Print ISSN: 1681-6900

Online ISSN: 2412-0758

Author : Fadhel Ibrheem, Abbas

Prediction of Surface Roughness in End-Milling with Multiple Regression Model

Saad Kareem Shather; Abbas Fadhel Ibrheem

Engineering and Technology Journal, 2008, Volume 26, Issue 3, Pages 326-337

In this Paper, we propose statistical package for social sciences (SPSS), to predict
surface roughness. Two independent data sets were obtained on the basis of
measurement: training data set and testing data set. Spindle speed, feed rate, and
depth of cut are used as independent input variables (parameters) while surface
roughness as dependent output variable. The multiple regression model by using
(SPSS) could predict the surface roughness (Ra) with average percentage deviation
of 7.8%, or 92.2%, accuracy from training data, and from testing data set that was
not included in the multiple regression analysis with average percentage deviation
of 11.95%, or accuracy of 88%, for 4-Flute end mill.