A Cutting‐Edge Survey of Tribological Behavior Evaluation Using Artificial and Computational Intelligence Models
Senthil Kumaran Selvaraj, Aditya Raj, Mohit Dharnidharka, Utkarsh Chadha, Isha Sachdeva, Chinmay Kapruan, Velmurugan Paramasivam
Abstract
Any metal surface’s usefulness is essential in various applications such as machining and welding and aerospace and aerodynamic applications. There is a great deal of wear in metals, used widely in machines and appliances. The gradual loss of the upper metal layers in all metal parts is inevitable over the machine or component’s lifetime. Artificial intelligence implementations and computational models are being studied to evaluate different metals’ tribological behavior, as technological progress has been made in this field. Different neural networks were used for different metals. They are classified in this paper, together with a description of their benefits and inconveniences and an overview and use of the different types of wear. Artificial intelligence is a relatively new term that uses mechanical engineering. There is still no scientific progress to examine various metal wear cases and compare AI and computational models’ accuracy in wear behavior.