scholarly journals Optimization of Factorial Design with the type of Plackett-Burman Design to Study the Effects of Organic Rice Production Process: First Step Experiment

2021 ◽  
Vol 10 (3) ◽  
pp. 2080-2084
Keyword(s):  
Experimental Design ◽  
Statistical Model ◽  
Production Process ◽  
Factorial Design ◽  
Process Model ◽  
Basic Principles ◽  
Organic Rice ◽  
Burman Design ◽  
Design Type ◽  
Plackett Burman Design

The research aims at the optimization to determine factors production process of the of the output organic rice so that the best possible set of parameters affecting it can be selected to get the desired output. For this purpose, the effect of various parameters on the organic rice output is studied. To facilitate the study and detailed analysis, a statistical model is constructed which is used to predict and optimize the performance of the system. Efficient organic rice optimization determines the input variable settings to adjust the organic rice of the organic rice according to the consumption of the parts in the next phase of production process.To study the interaction among the factors a 36 factorial experiment approach has been adopted using the two basic principles of experimental design replication and randomization. The process model was formulated based on analysis of variance (ANOVA) and regression of coefficient using Minitab Release 19.00. The output is represented graphically and in the form of empirical model which defines the performance characteristics of the production process of organic rice by factorial design type of Placket-Burman design

Optimization of Factorial Design with the type of Plackett-Burman Design to Study the Effects of Organic Rice Production Process: Second Step Experiment

2021 ◽  
Vol 10 (3) ◽  
pp. 2085-2089
Keyword(s):  
Production Process ◽  
Factorial Design ◽  
Process Model ◽  
Rice Production ◽  
P Value ◽  
Basic Principles ◽  
Organic Rice ◽  
Burman Design ◽  
Level Of Significance ◽  
Plackett Burman Design

This research conducted the second experiment is to evaluate the results of organic rice production by controlling two variables. To consist of the spindle of speed and clearance between the rubber and two levels. The test statistics will be used. Factorial design Choose the type of Plackett-Burman design. Both variables and experiment levels have the effect of organic rice production process at the level of significance. To study the interaction among the factors a 36 factorial experiment approach has been adopted using the two basic principles of experimental design, replication and randomization. The process model was formulated based on Analysis of variance (ANOVA) and regression of coefficient using Minitab Release 15.00. The results showed that both variables were p value is greater than alpha value (0.216 > 0.05). There are no significant differences. Shows that the SS and CL is significant to the effect of organic rice production process. So, the conclusion is accepting H0

Statistical Modeling Approach for Optimization of a Stationary Hook Hopper

2011 ◽  
Vol 110-116 ◽  
pp. 2821-2828
Author(s):  
Astha Kukreja ◽  
Pankaj Chopra ◽  
Akshay Aggarwal ◽  
Pradeep Khanna
Keyword(s):  
Experimental Design ◽  
Statistical Model ◽  
Process Parameters ◽  
Feed Rate ◽  
Process Model ◽  
Basic Principles ◽  
Factors Influencing ◽  
Series Of Experiments ◽  
Rate Optimization ◽  
Feed Rate Optimization

The work aims at the optimization of the output feed rate of a Stationary Hook Hopper Feeder so that the best possible set of parameters affecting it can be selected to get the desired output. For this purpose the effect of various parameters on the feeder output is studied. To facilitate the study and detailed analysis, a statistical model is constructed which is used to predict and optimize the performance of the system. Efficient feed rate optimization determines the input variable settings to adjust the feed rate of the feeder according to the consumption of the parts in the next phase of production. The Stationary Hook Hopper Feeder, whose performance is to be studied, consists of a rotating circular plate and a guiding hook fixed at the centre and running up to the periphery of the plate. As the plate rotates, the parts follow the trajectory of the hook, orient themselves and then eventually are delivered through the delivery chute, tangentially to the plate. The factors influencing the feeder’s performance include the speed of rotation of the disc, the population of the parts in the hopper and the size of parts to be fed. A series of experiments is performed on the three process parameters to investigate their effect on the feed rate. To study the interaction among the factors a full 23 factorial experiment approach has been adopted using the two basic principles of experimental design-replication and randomization. The process model was formulated based on Analysis of variance (ANOVA) using Minitab® statistical package. The outcome is represented graphically and in the form of empirical model which defines the performance characteristics of the Stationary Hook Hopper Feeder.

scholarly journals Use of chemometric techniques to design a microbiological method for sulfonamide detection in milk

2013 ◽  
Vol 31 (No. 6) ◽  
pp. 627-632 ◽  
Author(s):  
O.G. Nagel ◽  
M.P. Molina ◽  
R.L. Althaus
Keyword(s):  
Experimental Design ◽  
Logistic Model ◽  
Logistic Regression Model ◽  
Culture Medium ◽  
Spore Concentration ◽  
Microbiological Method ◽  
Burman Design ◽  
Detection Capabilities ◽  
Sulfonamide Residues ◽  
Plackett Burman Design

We proposed an experimental design of a microbial bioassay of dichotomous response (positive or negative) using Bacillus subtilis BGA for the detection of sulfonamide residues. In the first stage, the bioassay response time was reduced to 6 h by increasing the spore concentration of B. subtilis. Then, the effects of spore, indicator, trimethoprim (TMP) concentration, and volume of the culture medium were examined with a Plackett Burman design (2<sup>4-1</sup>). Finally, the effect of TMP concentration on the method detection capabilities and specificity was analysed using a logistic model with interaction. The detection capabilities of sulfonamides in milk are close to the MRLs when using 500 mg/l of TMP in the culture medium of the bioassay. It is concluded that the experimental design techniques and a logistic regression model can be used to design successfully a dichotomous response bioassay.

Evaluation of Resistance Spot Welding Conditions Using Experimental Design

2012 ◽  
Vol 1481 ◽  
pp. 97-102
Author(s):  
D.Y. Medina ◽  
R. Bermejo ◽  
R.T. Hernandez ◽  
I. Hernandez ◽  
S. Orozco
Keyword(s):  
Experimental Design ◽  
Statistical Model ◽  
Factorial Design ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Breaking Strength ◽  
Evaluation Process ◽  
Resistance Welding ◽  
Post Induction ◽  
Welding Steel

ABSTRACTThe breaking strength that can withstand solder is known as resistance welding, low resistance welding will cause a failure of the weld. This study optimized the effect of the main variables in a welding steel proceess on the mechanical propierties of the steel like the resistance welding. The main variables studied were electrode, machine, post induction, and dotted pressure. The factors that have the most influence in the resistance welding are the post induction, and the combination of post induction and the raw material.The statistical model used for the evaluation process was an analysis of variance (ANOVA) in a full crossing factorial design 2k with a second order of interaction.

scholarly journals Optimization of Bifonazole-Loaded Nisomal Formulation Using Plackett-Burman Design and 2 Factorial Design

2016 ◽  
Vol 3 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Harshal Ashok Pawar ◽  
Vibhavari Bhaskar Attarde ◽  
Gide Parag Subhash
Keyword(s):  
Factorial Design ◽  
Burman Design ◽  
Plackett Burman Design

scholarly journals The Factorial Design with the type of Plackett-Burman to Determine the Optimization in the Brown Rice Production Process

2021 ◽  
Vol 9 (7) ◽  
pp. 859-864
Keyword(s):  
Production Process ◽  
Factorial Design ◽  
Analysis Of Variance ◽  
Confidence Level ◽  
Process Model ◽  
Brown Rice ◽  
Controlling Factors ◽  
Factorial Experiment ◽  
Broken Rice ◽  
Two Factors

This research aims to improve the paddy husking process by experimenting with Hom Nin rice. By designing a factorial experiment, placket-Berman type, to determine the optimum value in the husking process to obtain the lowest and best percentage of broken rice in the husking process. By controlling factors two variables are the spindle of speed,and the clearance of rubber forthe two rubbers.The process model was formulated based on analysis of variance (ANOVA) and regression of coefficient.The results showed that both variables were pvalue is greater than alpha value (0.278> 0.05). The percentage of broken rice was at 8.76 at the confidence level 95 percent significance between the two factors That are, the spindleof speedis equal to 1,420 rpm and the clearance rubber between the two rubbers are equal to 1 millimeters.

Assessment of liquid chromatographic method robustness by use of Plackett-Burman design

2010 ◽  
Vol 22 (2) ◽  
pp. 281-296 ◽  
Author(s):  
M. Mašković ◽  
B. Jančić-Stojanović ◽  
A. Malenović ◽  
D. Ivanović ◽  
M. Medenica
Keyword(s):  
Chromatographic Method ◽  
Liquid Chromatographic Method ◽  
Burman Design ◽  
Liquid Chromatographic ◽  
Plackett Burman Design

Optimization of PES Nanocomposite Membrane Preparation Using Statistical Analysis and Experimental Design

2019 ◽  
Author(s):  
Yasin Orooji ◽  
Fatemeh Noorisafa ◽  
Nahid Imami ◽  
Amir R. Chaharmahali
Keyword(s):  
Statistical Analysis ◽  
Experimental Design ◽  
Factorial Design ◽  
Fractional Factorial Design ◽  
Fractional Factorial ◽  
Nanocomposite Membrane ◽  
Membrane Preparation ◽  
Membrane Fabrication

<p>Using experimental design and statistical analysis (½ Fractional Factorial Design), this study investigates the effect of different parameters in the membrane fabrication on the performance of nanocomposite PES/TiO<sub>2</sub> membrane. </p>

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