Fuzzy Logic Modeling For Peripheral End Milling Process

Fuzzy logic has been deployed in this study to predict cutting speed and feed rate of peripheral end milling process at given hardness of material, radial depth of cut and cutter diameter. There were two types of fuzzy models had been designed and developed throughout in this study. The first developed fuzzy model (Model A) was two inputs with two outputs while the second developed model (Model B) was three inputs with two outputs. Hardness of material and radial depth of cut had been chosen as the inputs for the Model A. Cutter diameter then had been introduced as the third input besides material hardness and radial depth of cut for Model B. Two types of fuzzy model were designed to evaluate the effectiveness and efficiency of introducing cutter diameter as another input into the system. Both types of fuzzy model had been tested and validated with the recommended data obtained from Machining Data Handbook (MDH). The results showed a very good correlation between predicted data and the data from MDH. Model B had been chosen as the best fuzzy model to represent peripheral end milling process although Model A had performed better; 3.78% and 2.06% (Model A) compared to 3.81% and 2.27% (Model B) for cutting speed and feed percentage errors respectively. This is due to less development time and the ability to predict cutting speed and feed at any given cutting tool diameter.