Digital Twins: A Comprehensive Study on Models, Platforms, Applications and Challenges

Technological innovation has created "digital twins," which can replicate and synchronize digital and physical things in (almost) real-time, assess situations from multiple perspectives, and optimize physical objects by predicting how they will behave in the future based on these analyses. This study delves deeply into Digital Twin technology, covering its origins as a game-changing link between the real and the virtual. It explores diverse models, dissecting their functionalities and predictive capacities. Through a comparative lens, it evaluates prominent platforms Oracle Digital Twin, ANSYS Twin Builder, and Siemens Digital Twin - examining their features and adaptability across industries. Extensive applications across Manufacturing, Energy, Automotive, and Logistics underscore the technology's optimization potential and operational enhancements. Lastly, the study discusses challenges and future perspectives for digital twin technology, offering insight into potential breakthroughs and areas of exploration in this rapidly evolving sector.