• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• Resources Recycling
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• v.21 no.3
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• pp.39-47
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• 2012

This study was conducted to optimize a mixing design of lightweight aerated concrete with the blast furnace slag(BFS) using Box-Behnken method, one of response surface designs. The lightweight aerated concrete with the BFS was made on the conditions of steam curing method at atmospheric pressure. The experimental factors were unit Water(W)/total powder($P_d$) ratio, BFS replacement percentage and Al powder addition based on the total powder (${P_d}^*$%). From the results of the response surface analysis, regression models for dried specific gravity and compressive strength of the lightweight aerated concrete were derived. When the target values for dried specific gravity and compressive strength of the lightweight aerated concrete were set at 0.72 and 4.42 MPa respectively, its optimized mixing conditions driven from the regression models were 0.62 of $W/P_d$ ratio, 35.5% of BFS replacement and 0.05% of Al powder addition. This experimental design model was found to be credible by measuring the dried specific gravity and compressive strength of the sample made from the above mixing conditions.

• Food Science and Preservation
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• v.4 no.2
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• pp.123-130
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• 1997

To develop the prediction program for quality change of Citrus unshiu during marketing, we examined the quality characteristics of Citrus unshiu stored at experimental refrigerator set to 4, 8, 12 and 16$^{\circ}C$ for 2 months. According to the storage temperature the changes of quality characteristics were different respectively, but it was most severe during 16$^{\circ}C$ storage. Activation energy and Q10 value were 6683.16 cal/mol K and 1.53 respectively. The determination coefficient of regression equation of pH, acidity and vitamin C by surface response analysis were over 0.85. Using these regression equation, we developed the prediction program for the change of pH, acidity and vitamin C contents. The calculated values and experimental values of pH, acidity and vitamin C contents for short-term storage of Citrus unshiu were coincided well.

• Advances in environmental research
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• v.2 no.4
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• pp.291-308
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• 2013

In the present study, an experimental design methodology was used to optimize the adsorptive removal of Basic Yellow 13 (BY13) using Turkish coal powder. A central composite design (CCD) consisting of 31 experiments was employed to evaluate the simple and combined effects of the four independent variables, initial dye concentration (mg/L), adsorbent dosage (g/L), temperature ($^{\circ}C$) and contact time (min) on the color removal (CR) efficiency (%) and optimizing the process response. Analysis of variance (ANOVA) showed a high coefficient of determination value ($R^2=0.947$) and satisfactory prediction of the polynomial regression model was derived. Results indicated that the CR efficiency was not significantly affected by temperature in the range of $12-60^{\circ}C$. While all other variables significantly influenced response. The highest CR (95.14%), estimated by multivariate experimental design, was found at the optimal experimental conditions of initial dye concentration 30 mg/L, adsorbent dosage 1.5 g/L, temperature $25^{\circ}C$ and contact time 10 min.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.6
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• pp.15-24
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• 2005

The normalization on the characteristics of water level change at the upstream gauging station was attempted according to the operation of drainage sluice gate of the Geumgang estuary dam. The characteristics were normalized by the analysis of water level change and by the linear-regression of the water level data measured at the inner station of Geumgang estuary dam and upstream gauging station. The results of normalization may be referred to the management of Geumgang estuary lake, the operation of pumping and drainage stations in the shore of the lake. The mean response time of water level change on Ibpo, Ganggyeong and Gyuam water level station were 39,81 and 160 minutes, when sluice gate was opened respectively. The mean velocity of surface wave, the mean displacement of water level change, the mean time of water level change and the mean rate of water level change varied largely depending on the location of gauging station and the characteristics of stream section of the water level gauging station.

• Journal of the Korean Wood Science and Technology
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• v.46 no.4
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• pp.380-392
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• 2018

The importance of polysaccharides is increasing globally due to their role as a significant source of dietary prebiotics in the human diet. In the present study, in order to maximize the yield of crude polysaccharides from Pinus densiflora, response surface methodology (RSM) was used to optimize a two-stage extraction process consisting of steam explosion and water extraction. Three independent main variables, namely, the severity factor (Ro) for the steam explosion process, the water extraction temperature ($^{\circ}C$), and the ratio of water to raw material (v/w), were studied with respect to prebiotic sugar content. A Box-Behnken design was created on the basis of the results of these single-factor tests. The experimental data were fitted to a second-order polynomial equation for multiple regression analysis and examined using the appropriate statistical methods. The data showed that both the severity factor (Ro) and the ratio of water to material (v/w) had significant effects on the prebiotic sugar content. The optimal conditions for the two-stage process were as follows: a severity factor (Ro) of 3.86, a water extraction temperature of $89.66^{\circ}C$, and a ratio of water to material (v/w) of 39.20. Under these conditions, the prebiotic sugar content in the extract was 332.45 mg/g.

• Korean journal of food and cookery science
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• v.28 no.6
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• pp.655-663
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• 2012

This study was carried out response surface analysis for brown sauce optimization. Three factors of heating time (10, 20, 30, 40, and 50 min), the added gelatin content (0, 4, 8, 12, and 16%) and the added tomato paste amount (0, 6, 12, 18, and 24%) were encoded into 5 levels (-2, -1, 0, 1, 2). After the central synthesis plan was set up to produce samples in 16 pre-arranged conditions and the sensory tests were conducted, the investigation on optimum level of these factors was conducted. The scope of optimum conditions for extraction was established through reading the range of reaction surfaces superimposed between those representing sensory properties such as color, flavor, taste, viscosity and overall acceptability was established. In this study, it was found out that the scope of optimum conditions for brown sauce extraction was 30 min for heating time, 9.00% for gelatin content and 11.25% for tomato paste amount. The reliability test proved the mentioned scope to have a similar value to that of the estimated scope when compared to the experimental values which was observed through experiments conducted under the same conditions as applied to values predicted through RSM program, enabling the verification of the reliability of derived regression formula.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.115-121
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• 2019

Response surface methodology (RSM) is used to investigate the complex coupling effects of different operating parameters on silicon growth rate in planetary CVD reactor. Based on the computational fluid dynamics (CFD) model, an accurate RSM model is obtained to predict the growth rate with different parameters, including temperature, pressure, rotation speed of the wafer, and the mole fraction of dichlorosilane (DCS). Analysis of variance is used to estimate the contributions of process parameters and their interactions. Among the four operating parameters that have been studied, the influences of susceptor temperature and the operating pressure were the most significant factors that affect silicon growth rate, followed by the mole fraction of DCS. The influence of wafer rotation is the least. The validation tests show that the results of silicon deposition rate obtained from the regression model are in good agreement with those from CFD model and the maximum deviations is 2.15%.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.132-139
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• 2008

To meet demand of big capacity and high speed rotation for washing machine, more stress from bending and twisting are complexly loaded onto the shaft supporting the horizontal drum, causing problems in fracture strength and fatigue life. Also, Vibration occurs due to the frequency of the rotating parts. But, shaft has various design factors such as diameter and distance between bearings according to configuration of shaft, the optimal values can't be easily determined. Using a design of experiment (DOE) based on the FEM (Finite Element Method), which has several advantages such as less computing, high accuracy performance and usefulness, this study was performed investigating the interaction effect between the various design factor as well as the main effect of the each design factor under bending, twist and vibration and proposed optimum design using center composition method among response surface derived from regression equation of simulation-based DOE.

• Environmental Engineering Research
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• v.24 no.1
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• pp.24-30
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• 2019

The present study explores the applicability of response surface methodology (RSM) in conjunction with central composite design (CCD) matrix to statistically optimize ettringite crystallization process for the removal of sulphate from landfill leachate. A three factor-five coded level CCD with 20 runs, was performed to estimate the best fitted model. The RSM results indicated that the fitted quadratic regression model could be appropriate to predict sulfate removal efficiency. The pH was identified as the most dominant parameter affecting sulphate removal. 61.6% of maximum sulphate removal efficiency was obtained at pH of 11.06 for a 1.87 of $Ca/SO_4$ and 0.51 of $Al/SO_4$ molar ratios. The operating cost for ettringite crystallization at optimized conditions was calculated to be 0.52 $/$m^3$. The significance of independent variables and their interactions were tested by analysis of variance. Scanning electron microscope (SEM) and SEM coupled with energy dispersive X-Ray spectroscopy results confirmed the formation of ettringite crystal and were used to describe its morphology features.