Optimization of Storage Conditions of Malta (Citrus sinensis) Using Response Surface Methodology

2016 ◽  
Vol 12 (5) ◽  
pp. 507-514 ◽  
Author(s):  
Rishi Richa ◽  
J.P. Pandey ◽  
N.C. Shahi ◽  
S.S. Kautkar
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Desirability Function ◽  
Minimum Weight ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Storage Conditions ◽  
Box Behnken Design ◽  
Order Polynomial ◽  
Soluble Solid

Abstract Response surface methodology was used to determine the optimum storage conditions of malta fruits that give minimum weight loss and maximum total soluble solid (TSS) retained value. Scavenger (3–5 g), polythene thickness (75–125 gauge) and fungicide concentration (75–200 ppm) were the factors investigated. Experiments were designed according to Box–Behnken design with these three factors, including central points. For each response, a second-order polynomial model was developed using multiple linear regression analysis. Applying desirability function method, optimum storage conditions were found to be 5 g scavenger, 125 gauge polythene thickness and 200 ppm fungicide concentration.

scholarly journals Effect of Terminalia catappa Leaves Extract on Corrosion of Mild Steel using Response Surface Methodology

2020 ◽  
Vol 27 (2) ◽  
pp. 47-56
Author(s):  
A.O. Okewale ◽  
O.A. Adesina ◽  
B.H. Akpeji
Keyword(s):  
Response Surface Methodology ◽  
Mild Steel ◽  
Response Surface ◽  
Inhibition Efficiency ◽  
Desirability Function ◽  
Inhibitory Effect ◽  
Quadratic Model ◽  
Box Behnken Design ◽  
Terminalia Catappa ◽  
Maximum Inhibition

Effect of Terminalia catappa leaves (TCL) extract in inhibiting corrosion of mild steel was investigated. In order to obtain the maximum inhibition efficiency, optimization of the process variables affecting corrosion of mild steel was carried out using the Box – Behnken Design plan and desirability function of Response Surface Methodology (RSM). The three parameters - varied include; TCL concentration (inhibitor), immersion time, and temperature and there effects in corrosion inhibition were established. The optimum conditions predicted from the quadratic model were inhibitor’s concentratrion (0.39 g/l), exposure time (8.68 hours), and temperature (36.06 oC) with the inhibition efficiency of 91.95 %. The data fitted well to the quadratic model which was validated. Adsorption of the extract’s component on the mild steel was responsible for the inhibitory effect of the TCL extract.The results showed that 97.92% of the total variation in the inhibition efficiency of TCL can be connected to the variables studied. Keywords: Mild steel, acid, Terminalia catappa, Corrosion, Response surface methodology (RSM).

The Optimization of Pb(II),Cu(II),Zn(II) and Cd(II) Ions Removal by Micro-Electrolysis Using Response Surface Methodology

2013 ◽  
Vol 800 ◽  
pp. 537-545
Author(s):  
Jian Ping Xu ◽  
Zhi Huang ◽  
Yan Ling Gao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Mine Drainage ◽  
Polynomial Equation ◽  
Interactive Effects ◽  
Quadratic Model ◽  
Design Matrix ◽  
Box Behnken Design ◽  
Operating Variables ◽  
Order Polynomial

In this study, the Box–Behnken design matrix and response surface methodology (RSM) have been applied in the experiments to evaluate the interactive effects of four most important operating variables: pH (2.0–4.0), temperature (30–40°C )，iron/carbon ratio（1/2–3/2）and iron carbon amounts (2-4) on the removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions in acid mine drainage with micro-electrolysis (ME) . The total 29 experiments were conducted in the present study for the construction of a quadratic model. The independent variables have significant value 0.0001, which indicates the importance of these variables in the ME process. The values of “Prob > F” less than 0.0500 indicate that model terms are significant for the removal of Cr (VI), Ni (II) and Zn (II) ions. The regression equation coefficients were calculated and the data fitted to a second-order polynomial equation for removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions with ME.

scholarly journals Orally disintegrating tablet: formulation design and optimisation using Response Surface Methodology

2005 ◽  
Vol 51 ◽  
pp. 15-22
Author(s):  
Biljana Nestorovska-Gjosevska Nestorovska-Gjosevska ◽  
Marija Glavas-Dodov ◽  
Katerina Goracinova
Keyword(s):  
Response Surface Methodology ◽  
Mechanical Strength ◽  
Factorial Design ◽  
Response Surface ◽  
Active Ingredient ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Contour Plot ◽  
Disintegration Time ◽  
Independent Variables

The objective of this study was to develop diazepam orally disintegrating tablets and to optimize tablets characteristics using response surface methodology (RSM). Tablets were prepared by direct compression of mixture containing mannitol, copovidone, crosspovidone flavor and lubricant. A full factorial design for 2 factors at 3 levels each was applied to investigate the influence of 2 formulation variables on the mechanical strength/hardness, the percent of friability, disintegration time and dissolution of the poorly soluble active ingredient. The amounts of copovidone and crosspovidone were taken as independent variables. All data were analyzed by using statistical program. The results of multiple linear regression analysis revealed that for obtaining a rapidly disintegrating dosage form, tablets should be prepared using an optimum concentration of crospovidone and copovidone. A contour plot is also presented to graphically represent the effect of the independent variables on the tablet hardness, disintegration time, percentage friability and dissolution. A checkpoint batch was also prepared to prove the validity of the evolved mathematical model. 3 level factorial design allowed us to obtain ODT with rapid disintegration and dissolution of the active ingredient with desirable properties of low tablet friability and appropriate mechanical strength (hardness) of the tablet.

Optimisation of the Oil Extraction from Nigella sativa Seeds Using Response Surface Methodology

2017 ◽  
Vol 68 (2) ◽  
pp. 331-336
Author(s):  
Gabriela Isopencu ◽  
Mirela Marfa ◽  
Iuliana Jipa ◽  
Marta Stroescu ◽  
Anicuta Stoica Guzun ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Nigella Sativa ◽  
Polynomial Equation ◽  
Herbaceous Plant ◽  
Box Behnken Design ◽  
Pareto Analysis ◽  
Black Cumin ◽  
Mediterranean Countries ◽  
Experimental Values

Nigella sativa, also known as black cumin, an annual herbaceous plant growing especially in Mediterranean countries, has recently gained considerable interest not only for its use as spice and condiment but also for its healthy properties of the fixed and essential oil and its potential as a biofuel. Nigella sativa seeds fixed oil, due to its high content in linoleic acid followed by oleic and palmitic acid, could be beneficial to human health. The objective of this study is to determine the optimum conditions for the solvent extraction of Nigella sativa seeds fixed oil using a three-level, three-factor Box-Behnken design (BBD) under response surface methodology (RSM). The obtained experimental data, fitted by a second-order polynomial equation were analysed by Pareto analysis of variance (ANOVA). From a total of 10 coefficients of the statistical model only 5 are important. The obtained experimental values agreed with the predicted ones.

scholarly journals Determination of the Optimal Neural Network Transfer Function for Response Surface Methodology and Robust Design

2021 ◽  
Vol 11 (15) ◽  
pp. 6768
Author(s):  
Tuan-Ho Le ◽  
Hyeonae Jang ◽  
Sangmun Shin
Keyword(s):  
Response Surface Methodology ◽  
Transfer Function ◽  
Response Surface ◽  
Robust Design ◽  
Transfer Functions ◽  
Desirability Function ◽  
Likelihood Estimation ◽  
Statistical Simulation ◽  
Screening Procedure ◽  
Function Estimation

Response surface methodology (RSM) has been widely recognized as an essential estimation tool in many robust design studies investigating the second-order polynomial functional relationship between the responses of interest and their associated input variables. However, there is scope for improvement in the flexibility of estimation models and the accuracy of their results. Although many NN-based estimations and optimization approaches have been reported in the literature, a closed functional form is not readily available. To address this limitation, a maximum-likelihood estimation approach for an NN-based response function estimation (NRFE) is used to obtain the functional forms of the process mean and standard deviation. While the estimation results of most existing NN-based approaches depend primarily on their transfer functions, this approach often requires a screening procedure for various transfer functions. In this study, the proposed NRFE identifies a new screening procedure to obtain the best transfer function in an NN structure using a desirability function family while determining its associated weight parameters. A statistical simulation was performed to evaluate the efficiency of the proposed NRFE method. In this particular simulation, the proposed NRFE method provided significantly better results than conventional RSM. Finally, a numerical example is used for validating the proposed method.

scholarly journals Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Oxygen Demand ◽  
Inoculum Size ◽  
Coefficient Of Determination ◽  
Oil Removal ◽  
Box Behnken Design ◽  
Stenotrophomonas Rhizophila ◽  
Crude Oil Removal

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.

Modeling and Optimization of Vibration Amplitude in Turning of Ti-6Al-4V Using Response Surface Methodology

2012 ◽  
Vol 217-219 ◽  
pp. 1567-1570
Author(s):  
A.K.M. Nurul Amin ◽  
Muammer Din Arif ◽  
Syidatul Akma Sulaiman
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Vibration Amplitude ◽  
Desirability Function ◽  
Cutting Speed ◽  
Vibration Sensor ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Work Piece ◽  
Inferior Surface

Chatter is detrimental to turning operations and leads to inferior surface topography, reduced productivity, dimensional accuracy, and shortened tool life. Avoidance of chatter has mostly been through reliance on heuristics such as: limiting material removal rates or selecting low spindle speeds and shallow depth of cuts. But, modern industries demand increased output and not steady operational limits. Various research efforts have therefore focused on developing mathematical models for chatter formation. However, as yet there is no existent model that meets all experimental verification. This research employed a novel technique based on the synergy of statistical modeling and experimental investigations in order to develop an effective empirical mathematical model for chatter amplitude and to subsequently find optimal machining conditions. Ti-6Al-4V, Titanium alloy, was used as the work-piece due to its increased popularity in applications related to aerospace, automotive, nuclear, medical, marine etc. A sequence of 15 experimental runs was conducted based on a small Central Composite Design (CCD) model in Response Surface Methodology (RSM). The primary (independent) parameters were: cutting speed, feed, and depth of cut. The tool overhang was kept constant at 70 mm. An engine lathe (Harrison M390) was employed for turning purposes. The data acquisition system comprised a vibration sensor (accelerometer) and a signal conditioning unit. The resultant vibrations were analyzed using the DASYLab 5.6 software. The best model was found to be quadratic which had a confidence level of 95% (ANOVA) and insignificant Lack of Fit (LOF) in Fit and Summary analyses. Desirability Function (DF) approach predicted minimum vibration amplitude of 0.0276 Volts and overlay plots identified two preferred machining regimes for optimal vibration amplitude.

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