Modelling and optimisation of laser shock peening using an integrated simulated annealing-based method

Abstract

Laser shock peening is an innovative surface treatment technique, which has been successfully applied to improve fatigue performance of metallic components. Laser shock peening improves the surface morphology and microstructure of the material. In this paper, three Nd3+:YAG laser process parameters (voltage, focus position and pulse duration) are varied in an experiment, in order to determine the optimal process parameters that could simultaneously meet the specifications for seven correlated responses of processed Nimonic 263 sheets. The modelling and optimisation of a process were performed using the advanced, problem-independent method. First, responses are expressed using Taguchi’s quality loss function, followed by the application of multivariate statistical methods to uncorrelate and synthesise them into a single performance measure. Then, artificial neural networks are used to build the process model, and simulated annealing was utilised to find the optimal process parameters setting in a global continual space of solutions. Effectiveness of the proposed method in the development of a robust laser shock peening was proved in comparison to several commonly used approaches from the literature, resulting in the highest process performance measure, the most favourable response values and the corresponding process parameters optimum. Besides the improved surface characteristics, the optimised laser shock peening (LSP) showed an improvement in terms of microhardness and formation of favourable microstructural transformations.