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Predictioin Of Surface Roughness In Turning By Multiple Regression Model | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 26, Issue 9, 2008, Pages 1055-1060 PDF (258.02 K) | ||
| DOI: 10.30684/etj.26.9.1 | ||
| Author | ||
| Abbas Fadhel Ibraheem | ||
| Abstract | ||
| In this research, we propose statistical package for social sciences (SPSS), to predict surface roughness in turning process. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Original length, diameter and selected length are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by multiple regression model. The multiple regression model by using (SPSS) could predict the surface roughness (Ra) with average percentage deviation of 4.6%, or 95.4%, accuracy from training data, and from testing data set that was not included in the multiple regression analysis with average percentage deviation of 7.9%, or accuracy of 92.1%. | ||
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