Force evaluation and machining parameter optimization in milling of aluminium burr composite based on response surface method

Abstract

ABSTRACT A significant measure for improving surface quality and workpiece machining efficiency is an optimisation of cutting parameters in millings. To increase machining capacities, the investigation of friction forces prediction plays a positive role. A rotatable centre composite experiment with abrasion of flat/slot in aluminium working part was developed to determine cutting forces to enhance cutting parameter, feed per tooth (ft), axial cutting depth (ad), speed of spindle (n), and length of tool (lt) based on methods of reaction of the second-order surface. To determine the regression model referring to cutting parameters, the least-squares procedure was used during the experimental results. At the same time, a friction prediction model has been developed and the parameters are calculated to eventually enhance the experimental values. ANOVA checked the estimated regression Eqn s and analysed the effect of machining process parameters on the morphology of force and topmost burrs. The results of the experiment show that ad and ft have an important milling force and width of top burrs in a certain range of cutting parameters. Optimised cutting parameters are: n is 1000 r per minute; ap is 5 μm, and l is 15.2 mm, ft is 3 μm/z according to optimum response value.