Shot peening optimization with complex decision-making tool: Multi criteria decision-making

Abstract

Controlled shot peening process is performed on two independent ways: (1) Pre-shot peening of Almen strips to determine the desired intensity (2) Shot peening of the real sample with the Almen intensity obtained. Shot peening of Almen strips in the first step takes more time. This is because, the application of input parameters, also measuring arc height and controlling the Almen intensity stages have to be completed consecutively. The results influence the real sample characteristics directly. Still, the arc height measurements and the input parameters adjustment depend on technicians’ expertness. So, numerical approaches by conducting finite element modelling (FEM), ANN (artificial neural network) and RSM (response surface methodology) takes more attention growingly. For this purpose, another numerical approach, multi-criteria decision making (MCDM) methods have been developed and verified among their counterparts and also by comparing the experimental results, surface roughness and surface hardness in this study. The results show that the MCDM methods are consistent within themselves and in the context of input parameters (air pressure, shot size, peening duration) and output parameters (surface hardness, surface roughness). The Topsis approach presents consistent results with compared to both the other approaches and the experimental conditions.