Investigating Deformation and Stress Distribution in Ball Bearings Using Finite Element Analysis

This research focuses on the deformation and stress responses of five materials—Structural Steel, Chrome Steel AISI 5200, Aluminum Alloy, Brass C3700, and Cast Iron EN GJL100—under varying pressure conditions utilizing Finite Element Analysis (FEA). The study aims to provide a comprehensive understanding of how these materials behave when subjected to different levels of pressure, specifically at 50, 60, 70, 80, and 90 MPa. The results indicate that Brass C3700 consistently exhibits the highest tensile stress resistance, making it highly suitable for applications that demand superior strength and durability. Aluminum Alloy also shows significant tensile strength, performing well under increased loads, which highlights its potential for high-stress applications. Structural Steel and Chrome Steel AISI 5200 demonstrate similar performance trends, maintaining moderate stress levels and exhibiting predictable behavior under varying pressure conditions. These materials offer reliable performance and are suitable for applications where moderate stress resistance is sufficient. Cast Iron EN GJL100, while showing moderate tensile stress resistance, aligns closely with the steel materials and provides a balance of strength and predictability, making it a viable option for various industrial applications. The use of computational simulation tools, such as FEA, proves invaluable in this research. These tools enable the simulation and investigation of deformation and stress responses under various load conditions, providing detailed insights into material behavior before actual implementation. This capability allows engineers to make informed decisions regarding material selection, optimizing material usage and enhancing the reliability and safety of engineering designs. The findings from this study offer valuable guidance for material selection in industrial applications, ensuring that materials are chosen based on their performance characteristics under operational conditions.