American Journal of Modeling and Optimization
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American Journal of Modeling and Optimization. 2015, 3(1), 1-6
DOI: 10.12691/ajmo-3-1-1
Open AccessArticle

Prediction Models by Response Surface Methodology for Turning Operation

Basim A. Khidhir1, , Waleed Al- Oqaiel2 and PshtwanMuhammed Kareem3

1Slemani Technical College, Iraq

2Ministry of Industry, Kingdom of Saudi Arabia

3Slemani technical Institute, Iraq

Pub. Date: January 26, 2015

Cite this paper:
Basim A. Khidhir, Waleed Al- Oqaiel and 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

Abstract

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.

Keywords:
response surface methodology machining parameters surface roughness AISI 1020 mild steel

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