A contemporary approach to the MSE paradigm powered by Artificial Intelligence from a review focused on Polymer Matrix Composites

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Gomez, C.
Guardia, A.
Mantari, J. L.
Coronado, A. M.
Reddy, J. N.
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Taylor & Francis INC
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Artificial Intelligence (AI) is a broad discipline that uses powerful algorithms to emulate important aspects of human intelligence. Provided by the Industry 4.0 revolution, AI is increasingly applied in different fields from research to production. One of these fields is Materials Science and Engineering (MSE) which studies the relationships between processing, structure, properties, and performance of materials. The application of AI to MSE has triggered the invention of new materials to satisfy the demanding requirements in myriad sectors through the years. In this context, the MSE paradigm emerged as a framework to define these relationships supported by the available technologies at the corresponding time. This is how Polymer Matrix Composites (PMC) were synthesized. During the last years, they have turned from a futuristic solution to a necessity due to the wide range of advantages they offer concerning other conventional materials. The present work presents a modified approach to the MSE paradigm with the application of AI algorithms. An overview of the research advances from 2003 to 2019 in each fundamental link of the proposed MSE paradigm for PMC is exhibited in an organized fashion. This article must serve engineers and scientists working at the intersection of mechanical engineering, materials science and computer science to identify trendy topics in these fields. It aims to represent a starting point for developing innovative methods and proposing new research topics in the framework of the MSE paradigm powered by AI for PMC.
This paper was written in the context of the project: Desarrollo de un software para predecir el desempe no structural de product terminado en el proceso de fabricacion por manufactura aditiva de materiales compuestos founded by Cienciactiva, CONCYTEC, under the contract number No 112-2018-FONDECYT-BM-IADT-MU. The authors of this manuscript appreciate the financial support from the Peruvian Government.
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polymer matrix composites (PMC), Industry 4, 0, Materials Science and Engineering paradigm (MSE paradigm), artificial intelligence (AI)