Abstract

This research paper explores the opportunities and challenges associated with the use of machine learning and artificial intelligence in advanced materials processing. With the exponential growth of data, advanced analytical techniques and powerful computational tools, machine learning and artificial intelligence can be leveraged to develop novel materials with tailored properties, enhance process optimization, and improve manufacturing efficiencies. However, the integration of these technologies into materials processing systems is not without challenges, including data acquisition and pre-processing, algorithm selection and optimization, and the interpretation of results. This paper provides an overview of the state-of-the-art in machine learning and artificial intelligence for advanced materials processing, highlighting case studies and examples of successful applications, and identifying potential future research directions. The goal of this research is to provide insights and recommendations to accelerate the adoption of these technologies and their impact on the development of advanced materials.

Details

Title
Machine Learning and Artificial Intelligence for Advanced Materials Processing: A review on opportunities and challenges
Author
Srivastava, Shashank; Kumar, Indradeep; Kumar, Manish; Shakier, Hussein Ghafel; Swathi, B; Chahuan, Neeraj
Section
Materials Science
Publication year
2024
Publication date
2024
Publisher
EDP Sciences
ISSN
25550403
e-ISSN
22671242
Source type
Conference Paper
Language of publication
English
ProQuest document ID
3180954891
Copyright
© 2024. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.