Experimental Investigation of Surface Roughness of Cutting Parameters in T6 Aluminum Alloy Milling Process
In this study, optimum machining conditions were determined by investigating the surface roughness of the 7075-T6 aluminum alloy milling, depending on the spindle speed (rpm), feed per tooth (Fz-mm/tooth) and the cooling type parameters. Taguchi experiment design method was used to save time and cost. Experiments were based on the Taguchi L16 orthogonal array and signal/noise (S/N) ratios were used in the evaluation of the test results. Optimum surface roughness values were determined with Taguchi optimization. In addition, variance analysis and regression analysis were performed. Confirmation tests were conducted to verify the work. As a result of the confirmation tests, it was found that the surface roughness optimization in the milling of the 7075-T6 aluminium alloy was successfully applied.
A New NASA Handbook presents recommended procedures for the preliminary and final design of equipment items exposed to various dynamic loads, including random vibration excitations.1 For the final design when the geometric details of the equipment items have been largely determined, finite element method (FEM) and statistical energy analysis (SEA) procedures can be employed to predict the maximum stresses in equipment items due to random vibration excitations at their mounting points. In the preliminary design phase, however, more approximate prediction techniques are often needed, as summarized in the Handbook. The purpose of this paper is to detail the rationale behind these preliminary procedures. Included are simple techniques to predict a maximum instantaneous stress during a short duration vibration environment and fatigue damage during a long-duration vibration environment, based only upon estimates for the frequency and damping ratio of the first significant resonance of the equipment.