ABSTRACT
Digital Twin (DT) technology gained prominence across various disciplines and engineering fields, peaking in the Gartner Hype Cycle for lnternet Technology (IT) in GNU Compiler Collection (GCC) in 2019 and ranking third in trending technologies for 2020 (IEEE Computer Society 2019). It has been applied across diverse domains:
Healthcare: DT is well-suited for healthcare 4.0, with applications in digital patients, pharmaceuticals, hospitals, and wearable technologies (Erol, Mendi, and Dogan 2020). Projects include the Human Brain Project, Brain Initiative, and Blue Brain Cell Atlas project (Erö et al. 2018), along with patient-based simulation models (Sim and Cure 2022), heart DTs (van Houten 2018), virtual humans, hospital department DTs (Siemens Healthineers 2018), and wireless devices for patient observation (Kellner 2015).
Smart cities and buildings: Cities have developed into smarter cities over the last years as a result of the widespread information and communications technology, utilizing data-driven models and Artificial Intelligence(AI) solutions (White et al. 2021). DTs of cities include Dublin’s Docklands (White et al. 2021), Virtual Singapore (Farsi et al. 2020), and Zurich (Shahat et al. 2021). Intelligent buildings use IoT and microsensors for control and efficiency, with projects like the West Cambridge site (Lu et al. 2020) and structural health monitoring (Shu et al. 2019). Building Information Modeling(BIM) has also been used for building DTs given the advantages offered by this tool for the development of digital models in the building field (Kaewunruen et al. 2018).
Transportation and logistics: DTs have been used in transportation and processing scheduling (Yan et al. 2021), digital shopfloor management systems (Brenner and Hummel 2017), and Automated Guided Vehicle(AGV) transportation (Martínez-Gutiérrez et al. 2021). Applications extend to elevators (Gonzalez et al. 2020), smart electric vehicles (Bhatti et al. 2021), pipeline DTs (Sleiti et al. 2022), traffic control systems (Wang et al. 2021; Saifutdinov et al. 2020), and Adaptive Traffic Control Systems (Dasgupta et al. 2021).
Energy 4.0: DTs provide disruptive advantages in energy production, transit, storage, and consumption (Karanjkar et al. 2018; Li et al. 2022). Examples include energy consumption optimization for robotic cells (Vatankhah Barenji et al. 2021), energy cyber-physical systems (Saad et al. 2020), energy storage systems for electric vehicles (Vandana et al. 2021), and smart electrical installations (Fathy et al. 2021; O'Dwyer et al. 2020).
Smart manufacturing: DT applications in industry can be categorized into four phases: design, production, service, and retirement (Liu et al. 2021). Applications range from iterative optimization (Xiang et al. 2019), virtual validation (Howard 2019), automated flow-shop production systems (Liu et al. 2019), autonomous manufacturing (Zhang et al. 2019), Manufacturing Execution Systems (Cimino et al. 2019), start-up phases acceleration (Zhu et al. 2021), optimization of time-based maintenance strategies (Savolainen and Urbani 2021), Remaining Useful Life (RUL) assessment (Werner et al. 2019), and applications in the retirement phase such as disassembly, reusage, disposal, retrospect, and upgrade (Falekas and Karlis 2021).
