Abstract—Turning is one of the most widely used metal cutting processes. The increasing importance of turning operation is gaining new dimensions in the present industrial age in which the growing competition calls for all the efforts to be directed towards the economical manufacture of machined parts as well as surface finish is one of the most critical quality measure in mechanical products. In present work, a non linear regression analysis is adopted to establish a prediction model for surface roughness which may help to optimize machining process. Once the process parameters viz., cutting speed, feed, depth of cut, Nose Radius are given, the surface roughness can be found out experimentally following which a comparative study are made to analyze the deviation in surface roughness values from prediction model. The work piece material is EN8 which is machined by carbide inserted tool. All the experimental works have been conducted on CNC lathe. The experiments are carried out by using design of experiment. Finally the contributions are summarized in tabular form and may be used as an indicative of quality measure of machined parts.

Index Terms—Design of experiment, Regression approach, Machining process optimization.

Cite: Soumik Dutta, Abhijit Saha, and Saikat Ranjan Maity, "Non Linear Regression Model of Surface Roughness," International Journal of Mechanical Engineering and Robotics Research, Vol. 2, No. 2, pp. 289-297, April 2013.