scholarly journals Optimization of the process parameters in rice mill using Response surface methodology (RSM)

2016 ◽  
Vol 8 (3) ◽  
pp. 1267-1277
Author(s):  
Kumkum Pandey ◽  
Deepa Vinay
Keyword(s):  
Heart Rate ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Reliability And Validity ◽  
Coefficient Of Determination ◽  
Operating Parameters ◽  
Vo2 Max ◽  
Reduce Heart Rate ◽  
Manual Handling ◽  
Load Weight

Objective of the current study was to analyze a wooden plank used as a loading ramp to perform manual handling task with a view to redesign and develop the new one for agriculture. Developed ramp was more wide, static and non slippery than the wooden plank. For this purpose experiments were conducted on a group of 10 experienced manual handlers in the KLA rice mill of Rudrapur Block, district Udhamsingh Nagar, Uttarakhand, India. The reliability and validity of the developed, modern loading ramp was assessed by using response surface methodology in terms of change in MSD, heart rate and VO2 max. Therefore RSM was applied to optimize the operating parameters of ramp such as load weight, height of ramp and time. As per Box Behenken design total 17 experiments were carried out. Each parameter was varied over three levels as load weight of 40, 50 and 60 kg., height of ramp 3, 4 and 5 feet, and the time viz. 3, 4 and 5 min. ANOVA test and coefficient of determination (R2) were applied. In result it was observed that use of developed pant loading ramp was able to reduce heart rate of selected respondent’s from 135.4 beats/min. to 126.76 beats/min., MSD from 85.45 to 22.80 % and VO2 max from 39.45 to 34L/min.

scholarly journals Prediction of standard aeration efficiency of propeller diffused aeration system using response surface methodology and artificial neural network

2021 ◽  
Author(s):  
Subha M. Roy ◽  
Mohammad Tanveer ◽  
Debaditya Gupta ◽  
C. M. Pareek ◽  
B. C. Mal
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Maximum Deviation ◽  
Operating Parameters ◽  
Aeration Efficiency ◽  
Artificial Neural

Abstract Aeration experiments were conducted in a masonry tank to study the effects of operating parameters on standard aeration efficiency (SAE) of a propeller diffused aeration (PDA) system. The operating parameters include the rotational speed of shaft (N), submergence depth (h), and propeller angle (α). The response surface methodology (RSM) and artificial neural network (ANN) were used for modelling and optimizing the standard aeration efficiency (SAE) of a PDA system. The results of the both approaches were compared for their modelling abilities in terms of coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE), computed from experimental and predicted data. ANN models were proved to be superior to RSM. The results indicate that for achieving the maximum standard aeration efficiency (SAE), N, h and α should be 1,000 rpm, 0.50 m, and 12°, respectively. The maximum SAE was found to be 1.711 kg O2/ kWh. The cross-validation results show that the best approximation of optimal values of input parameters for maximizing SAE is possible with a maximum deviation (absolute error) of ±15.2% between the model predicted and experimental values.

scholarly journals Parametric Investigation and Optimization of the Newly Developed Pant Loading Ramp Machine

2019 ◽  
pp. 1-13
Author(s):  
Kumkum Pandey ◽  
Deepa Vinay
Keyword(s):  
Response Surface Methodology ◽  
Energy Expenditure ◽  
Grip Strength ◽  
Response Surface ◽  
Perceived Exertion ◽  
Model Building ◽  
Coefficient Of Determination ◽  
Rate Of Perceived Exertion ◽  
Cardiac Cost ◽  
Load Weight

Objective of the current study was to optimize newly developed pant loading ramp to perform manual handling task. Pant loading ramp was 19 feet in length, having width of 2 feet, anti-slippery, easy to move due to provision of rotating wheels, adjustable at varying heights of the loading vehicle (between 2.5-5 feet) and reduces the loading time up to 30 minutes.  For this purpose experiments were conducted on a group of 20 experienced manual handlers in rice mills of Udham Singh Nagar district, Uttarakhand, India. The reliability and validity of the developed, loading ramp was assessed by using response surface methodology in terms of change in energy expenditure (EE), rate of perceived exertion (RPE), total cardiac cost of work (TCCW) and grip strength (GS). Therefore Response Surface Methodology (statistical tools to determine the significance of a factor over a response or collection of mathematical and statistical techniques for empirical model building) was applied to optimize the operating parameters of ramp such as load weight, height of ramp and time. As per Box Behenken design total 17 experiments were carried out each of which varied over three levels as load weight (40, 50 and 60 kg.), height of ramp (3, 4 and 5 feet), and time (3, 4 and 5 min.). ANOVA and coefficient of determination (R2) test were applied. In result it was observed that use of pant loading ramp was able to reduce Energy Expenditure (EE) of respondents’ from 14.55 kJ/min. to 11.41 kJ/min., Rate of Perceived Exertion (RPE) from 85.45 to 20%, Total Cardiac Cost of Work (TCCW) from 996.3 to 564.36 beats and Grip Strength (GS) from 47.45 to 3.30% with overall desirability of 0.84%. In comparison with traditional method it was also found to reduce Average Working heart Rate (AWHR) (14.55-11.41), Peak Energy Expenditure (PEE) (16-12), Rate of Perceived Exertion (RPE) (85.45-20), Grip Strength (GS) (47.45-3.30) and Total Cardiac Cost of Work (TCCW) (996.3-564.35). Relative advantages showed that more than 95% users were highly satisfied and found it advantageous.

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.

scholarly journals Optimization of an Ultrasound-Assisted Extraction Condition for Flavonoid Compounds from Cocoa Shells (Theobroma cacao) Using Response Surface Methodology

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 711 ◽  
Author(s):  
Arief Md Yusof ◽  
Siti Abd Gani ◽  
Uswatun Zaidan ◽  
Mohd Halmi ◽  
Badrul Zainudin
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Irradiation Time ◽  
Ultrasound Irradiation ◽  
Coefficient Of Determination ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Ultrasound Assisted ◽  
Experimental Values

This study investigates the ultrasound-assisted extraction of flavonoids from Malaysian cocoa shell extracts, and optimization using response surface methodology. There are three variables involved in this study, namely: ethanol concentration (70–90 v/v %), temperature (45–65 °C), and ultrasound irradiation time (30–60 min). All of the data were collected and analyzed for variance (ANOVA). The coefficient of determination (R2) and the model was significant in interaction between all variables (98% and p < 0.0001, respectively). In addition, the lack of fit test for the model was not of significance, with p > 0.0684. The ethanol concentration, temperature, and ultrasound irradiation time that yielded the maximum value of the total flavonoid content (TFC; 7.47 mg RE/g dried weight (DW)) was 80%, 55 °C, and 45 min, respectively. The optimum value from the validation of the experimental TFC was 7.23 ± 0.15 mg of rutin, equivalent per gram of extract with ethanol concentration, temperature, and ultrasound irradiation time values of 74.20%, 49.99 °C, and 42.82 min, respectively. While the modelled equation fits the data, the T-test is not significant, suggesting that the experimental values agree with those predicted by the response surface methodology models.

scholarly journals Optimization of electrocoagulation of instant coffee production wastewater using the response surface methodology

2017 ◽  
Vol 19 (2) ◽  
pp. 67-71 ◽  
Author(s):  
Ha Manh Bui
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Current Density ◽  
Cod Removal ◽  
Coefficient Of Determination ◽  
Electrolysis Time ◽  
Instant Coffee ◽  
Operating Variables ◽  
Initial Ph

Abstract The COD removal efficiency from an instant coffee processing wastewater using electrocoagulation was investigated. For this purpose, the response surface methodology was employed, using central composing design to optimize three of the most important operating variables, i.e., electrolysis time, current density and initial pH. The results based upon statistical analysis showed that the quadratic models for COD removal were significant at very low probability value (<0.0001) and high coefficient of determination (R2 = 0.9621) value. The statistical results also indicated that all the three variables and the interaction between initial pH and electrolysis time were significant on COD abatement. The maximum predicted COD removal using the response function reached 93.3% with electrolysis time of 10 min, current density of 108.3 A/m2 and initial pH of 7.0, respectively. The removal efficiency value was agreed well with the experimental value of COD removal (90.4%) under the optimum conditions.

Electrochemical treatment of Baker's yeast wastewater containing melanoidin: optimization through response surface methodology

2012 ◽  
Vol 65 (12) ◽  
pp. 2183-2190 ◽  
Author(s):  
E. Gengec ◽  
M. Kobya ◽  
E. Demirbas ◽  
A. Akyol ◽  
K. Oktor
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Current Density ◽  
Baker’S Yeast ◽  
Optimum Operating ◽  
Operating Parameters ◽  
Baker's Yeast ◽  
Toc Removal ◽  
Removal Efficiencies ◽  
Yeast Wastewater

Effluents from Baker's yeast production plant contain a high percentage of color and a large amount of organic load. In the present study, Baker's yeast wastewater (BYW) is treated with the electrocoagulation (EC) process using Al electrodes. Operating parameters (pH, current density, color intensity and operating time) are optimized by response surface methodology (RSM). Quadratic models are developed for the responses which are removal efficiencies of color, chemical oxygen demand (COD) and total organic carbon (TOC) and operating cost (OC). Optimum operating parameters and responses are determined as initial pH 5.2, current density of 61.3 A/m2 and operation time of 33 min, and 71% of color, 24% of COD, 24% of TOC removal efficiencies and OC of 0.869 €/m3, respectively. The quadratic model fits for all responses very well with R2 (&gt;0.95). This paper clearly shows that RSM is able to optimize the operating parameters to maximize the color, COD and TOC removal efficiencies and minimize the OC.

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