Multi-Response Optimisation of Thermal Barrier Coating Performance Based on Grey-Based Fuzzy Approach

This study applies grey theory alongside fuzzy models based on Taguchi design experiments to optimise the performance of coatings for multiple responses, which enhances the quality of plasma-sprayed ceramic coatings. An L18 orthogonal array experiment with eight control factors was conducted, and the impact of the control parameters on the surface properties of the coatings was critically evaluated. In addition, an analysis of variance was conducted, and the surface structure of the coatings was examined using SEM. The multi-response characteristics of surface roughness, porosity, hardness, coating thickness and wear depth values during the spraying of ceramic coatings were studied comparatively through optimisation. In addition, a confirmation experiment was conducted. The experimental results show that surface roughness was reduced by 15.96%, porosity by 65.35%, hardness by 34.60%, wear depth by 34.04%, and coating thickness by 32.01% through optimal factors by plasma spraying coatings. Overall, a 48.94% improvement in multi-properties was observed when compared to the initial settings. Based on the above results, this study employed Taguchi methods to optimize the modeling of plasma spraying using grey-based fuzzy theory, thereby significantly enhancing the multi-response quality of plasma-sprayed coatings. The expected outcomes in terms of coating surface properties have also been achieved by these results.