• Asian-Australasian Journal of Animal Sciences
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• v.14 no.6
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• pp.844-849
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• 2001

This study was carried out to determine the optimum conditions for cholesterol removal from homogenized milk by treatment with saponin using a response surface methodology (RSM). The effects of temperature, reaction time, and amounts of celite or saponin added on cholesterol removal from milk were investigated. The level of cholesterol removal from milk increased with saponin concentration and varied from 57.4 to 73.3%. The optimum reaction time, amount of celite addition determined by a partial differentiation of the model equation, and amount of saponin addition were 30min, 0.95% and 1.5%, respectively. Under these conditions, the predicted cholesterol removal by RSM was estimated to be 73.4%. The experimental removal value was 73.7%. Thus, there was no appreciable difference between the experimental value and the predicted value based on RSM.

• Journal of Microbiology and Biotechnology
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• v.16 no.9
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• pp.1410-1415
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• 2006

Media components, including date juice, sodium acetate, peptone, and $K_{2}HPO_4$, which were screened by Plackett-Burman fractional factorial design, were optimized for lactic acid production from date juice using the response surface method (RSM). Sodium acetate, peptone (p<0.0001), and $K_{2}HPO_4$ (p=0.0029) were highly significant in influencing the lactic acid production. Close correlationship between predicted and experimental values was observed. When the optimum values of the parameters obtained through RSM (25.0 g/l date sugar, 15.0 g/l sodium acetate, 19.1 g/l peptone, and 4.7 g/l $K_{2}HPO_4$) were applied, lactic acid production (22.7 g/l) increased by 50.33%, compared with unoptimized media (15.1 g/l). The subsequent validation experiments confirmed the validity of the statistical model.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.1
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• pp.103-109
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• 2007

The optimum conditions for springiness of polymannuronate acorn mook, in which polymannuronate was added to acorn powder, was investigated by the response-surface method(RSM). The fractional factorial design with three variables, i.e. polymannuronate addition, water addition and boiling time, and with three levels revealed that the range of acorn springiness was $0.804{\sim}0.987$. The governing equation was also partially differentiated for boiling time, showing that the optimum manufacturing condition for $90^{\circ}C$ is addition of 2% polymannuronate, addition of 120 mL of water, and 60 minutes of boiling time.

• Knowledge Management Research
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• v.21 no.1
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• Korean journal of food and cookery science
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• v.32 no.6
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• pp.704-715
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• 2016

Purpose: This study was conducted to optimize the conditions of manufacturing the wet noodle added with Aloe powder. Methods: The I-optimal design of response surface methodology (RSM) was used for the optimization of added amount of Aloe powder, water content, and kneading time as the independent variables. The quality characteristics (color, texture, water absorption ratio, volume, turbidity) and sensory characteristics (color, flavor, taste, mouth feel, overall acceptance) were analyzed as dependent variables. Results: The lightness, redness, and yellowness of the Aloe noodle were all lowered with the addition of Aloe powder. All texture characteristics such as hardness, elasticity and chewiness of Aloe noodle showed the tendency to increase with increasing amount of Aloe added and kneading time. The water uptake and the volume expansion tended to increase with increasing aloe addition and water addition. As the kneading time increased, the dissolution of solids decreased and the turbidity tended to decrease. Aloe powder content influenced the color, flavor and taste of the noodles most among independent variables, and the mouthfeel of the noodle influenced by the water addition and the kneading time. Conclusion: Aloe noodle showed the best desirability with 3.03% of Aloe powder, 43.56% of water content and 13.06 min of kneading time by RSM analysis. Aloe noodles prepared under these optimized conditions are expected to be able to manufacture and utilize functional Aloe noodles by meeting the content of isobarbaloin, which helps the intestinal functional activity.

• Preventive Nutrition and Food Science
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• v.13 no.3
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• pp.231-236
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• 2008

Response surface methodology (RSM) was used for the analysis and optimization of the production process of strawberry Kochujang. Experiments were carried out according to a central composite design, selecting strawberry puree content and red pepper powder content as independent variables and soluble solids content, moisture content, water activity, color characteristics ($L^*-$, $a^*-$, and $b^*$-values) as response variables. The polynomial models developed by RSM were highly effective for describing the relationships between the study factors and the responses. Kochujang containing a higher amount of red pepper powder had a higher soluble solids content; on the contrary, soluble solids content decreased with the increase in the strawberry puree content in the sample. Moisture content increased with increased strawberry puree content but decreased with increased red pepper powder content. Water activity increased with the increase in strawberry puree content in the sample but was less affected by the amount of red pepper powder content. Decreases in $L^*$-values with increasing amount of red pepper powder were noted. $a^*$-values decreased with the increases in red pepper powder content but increased with the increase in strawberry puree content in the Kochujang formulation. $b^*$-values decreased with the increases in red pepper powder content but was less affected by the strawberry puree content. Overall optimization, conducted by overlaying the contour plots under investigation, was able to point out an optimal range of the independent variables within which the six responses were simultaneously optimized. The point chosen as representative of this optimal area corresponded to strawberry puree content=14.36% and red pepper powder content=11.33%, conditions under which the model predicted soluble solids content=$59.31^{\circ}Brix$, moisture content=45.30% (w.b.), water activity=0.758, $L^*$-value=24.81, $a^*$-value=7.250, and $b^*$-value=10.19.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.4
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• pp.375-383
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• 2023

Malic acid-catalyzed transformation has been developed to produce ginsenoside Rg3 which is increasingly in demand as a functional ingredient. The optimization of the conversion of red ginseng saponin (RGS) to ginsenoside Rg3 by acid catalyzed transformation was carried out using Box-Behnken design (BBD) based on Response Surface Analysis (RSM). The main independent variables were malic acid concentration, temperature, and reaction time. Conversion of ginsenoside Rg3 was performed according to BBD model and optimization conditions were analyzed. The concentration of the converted ginsenoside Rg3 ranged from 1.548 mg/L to 4.558 mg/L, and the highest production was obtained under the condition of reacting 1% malic acid, 50 ℃ and 9h. Consequently, The independent variables affecting the production of ginsenoside Rg3 were identified in the following order: malic acid concentration, reaction time and temperature. In addition, it was confirmed that the interaction between malic acid concentration and reaction time had a greater influence than the temperature.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.387-392
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• 2005

Double-deck train have studied in the next generation train in KRRI. Double-deck train have more seat capacities compared with single deck vehicles and is a efficient, reliable and comfortable alternative train. Because of heavy weight, weight minimization of double-deck train carbody is imperative to reduce cost and extend life-time of train. Weight minimization problem of the double-deck train car-body is required to decide 66 design variables of thicknesses for large aluminum extruded panel while satisfying stress constraints. Design variables are too many and one execution of structural analysis of double-deck train carbody is time-consuming. Therefore, we adopt approximation technique to save computational cost of optimization process. Metamodels such as response surface model (RSM) and kriging model are used to approximate model-based optimization is described. RSM is easy to obtain and expressed explicit function, but this is not suitable for highly nonlinear and large scaled problems. Kriging model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. Target of this design is to find optimum thickness of AEP to minimize weight of doulbe-deck train carbody. In this study, meta model techniques are introduced to carry out weight minimization of a double-deck train car-body.

• Journal of Microbiology and Biotechnology
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• v.20 no.4
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• pp.835-843
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• 2010

The objectives of this study were to investigate the effect of fermentation medium on the hydroxyl radical scavenging activity of exopolysaccharides from Inonotus obliquus by response surface methodology (RSM). A two-level fractional factorial design was used to evaluate the effect of different components of the medium. Corn flour, peptone, and $KH_2PO_4$ were important factors significantly affecting hydroxyl radical scavenging activity. These selected variables were subsequently optimized using path of steepest ascent (descent), a central composite design, and response surface analysis. The optimal medium composition was (% w/v): corn flour 5.30, peptone 0.32, $KH_2PO_4$ 0.26, $MgSO_4$ 0.02, and $CaCl_2$ 0.01. Under the optimal condition, the hydroxyl radical scavenging rate (49.4%) was much higher than that using either basal fermentation medium (10.2%) and single variable optimization of fermentation medium (35.5%). The main monosaccharides components of the RSM optimized polysaccharides are rhamnose, arabinose, xylose, mannose, glucose, and galactose with molar proportion at 1.45%, 3.63%, 2.17%, 15.94%, 50.00%, and 26.81%.

• Structural Engineering and Mechanics
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• v.67 no.3
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• pp.301-310
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• 2018

In this paper, a multi-objective multiparameter optimization procedure is developed by combining rigorously developed metamodels with an evolutionary search algorithm-Genetic Algorithm (GA). Response surface methodology (RSM) is used for developing the metamodels to replace the tedious finite element analyses. A nine-node isoparametric plate bending element is used for conducting the finite element simulations. Highly accurate numerical data from an author compiled FORTRAN finite element program is first used by the RSM to develop second-order mathematical relations. Four material parameters-${\frac{E_1}{E_2}}$, ${\frac{G_{12}}{E_2}}$, ${\frac{G_{23}}{E_2}}$ and ${\upsilon}_{12}$ are considered as the independent variables while simultaneously maximizing fundamental frequency, ${\lambda}_1$ and frequency separation between the $1^{st}$ two natural modes, ${\lambda}_{21}$. The optimal material combination for maximizing ${\lambda}_1$ and ${\lambda}_{21}$ is predicted by using a multi-objective GA. A general sensitivity analysis is conducted to understand the effect of each parameter on the desired response parameters.