## 4 Digital Twin Modelling Methodology  
### Data Collection  
Data are produced from the tunneling survey sheets, geophysical surveys, borehole drilling and logging, in situ and laboratory testing, and geological surveys. They also include the operating parameters of the TBM, equipment electrical and mechanical status, and status of the TBM components. The type and format of the data differ in nature and size, including images, spreadsheets, and text documents. The TBM data are continuously generated. Furthermore, they include the geological data during the excavation. The data measured using sensors and other equipment are recorded and observed in the TBM cabin. The TBM continuously receives the data and stores them in a specific order and continuous number. The program for data acquisition automatically starts after each new start of the PC and loads all required program components into storage. Afterwards, it determines the instantaneous operating state of the machine. Termination of the program is controlled through the control cabin with the switch cabinets of the control panels. All the main controls of the TBM and components are connected using cables, tested, and started up; furthermore, a connection to the PLC of the TBM is established. In the switch cabinets, the programmable control system, data acquisition, as well as measurements and data cards are integrated. The programmable logic controller (PLC) is an S7 type, manufactured by Siemens. The control panels house all the necessary operating and display units installed. The operator panel desk is IP48-rated. A visual display shows all operational parameters of the TBM and its systems. Local control panels are located adjacent to moveable parts of the machine, and all are fitted with emergency stops and key switches where appropriate, for local isolation during maintenance. A Siemens S7 PLC is at the heart of the control system and is provided to control the main functions of the TBM; it is installed in the operator control desk with remote interface units installed in the distribution panels. The PLC system is interfaced with an industrial computer within the operator control desk. A graphical representation of data transmission from the TBM to the monitoring device is shown in Figure 4. A controller area network (CAN) bus uses a two-wire bus architecture to transmit and receive data messages between devices. It is a message-based protocol, which makes the CAN bus highly scalable and efficient in handling large amounts of data in real time. The software is protected from unauthorized access. The PLC system has a powered battery for power loss, a fail-safe system, interlocked circuits, and critical safety circuits hardwired separately to the PLC. It is necessary to investigate the effect of all the influential parameters and choose the key parameters important for a better AI-based predictive model of TBM performance. All influential parameters can be categorized into three related rock properties, machine characteristics, and tunnel geometry [12]. Based on the literature, compressive strength is the most influential parameter affecting TBM performance [53]. In another study, RMR, RQD, and UCS were considered the most influential parameters affecting TBM performance [16]. Similarly, an empirical TBM performance model has also been presented to predict PR using the Q and QTBM values [54]. Other researchers also have included the joint conditions, BTS, and weathering degree of the rock mass to predict TBM performance [16; 55]. Besides these rock-based parameters, thrust force (TF) is the most important machine parameter for predicting TBM performance [2; 12]. The maximum torque, maximum power, maximum revolutions per minute (RPM), and the function of thrust force are important parameters for TBM performance. Since the geometry parameters usually remain constant, these parameters are not considered in this study.