Affiliation:
1. Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, 33100 Tampere, Finland
Abstract
The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and now finds applications across a wide range of disciplines. This multidisciplinary expansion has impressively demonstrated the potential of digital twin research. While the simulation aspect of a digital twin is often emphasized, the role of artificial intelligence (AI) and machine learning (ML) is severely understudied. For this reason, in this paper, we highlight the pivotal role of AI and ML for digital twin research. By recognizing that a digital twin is a component of a broader Digital Twin System (DTS), we can fully grasp the diverse applications of AI and ML. In this paper, we explore six AI techniques—(1) optimization (model creation), (2) optimization (model updating), (3) generative modeling, (4) data analytics, (5) predictive analytics and (6) decision making—and their potential to advance applications in health, climate science, and sustainability.
Subject
Industrial and Manufacturing Engineering
Reference56 articles.
1. Analyzing the scholarly literature of digital twin research: Trends, topics and structure;Tripathi;IEEE Access,2023
2. Glaessgen, E., and Stargel, D. (2012, January 23–26). The digital twin paradigm for future NASA and US Air Force vehicles. Proceedings of the 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, Honolulu, HI, USA.
3. Review of digital twin applications in manufacturing;Cimino;Comput. Ind.,2019
4. A digital twin of Earth for the green transition;Bauer;Nat. Clim. Chang.,2021
5. Using digital twins in viral infection;Laubenbacher;Science,2021
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