Integration of TiC-Reinforced Aluminum Matrix Composites with CNN-Based Systems for Automotive Steering Knuckle Applications
Year: 2025
Type: article
Abstract: This study delivers a 35% reduction in steering knuckle failures by an innovative integration between advanced materials and AI-enhanced quality control. We prove that 6061+10%Si+4%TiC aluminum matrix composites behave most optimally with 138 MPa fatigue strength (25% improvement), 86 GPa elastic modulus, and 9.2/10 rating overall while still retaining manufacturability. Our neural network built upon convolutional principles posts 87% defect detection accuracy-the best compared to classical systems (SVM: 75%; RF: 70%)-and it performs inference within 28 milliseconds, allowing for production-line deployment. The amalgamation sees warranty claims go down by 28%, while costs increase by less than 5%, thus setting a new paradigm in the world of safety-critical automotive components. This work is bridging materials science with Industry 4.0 by supplying a validated framework for lightweight and high-reliability automotive design.
DOI: 10.14419/7bjmmc83
Authors: Kishor Dagale, Pramod Kumar, Makarand Shirke
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4413165634