23 ($^{\circ}Brix$), hardness=$25.45{\times}10^5$ (dyne/$cm^2$), cohesiveness=67.90 (%), springiness=46.20 (%), and gumminess=12.71 (g).

• Journal of the Korean Wood Science and Technology
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• 제45권2호
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• pp.182-194
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• 2017

The optimum alkali pretreatment parameters (reaction time, reaction temperature and potassium hydroxide concentration) for facilitate the conversion into fermentable sugar (glucose) from steam exploded (severity log Ro 2.45) barley husk were determined using Response Surface Methodology (RSM) based on a factorial Central Composite Design (CCD). The prediction of the response was carried out by a second-order polynomial model and regression analysis revealed that more than 88% of the variation can be explained by the models. The optimum conditions for maximum cellulose content were determined to be 201 min reaction time, $124^{\circ}C$ reaction temperature and 0.9% potassium hydroxide concentration. This data shows that the actual value obtained was similar to the predicted value calculated from the model. The pretreated barley husk using acid hydrolysis resulted in a glucose conversion of 94.6%. This research of steam explosion and alkali pretreatment was a promising method to improve cellulose-rich residue for lignocellulosic biomass.

• 한국식품조리과학회지
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• 제15권3호
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• pp.216-223
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• 1999

The purpose of this study is to find out the optimal mixing ratios of three different amounts of green tea powder, sugar and water for preparation of Sulgiduk through Response Surface Methodology based on the color, sensory, and texture test. The green tea powder levels were included 0.5∼1.0%, water levels were included 15∼25% and sugar levels were included 5∼15% per weight of rice powder. The optimal mixing ratios of a green tea powder, sugar and water for manufacturing the best quality of Sulgiduk were 1.0%, 12% and 22%, respectively.

• 지식경영연구
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• 제20권3호
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• pp.39-47
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• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• 한국정밀공학회지
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• 제22권1호
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• pp.167-174
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• 2005

The design for cold extrusion dies is very important, because the die insert is subjected to very high radial and hoop stresses. The design of cold extrusion dies has many constrained conditions. In this paper, the used assumptions are such that the yield strength of each ring is selected according to the allowable tensile or compressive hoop stress in each ring and the maximum allowable inner pressure, when yielding occurs in one ring of the dies, is obtained by the proposed equation. In order to obtain design variables, such as diameter ratios and interferences, using the maximum inner pressure, the flexible tolerance method was used for shrink-fitted thick-walled cylinders. ANSYS APDL was used to perform the repeated analysis of deformation of the dies due to the variation of the design variables. The response surface methodology is utilized to analyze the relationship between the design variables and the maximum radial displacement of the die insert during extrusion. From the results, it is found that outer diameter of the die insert has the largest effect on the minimization of maximum radial displacement at the inner surface of the dies.