Prediction of machining quality due to the initial residual stress redistribution of aerospace structural parts made of low-density aluminium alloy rolled plates

During the machining of thick, large and complex aluminium parts, the redistribution of initial residual stresses is the main reason for machining errors such as dimensional variations and the post-machining distortions. These errors can lead to the rejection of the parts or to additional conforming operations increasing production costs. It is therefore a requirement to predict potential geometrical and dimensional errors resulting from a given machining process plan and in taking into consideration the redistribution of the residual stresses. A specific finite element tool which allows to predict the behaviour of the workpiece during machining due to its changing geometry and to fixture-workpiece contacts has been developed. This numerical tool uses a material removal approach which enables to simulate the machining of parts with complex geometries. In order to deal with industrial problems this numerical tool has been developed for parallel computing, allowing the study of parts with large dimensions. In this paper, the approach developed to predict the machining quality is presented. First, the layer removal method used to determine the initial residual stress profiles of an AIRWAREⓇ 2050-T84 alloy rolled plate is introduced. Experimental results obtained are analysed and the same layer removal method is simulated to validate the residual stress profiles and to test the accuracy of the developed numerical tool. The machining of a part taken from this rolled plate is then performed (experimentally and numerically). The machining quality obtained is compared, showing a good agreement, thus validating the numerical tool and the developed approach. This study also demonstrates the importance of taking into account the mechanical behaviour of the workpiece due to the redistribution of the initial residual stresses during machining when defining a machining process plan.