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http://dx.doi.org/10.7735/ksmte.2017.26.3.278

Optimization of Classifier Operation Conditions Using Taguchi Method and Multiphase Flow Analysis  

Jin, Byeong-Ju (Department of Machanical Engineering, Mokpo National University)
Park, Min-Ho (Department of Machanical Engineering, Mokpo National University)
Yoon, Tae-Jong (Department of Machanical Engineering, Mokpo National University)
Kim, Young-Joo (Convergence Agricultural Machinery R&D Group, KITECH)
Kang, Bong-Young (Carbon&LightMaterials Application R&D Group, KITECH)
Shim, Ji-Yeon (Carbon&LightMaterials Application R&D Group, KITECH)
Kim, Ill-Soo (Department of Machanical Engineering, Mokpo National University)
Publication Information
Journal of the Korean Society of Manufacturing Technology Engineers / v.26, no.3, 2017 , pp. 278-284 More about this Journal
Abstract
Generally, classifiers have been used as machines to crush raw materials and classify suitable particle sizes in all industrial fields, such as food, chemical, and mineral. However, the technique for classifying micron-sized particles between 5 and $20{\mu}m$ is inferior. In particular, numerous experiments and considerable experiences are required to predict the particle size, because the classifier particle size is determined according to the internal flow. However, it is quite difficult to set the driving conditions so that the desired particle size can be classified only by experience and experimentation. Therefore, this study proposes a method of predicting the average particle size by employing multiphase flow analysis and the Taguchi method; this method is subsequently verified.
Keywords
Multiphase analysis; Classifier; Taguchi method; CFD analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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