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

Area of Science:

• Materials Science
• Surface Engineering
• Manufacturing Processes

Background:

• Plasma-sprayed ceramic coatings are crucial for various industrial applications.
• Optimizing multiple performance characteristics simultaneously presents a significant challenge.
• Existing methods often struggle to balance competing surface property requirements.

Purpose of the Study:

• To enhance the multi-response quality of plasma-sprayed ceramic coatings.
• To apply grey theory and fuzzy models based on Taguchi design experiments for optimization.
• To critically evaluate the impact of control parameters on coating surface properties.

Main Methods:

• Utilized an L18 orthogonal array experiment with eight control factors.
• Applied grey-based fuzzy theory and Taguchi methods for multi-response optimization.
• Conducted analysis of variance (ANOVA) and Scanning Electron Microscopy (SEM) for surface analysis.

Main Results:

• Achieved significant reductions in surface roughness (15.96%), porosity (65.35%), hardness (34.60%), wear depth (34.04%), and coating thickness (32.01%).
• Demonstrated an overall 48.94% improvement in multi-properties compared to initial settings.
• Identified optimal process parameters for enhanced plasma-sprayed coating performance.

Conclusions:

• Taguchi methods combined with grey-based fuzzy theory effectively optimize plasma spraying processes.
• The study successfully enhanced the multi-response quality of ceramic coatings.
• Achieved desired improvements in critical coating surface properties through optimized parameters.