Title:	Metaverse and AI Digital Twinning of 42SiCr Steel Alloys
Authors:	Khalaj, Omid Jamshidi, Mohammad Hassas, Parsa Hosseininezhad, Marziyeh Mašek, Bohuslav Štádler, Ctibor Svoboda, Jiří
Citation:	KHALAJ, O. JAMSHIDI, M. HASSAS, P. HOSSEININEZHAD, M. MAŠEK, B. ŠTÁDLER, C. SVOBODA, J. Metaverse and AI Digital Twinning of 42SiCr Steel Alloys. Mathematics, 2023, roč. 11, č. 1, s. nestránkováno. ISSN: 2227-7390
Issue Date:	2023
Publisher:	MDPI
Document type:	článek article
URI:	2-s2.0-85145906268 http://hdl.handle.net/11025/51905
ISSN:	2227-7390
Keywords in different language:	smart manufacturing;metaverse;digital twin;machine learning;cyber-physical systems;42SiCr steel;Q& P treatment;artificial intelligence
Abstract in different language:	Digital twins are the most important parts of Cyber-Physical Systems (CPSs), and play a crucial role in the realization of the Metaverse. Therefore, two important factors: flexibility and adaptability, need to be focused on digital twinning systems. From a virtual perspective, constructing buildings, structures, and mechanisms in the Metaverse requires digital materials and components. Hence, accurate and reliable digital models can guarantee the success of implementation, particularly when it comes to completing physical twins in the real world. Accordingly, four Machine Learning (ML) methods to make digital twins of an advanced 42SiCr alloy considering all of its uncertainties and non-linearities have been employed in this paper. These ML methods accelerate the digitalization of the proposed alloy and allow users to employ them for a wide range of similar metals. Based on this technique, producers can borrow these virtual materials and build their structures in the Metaverse. This way, if the properties of the materials were satisfactory, they might buy them and start manufacturing their products. As a case study, we focus on digital twining of an 42SiCr steel with some influential factors in its mechanical properties, making the nature of the alloy complex. Processes, including heat treatment, may restore the material’s deformability; however, Quenching and Partitioning (Q&P) not only eliminates the impact of cold forming but also provides advanced high-strength steel (AHSS) properties. In this research, the combined impacts of different Q&P treatments were investigated on the mechanical properties of 42SiCr steel alloy. The results have shown the acceptability and accuracy of the proposed ML methods in realizing the digital twins of this complex alloy.
Rights:	© The Author(s)
Appears in Collections:	Články / Articles (KKY) Články / Articles (RICE) Články / Articles (KEV) Články / Articles (KEI) OBD

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