Kalla, D. (2024, June), Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46522

\bibitem{asee_peer_46522}
  Kalla, D. (2024, June), \emph{Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  10.18260/1-2--46522

Devi Kalla.  "Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/46522 Internet.  07 Jan, 2025

\bibitem{asee_peer_46522}
  Devi Kalla.
  "Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/46522 Internet.  07 Jan, 2025

@INPROCEEDINGS{asee_peer_46522
author = "Devi Kalla"
title = "Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/46522}
number = {10.18260/1-2--46522}
}

TY  - CPAPER
AB  - The transformation of artificial intelligence (AI) and machine learning (ML) from computer science theory into real-world technologies is a primary driver of the fourth industrial revolution (Industry 4.0). Industry 4.0 has shifted manufacturing operations away from mechanical technologies and toward digitalization. Metal Additive manufacturing (MAM) as a highly digitalized manufacturing technology can apply the concept of the digital twin (DT) and AI, which promises highly automated and optimized part production. However, adoption of DT and AI requiring a wide framework of various technologies, it is not state of the art yet. This paper presents a comprehensive review of AI and DT enabled models in Metal Additive Manufacturing. This paper also identifies challenges and opportunities to not only further leverage emerging technologies, artificial intelligence (AI) and digital twin (DT) for metal additive manufacturing, but also influence of future development of DT and AI to better meet the needs of additive manufacturing. These advanced technologies have radically transformed advanced manufacturing and are essential to modern economic prosperity.
AU  - Devi Kalla
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Adoption of Digital Twin and Artificial Intelligence in Metal Additive Manufacturing: Current Status and Vision for Future
UR  - https://peer.asee.org/46522
DO  - 10.18260/1-2--46522
ER  -