Implementation of Artificial Intelligence for Predicting the Properties of Metallic Materials

Abstract

Artificial intelligence (AI) is transforming the field of materials science by providing advanced tools for predicting the properties of metallic materials, which are crucial for various industrial applications. The relevance of this topic stems from the increasing demand for effective and accurate methods for optimizing material characteristics and design, driven by the need for high-performance materials in industries such as aerospace, automotive, and manufacturing. Traditional approaches to predicting material properties often involve extensive experimental testing and computational modeling, which can be time-consuming and costly. In contrast, AI methods, particularly machine learning algorithms, enhance prediction accuracy and reduce development time by leveraging large datasets and uncovering complex patterns that may be invisible through traditional methods. The purpose of the article is to analyse the use of artificial intelligence, in particular machine learning methods, to predict the properties of metal materials. The article focuses on the integration of machine learning models with existing experimental and computer methods to improve the accuracy and efficiency of predictions. This paper explores the application of AI for predicting the properties of metallic materials with a focus on integrating machine learning models and data-driven methodologies. The research findings indicate significant progress in prediction accuracy and efficiency, demonstrating how AI can effectively model complex relationships between material composition, processing conditions, and resulting properties. The conclusions drawn from these studies highlight the transformative impact of AI on materials science. AI-based methods not only simplify the prediction process but also enable more precise and customized material development, ultimately leading to enhanced performance and innovation. The integration of AI into this field represents a significant advancement over traditional approaches, opening up broad prospects for future research and development. By continuing to refine AI models and expand their applications, researchers and engineers can further unlock the potential of metallic materials, driving progress across various industrial sectors and applications.