The Optimal Milling Condition of the Quartz Rice Polishing Cylinder Using Response Surface Methodology

被引:0
作者
Bangphan, Surapong [1 ]
Bangphan, Phiraphan [2 ]
Lee, Sukangkana [3 ]
Jomjunyong, Sermkiat [4 ]
Phanphet, Suwattananrwong [5 ]
机构
[1] Rajamangala Univ Technol, Ubon Ratchathani Univ, Dept Ind Engn, Lanna Chiangmai Campus 128,Mu Huaykeaw Rd, Chiangmai 50300, Thailand
[2] Rajamangala Univ Technol, Tech Educ, Chiang Mai 50300, Thailand
[3] Ubon Ratchathani Univ, Dept Ind Engn, Ubon Ratchathani 34190, Thailand
[4] Chiang Mai Univ, Fac Engn, Chiang Mai 50300, Thailand
[5] Rajabhat Univ, Fac Sci & Technol, Chiang Mai 50200, Thailand
来源
WORLD CONGRESS ON ENGINEERING 2009, VOLS I AND II | 2009年
关键词
Response surface methodology; Rice Polishing Cylinder; Abrasive; Design of Experiment;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The purpose of this research is to develop the small rice milling machine in order to support the agricultural communities in Chiang Mai province and Ubon Ratchathani province using design of experiment technique. The experiment was designed by Response Surface Methodology (RSM) based on Central Composite Design (CCD). Type of rice: Thai Hom Mali rice 105 was chosen as testing rice. The two major factors including revolution per minute (RPM) and clearance between rubber and polishing cylinder were studied their effect on the percentage of broken rice after milling. In addition, the inverter system is also implemented in order to control the operation of the small rice milling. The level of factor was determined to evaluate the factor's effect that optimized the yield and to verify the optimal conditions. Based on the statistical significance with a level of 0.05, the optimal conditions are as follows. The revolution per minute and clearance between rubber and rice polishing cylinder to yield 15.29 % broken rice were 1560 rpm and 1.71 mm, respectively. After milling, the percentages of broken rice were calculated and analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level alpha = 0.05, the values of Regression coefficient, R-(adj)(2) were 98.42 %.
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页码:743 / +
页数:2
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