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September 23, 2025Open Access

Multi Criteria Optimization of Al/Al2O3 Functionally Graded Composite Fabricated Using Grey Relational Analysis

Key Points

Optimal wear resistance achieved at a 30% Al/Al2O3 ratio, demonstrating significant improvements in performance.
Key metrics such as microstructure and hardness were extensively analyzed to enhance tribological performance.
Grey Relational Analysis effectively optimized multiple criteria influencing the durability of the FGCM.
The integration of powder metallurgy and GRA highlights potential applications in automotive and aerospace sectors.

Abstract

A six-layered Al/Al2O3 functionally graded composite material (FGCM) was successfully fabricated via powder metallurgy (PM), with each layer approximately 1.5 mm. thick. The influence of varying Al2O3 volume fractions on the microstructure, hardness and tribological properties (wear rate, specific wear rate, relative wear resistance and coefficient of friction) was systematically evaluated. Grey Relational Analysis (GRA)was effectively utilized for multi-criteria optimization, revealing that, relative wear resistance significantly influences the wear stability of the FGCM. Optimal performance was achieved at an intermediate Al/ Al2O3 fraction (e.g., 30%), resulting in notably enhanced wear resistance. The study demonstrates the efficacy of integrating PM fabrication and GRA optimization in producing FGCMs suitable for demanding applications in automotive and aerospace industries.

Multi Criteria Optimization of Al/Al2O3 Functionally Graded Composite Fabricated Using Grey Relational Analysis

Key Points

Abstract

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