Abstract

In the aerospace industry, the milling of aluminum alloy parts is a machining process with the primary purpose of removing high volumes of material. Aluminum alloys are materials that have relatively good machinability, which helps the process because many of the components of the aircraft are of high dimensions. These parts have many pockets more or less deep, and the removal by cutting off about 90% of the initial volume of the workpiece is a matter of consideration. The manufacturing process is protracted and involves long semi-finishing and finishing operations, so it is recommended that any researcher who begins and finishes an experimental study should do it base on a specific experimental plan. Mathematical statistics techniques and methods are used, but also optimization methods that lead to a rational choice of process parameters, process input data and objective functions that need to be improved. This scientific paper presents applied research based on an extremely pertinent active experiment that has led to some practical solutions applied in the aerospace industry worldwide. The dedicated objective function on which the study conducted in this case was the mean arithmetic deviation of the surface profile. The independent variables were chosen by the concrete application of a dispersion analysis applied to the milling process, namely the cutting speed, the cutting depth and the feed per tooth. Interpretation of the results was performed by a graphical evaluation of the normality of the data distribution, by presenting the histogram responses as well as by the dispersion diagrams. It was used for a better correlation a 3D graphical analysis that followed the Ra variation of the mean arithmetic deviation of the machined surface profile under the influence of the cutting parameters and the independent variables respectively. The obtained conclusions led to the validation of the experimental model and the application of the research presented within an aerospace industry organization with important global valences.

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