APPLICATION OF FUZZY LOGIC AND REGRESSION ANALYSIS FOR MODELING SURFACE ROUGHNESS IN FACE MILLING
Niket Vishnu Malvade1 and Dr. Raju. S. Pawade2
1Research Scholar, Department of Mechanical Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India
Assistant Professor, Karmaveer Bhaurao Patil College of Engineering, Satara, Maharashtra ,India.
2Associate Professor, Department of Mechanical Engineering, Dr. Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India,
Corresponding Author : niket2383@gmail.com
Abstract: Examining how machining settings affect surface finish in face milling is the goal of this study. This study describes an innovative use of artificial intelligence to the simulation of surface roughness. The purpose of this work is to develop empirical models using fuzzy logic and regression analysis. The predicted surface roughness values of these models are then contrasted. The results showed that the suggested technique may significantly increase the accuracy of the product performance. The outcomes demonstrate the effectiveness of using fuzzy logic modelling to accurately estimate surface roughness in dry machining.
Key words: Face milling, Regression analysis, Fuzzy logic.