Experimental measurement and optimization of tensile residual stress in turning process of Inconel718 superalloy

Generated residual stress in the machining processes is one of the most important factors which affects significantly service quality and component life. Inconel718 superalloy is one of the hard materials utilized widely in the aerospace industries. State of surface residual stress is a critical problem in the finish machining of Inconel718. Therefore, the aim of the present study is to estimate and optimize the effect of machining parameters including cutting speed, depth of cut and feed rate on induced tensile residual stress in the finish/ semi-finish turning process of Inconel718. Machining residual stresses were measured by X-ray Diffraction (XRD) method. Then, the results were introduced to the intelligent systems (including Artificial Neural Network (ANN) and Genetic Algorithm (GA)) to estimate residual stress at the various machining parameters and optimize the process. Finally, it was shown that, implemented efficient intelligent techniques in this paper are remarkably appropriate for machining of Inconel718. (C) 2014 Elsevier Ltd. All rights reserved.