Response Surface Methodology

Suleyman Neseli et. al. [1] focuses on the influence of tool geometry on the surface finish obtained in turning of AISI 1040 steel. In order to find out the effect of tool geometry parameters on the surface roughness during turning, response surface methodology (RSM) was used and a prediction model was developed related to average surface roughness (Ra) using experimental data.

impeller were optimized using the Response Surface Methodology (RSM). Nine optimization cases were presented. The aerodynamic performance and the flow field of the optimized model were carefully compared with the orig- inal model. The results show that the total pressure difference and the to- tal-pressure efficiency increase by 5.7% and 4.2% respectively after the opti- mization. Compared with the original fan, the flow field inside the impeller of the optimized fan has been improved. The flow separation existing around the blade suction surface outlet is suppressed significantly. For fields in the volute, the optimization scheme has reduced the local vortex intensity and weakened the vortex scale. The flow field stability around the volute tongue is also correspondingly improved.

used both as spice and medicine and its therapeutic benefits of ginger are mainly due to the presence of volatile oils. Consumption of bakery products in the country is increasing day by day and bread is a staple food having several benefit of ginger it may be worthwhile to explore possibility of incorporating ginger extract in wheat flour for the development of bread to provide a convenient . Present study was an effort to standardize the level of ginger extract in formulation for the development of value added bread. To optimize the quantity of sugar and ginger extract to be added, Response Surface Methodology (RSM) was used, while rest of the ingredient for sugar and ginger extract were taken as 20-30 g Control treatment was prepared without ginger extract addition. All combinations and control were subjected for sensory quality evaluation on a 9 point hedonic From the study, it was found that the bread having composition 17.93 g sugar, and 15 ml ginger extract per 100 g of bread was found optimum and the said formulation was acceptable and recommended for value added bread. The optimized bread was found to be superior in terms of minerals, calcium and iron as compared to control bread. Since, the bread was a good source of calcium and iron, hence it can be recommended for consumption for children and old age people. The xcellent antioxidant effect on the bread compared with It can be recommended as one of the value added products.

M.K. Pradhan et al. [13] In this investigation, response surface methodology (RSM) is used to investigate the effect of four controllable input variables namely: discharge current, pulse duration, pulse off time and gape voltage on surface roughness (Ra). A face centred central composite design matrix is used to conduct the experiments on AISI D2 tool steel with copper electrode. The response is modelled using RSM on experimental data. The significant coefficients are obtained by performing analysis of variance (ANOVA) at 95% confidence level. It is found that discharge current and pulse duration are significant factors. RSM is a precision methodology that needs only 30 experiments to assess the conditions and is very effectual. The model sufficiency is very satisfactory as the coefficient of determination is found to be 98.1%. The electro discharge machined surface morphology was examined with a scanning electron microscope (SEM). It is observed from the SEM micrographs that there is a clear deterioration of surface with increase in discharge current.

This study applied response surface methodology and synthetic evaluation method to optimize the alkaloid content of buckwheat sprouts. Solid-liquid (1:10-1:30), ethanol concentration (60%-80%), extraction temperature (20 ℃ -60 ℃ ) and extraction time (20-40 min) were considered as treatment factors in the optimization. All treatment variables shown significant effects on the alkaloid content of buckwheat sprouts (P<0.05). A second order polynomial model produced a satisfactory fitting of the experimental data considering the alkaloid content (R 2 adj =0.8803, S=0.094). Considering the feasibility, the best conditions for the alkaloids content were identified as

Abstract. To produce oligopeptides with high Fisher ratio from the corn gluten meal, the optimal conditions were investigated to absorb aromatic amino acids in the form of free amino acids or peptides in the hydrolysate of corn protein. Response surface methodology was applied to optimize the adsorption conditions, including concentration of NaOH, the concentration of activated carbon and reaction temperature. The highest adsorption rate (50.40%) was obtained at concentration of NaOH at 5.53%, temperature at 24.56°C, concentration of activated carbon at 0.10g/mL, which was in agreement with the predicted value (51.41%) estimated by response surface methodology within a 95% confidence interval. In addition, the final adsorption solution was analyzed by using high performance liquid chromatography to evaluate the kinds and amounts of amino acids in it. The result revealed that Phe was 30.00 mg/100mL, Tyr was 20.98 mg/100mL,and Trp was 4.93 mg/100mL, and the content of aromatic amino acids accounted for 91.82% of the total amino acids. These results support that the aromatic amino acids could be effectively absorbed by the activated carbon under the appropriate conditions, which would contribute to a lot in the process of preparation of high Fischer ratio oligopeptides from corn gluten meal.

Response surface methodology. This research uses the central composite design (CCD) model with 3 independent variables to obtain a response to produce Cyclosporin A, which in this case is in the form of Cyclosporin A concentrate (mg L -1 ). The trial model uses an 8 point fractional factorial 2 3-1 design, 6 star points, and 6 central points, making a total of 20 experiments repeated twice. The central values used are glucose concentrate 25 g L -1 , casein concentrate 8 g L -1 , and KH 2 PO 4 concentrate 0.75 g L -1 . The range and

In this study, oil extracted from coconut fruits was optimized using Response Surface Methodology (RSM). Effects of roasting temperature and roasting time on the yield and oil quality were investigated. Thirteen experimental runs applying a central composite design combined with RSM was employed. The parameters measured were oil yield, free fatty acid, colour, refractive index, specific gravity and pH. Statistical analysis with response surface regression showed that the oil yield, free fatty acid, colour, refractive index, specific gravity and pH of coconut oil were significantly (p<0.05) affected with roasting temperature and time. Based on response surface, optimum conditions were roasting temperature of 110

The Anoxybaccilus DT3-1 is a newly found bacterium that is able to express amylase. The gene that encodes the amylase was recently cloned and expressed in E. coli system. However, the expression level was far too low to be used. The main objective of this study is to enhance the recombinant amylase expression level using pET-22b vector. Another objective of this study is to determine the end product release by the reaction of this amylase. The media optimization was carried out with five different media i.e. LB, TB, SB, CDM 1 and CDM 2. Medium LB was found to be the best medium to support the cell growth and amylase production (72 U/ml). Relevant factors such as the inducer (IPTG) concentration, yeast extract concentration and induction time (OD 600nm ) were optimized through two Response Surface Methodology

Three level variables were employed in this study, requiring 27 experiments. Methanol-to-oil ratio, catalyst concentration and reaction time were the independent variables selected to optimize the yield of Mahua oil after transesterification. A response surface methodology (RSM) was used to examine the influence of these three process variables on the fatty acid methyl esters (FAMEs) content. This methodology is a sequential process that usually originates at one reasonable operating condition, and then requires three points to achieve a set of “better” conditions as rapidly and efficiently as possible.

The response surface methodology ( RSM ) is employed to quantify the relationship between individual responses and input cutting parameters. Response Surface Methodology ( RSM ) can be defined as a collection of statistical and mathematical techniques useful for developing, improving and optimizing processes [4]. The most extensive applications of RSM are in the particular situations where several input variables potentially influence some performance measure or quality characteristic ( i.e. response ) of the process. The input variables are sometimes called independent variables, and are to be controlled by the engineer. In order to investigate the influence of cutting parameters on surface roughness and geometrical error, four independent modeling parameters viz. Spindle speed , depth of cut, feed and stepover are selected as input parameters, while the output responses are the surface roughness and geometrical error. The range of input parameters is decided on the basis of literature available. The necessary data required for developing the response models have been collected by designing the experiments based on Taguchi L 9 orthogonal array design by varying each numeric factor up to 3

Central composite design procedure Response surface methodology (RSM) consists of statistical tools and techniques for estimating functional relationship between variables and responses [24]. A three-level factorial design was established with the help of the Design Expert software (Central Composite Design Expert Version 8.0.3, Stat Ease, Minneapolis, USA). In this study, central composite design (CCD) was used for RSM in the experimental design, which is well suited for fitting a quadratic surface and usually works well for process optimization. The variables selected were pH (X 1 ) time (X 2 ) and ozone dosage (X 3 ) while the response

Response Surface Methodology is an effective statistical technique for optimization of complex processes. It reduces the number of experiment trial and multiple parameters and their interaction could be studied simultaneously in a single experimental trial [18]. RSM is a collection of statistical and mathematical techniques useful for developing, improving and optimizing processes [24]. RSM technique has been employed to optimize parameter for enzymatic fruit juice clarification of fruit juice such as Carambola juice [1], Guava juice [03, 33], Carrot juice [05], Blueberry juice [12], Pineapple- Mango blend [14], Carrot-Orange blend [15], Pineapple juice [26], Sapodilla juice [37] and Banana juice [43]. Nowadays RSM is widely used approach to design of several experiments as it decreases number of trials, time and is less laborious than other approaches [14].

the dye compounds which is harmful to human’s life its removal from industrial waste water would reduce their environmental impact and health effect. Copper nanoparticle (CuNP) is a simple and eco-friendly material which can be used to remove this pollutant. In this paper, copper nanoparticles were synthesized, for removal of AM dye. The experiments were designed by response surface methodology with a modified cubic model to predict the variables. To investigate variables and interaction between them analysis of variance was used with high F-value (1.44), low P-value (<0.0409), non-significant lack of fit, the determination coefficient of 0.898 and the adequate precision of 7.25. Experimental and predicted values of the response illustrated a good correlation. The optimum parameters catalyst amount (0.14 w/w%), initial concentration (7.38 mg/l), reaction time (47.75 s) and pH (2.83) for the highest removal percentage of (96.10%) was attained.

Non-conventional machining technology is effectively used in modern manufacturing industries. This paper investigatesthe influence of three different input parameters such Peak current, Pulse on time and Pulse off Time ofwire electrical discharge machining (WEDM) performances of surface roughness (SR) using response surface methodology with central compositedesign (CCD). The Machining analyses were performed at WEDM machine utilizing 0.25 mm wire as electrode material on aluminium based alloy . The machining characteristicsare significantly influenced by the electrical and non-electrical parameters in WEDMprocess. The impacts of the methodology parameters on surface roughness were assessed by the examination of change (ANOVA). Analysis of variance (ANOVA) was performed to find out the significant influence of each factor.

Statistics is a branch of mathematics used extensively in natural science and also in the engineering field as well as in social science, physics and computing. The machining process selected as for this study is laser cutting process of mild steel. Response surface methodology will be used as a technique for the statistical study where the investigated parameters are cutting speed, frequency and duty cycle and the response is kerf width. The primary focus of this study will be on predicting the responses of a process by statistical means. Statistical approach here refers to an empirical method of describing the relationship between the input factors (parameters) as to how far their influence ranges on the output (responses). It is a mathematical evaluation of signifying the relationship of the parameters to the responses.

[14] Chen, F., Cai, T., Zhao, G., Liao, X., Guo, L. and Hu, X. (2005) Optimizing conditions for the purification of crude octacosanol extract from rice bran wax by molecular dis- tillation analyzed using response surface methodology. Journal of Food Engineering, 70, 47-53.

A clay catalyst (montmorillonite and kaolinite) was prepared and used to degrade three phenolic compounds: hydroquinone, resorcinol and catechol obtained from the treatment the Olive Mill Wastewater (OMW) generated in the production of olive oil. The operating conditions of the de- gradation of these compounds are optimized by the response surface methodology (RSM) which is an experimental design used in process optimization studies. The results obtained by the catalytic tests and analyses performed by different techniques showed that the modified montmorillonites have very interesting catalytic, structural and textural properties; they are more effective for the catalytic phenolic compound degradation, they present the highest specific surface and they may support iron ions. We also determined the optimal degradation conditions by tracing the response surfaces of each compound; for example, for the catechol, the optimal conditions of degradation at pH 4 are obtained after 120 min at a concentration of H 2 O 2 equal to 0.3 M. Of the three phenolic

Chocolate is a luxury food. It is not only popular among children, but also consumed by youth and old age persons. The present project was taken up to develop vitamin-C enriched guava milk chocolate. The purpose of addition of guava powder was to enhance nutritional and sensory qualities of chocolate. Guava is a very rich source of soluble dietary fiber and vitamin-C (an excellent antioxidant). The effect of various ingredients like guava powder, milk powder and cocoa powder on sensory characteristics of the prepared chocolate was studied and their levels were optimized using Response Surface Methodology (RSM) using regression equation model. Optimization of the product was done by maximising the score for sensory characteristics while keeping the hardness of the chocolate in range. The optimised guava milk chocolate constituted 14.13 percent guava power, 15 percent milk powder, 15 percent cocoa powder, 30 percent sugar and 30 percent cocoa butter.

_____________________________________________________________________________________________________ Abstract— This research work was carried out to investigate the application of response surface methodology (RSM) for the optimization of refractive bricks production using Box-Behnken design. The optimum response of refractory bricks produced from local raw materials (clay, kaolin and saw dust) that can retain thermal heat was validated experimentally using the optimum parameters obtained. The produced refractory bricks were characterized at its best optimum condition. The optimum parameters obtained for the refractory bricks are temperature of 870.58 °C, time of 6.5 hrs and composition of 8% sawdust. The ANOVA analysis shows that the model is significant and well represents the experimental data. The characterization of the produced fire bricks show that the firing shrinkage and porosity are 1.67 % - 2.87% and 11.63% - 22.69% respectively while the bulk density decreases with increase in composition (5 - 15%) of saw dust from 1.799 - 2.327g/ m 3 . The cold crushing strength of the sample without sawdust gave the highest