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Abstract
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Article Information:
Fuzzy and Regression Modelling of Hard Milling Process
A. Tamilarasan and K. Marimuthu
Corresponding Author: A. Tamilarasan
Submitted: October 19, 2013
Accepted: October 28, 2013
Published: April 25, 2014 |
Abstract:
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The present study highlights the application of box-behnken design coupled with fuzzy and regression modeling approach for making expert system in hard milling process to improve the process performance with systematic reduction of production cost. The important input fields of work piece hardness, nose radius, feed per tooth, radial depth of cut and axial depth cut were considered. The cutting forces, work surface temperature and sound pressure level were identified as key index of machining outputs. The results indicate that the fuzzy logic and regression modeling technique can be effectively used for the prediction of desired responses with less average error variation. Predicted results were verified by experiments and shown the good potential characteristics of the developed system for automated machining environment.
Key words: Box-behnken design, cutting forces, fuzzy logic, hard milling, sound, temperature,
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Cite this Reference:
A. Tamilarasan and K. Marimuthu, . Fuzzy and Regression Modelling of Hard Milling Process. Research Journal of Applied Sciences, Engineering and Technology, (16): 3380-3386.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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