1Slemani Technical College, Iraq
2Ministry of Industry, Kingdom of Saudi Arabia
3Slemani technical Institute, Iraq
American Journal of Modeling and Optimization.
2015,
Vol. 3 No. 1, 1-6
DOI: 10.12691/ajmo-3-1-1
Copyright © 2015 Science and Education PublishingCite this paper: Basim A. Khidhir, Waleed Al- Oqaiel, PshtwanMuhammed Kareem. Prediction Models by Response Surface Methodology for Turning Operation.
American Journal of Modeling and Optimization. 2015; 3(1):1-6. doi: 10.12691/ajmo-3-1-1.
Correspondence to: Basim A. Khidhir, Slemani Technical College, Iraq. Email:
bak-time@hotmail.comAbstract
This study is intended to develop a predictive model for surface roughness and temperature in turning operation of AISI 1020 mild steel using cemented carbide in a dry condition using the Response Surface Method (RSM). The values of the selected cutting speed, feed rate, and depth of cut are based on the preliminary trial experiments by design of experiments. The analysis of variance for the predictive model of second order for both models shows that the feed rate is the most significant parameter which affects the surface roughness and temperature followed by cutting speed. The goal is to monitor one response by other instead of using different techniques. Both models are convenient for predicting of the main effects of the machining parameters and are economical for determining the influence of various parameters in a systematic manner.
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