# Digital Twin for Human-Robot Collaboration in Manufacturing: Review and Outlook
## 3 Review of DT in HRC
### SBA vs. LBA Development  
The SBA focuses on the integration of various stakeholders in the product lifecycle to share and exchange information at each stage [95]. Therefore, the development of the SBA model is concurrent with each step of the product development from design to engineering to operations and service. The information gathered at each stage of the product development lifecycle can be reused when the product is revised or modified, thereby facilitating modularity [23]. Hence, SBA is more likely to be suitable for new products that are developed from scratch. The data from the initial stages of the design are stored and carried over to create an entire lifecycle of the product with DT [49]. The DT model is tested virtually using VC techniques to analyse the feasibility and cost before the actual start of the physical commissioning of the manufacturing processes [96]. The recent developments in the SBA enable the creation of a DT of existing machines, its reverse engineering for the \begin{table}
\begin{tabular}{c c} \hline \hline
**Layer Based DT** & **References** \\ \hline Three-Layers & [14; 19; 29; 53; 78; 79; 82; 81; 82; 83; 84; 85; 86; 87; 88; 89; 91] \\ \hline Five-Layers & [21; 83; 84; 92; 93; 94] \\ \hline Six or more Layers & [87; 90] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Different approaches within LBA using three are more layers. identification of faults as well as for improving the condition of the machine. Such reverse engineering techniques can be used in the development of DT of older industrial robots to increase efficiency, accuracy and repeatability. The development of such a DT for an existing robotic work cell by utilizing multi-level calibration is discussed in [97]. Although researchers follow both SBA and LBA methods, there is still a lack of clarity on the development of the DT [14]. The development of DT in both SBA and LBA requires information about physical entities, such as material properties, behavioral properties, geometry, sensor attributes, and data management tools. Therefore, an LBA-based approach is more suitable to model the DT of existing manufacturing shop floors. LBA can be used for the development of a digital twin for an existing system which is monitored in real-time and where there is access to the system parameters [98,99]. For example, the LBA of a shop floor can be implemented by utilizing point cloud data from sensors or IoT devices. Such devices can also capture human motion and utilize this data in the DT model [98,100]. The modularity of SBA is favourable for the development of individual products or components, which can be integrated later into a more extensive system such as a digital factory [101,102]. In a digital factory, the lifecycle of the entire system is monitored and tracked to provide additional value to the operation [103]. However, the development process of DT for individual products itself is intense and requires a lot of effort [104]. For instance, the effort to create the DT of a simple casting mould, which has mass and shape properties, shows the difficulty in creating the DT due to non-repeatability inherent with casting [105]. Similar problems may be faced while creating the DT of a manufacturing process. Manufacturing companies often outsource components or sub-assembly manufacturing to third-party suppliers. In such cases, the suppliers should be equipped with the tools necessary to create a DT for the component or sub-assembly being made. The data generated at this stage in the supplier has to be sent back to integrate with the product data. This can be one of the challenges for SBA. Figure 7 suggests a conceptual framework involving SBA and LBA for developing the DT of a collaborative robot. * For instance, in the development of a collaborative robotic arm, the information pertaining to each of the joints is gathered, including the motor performance data, efficiency, motor velocities, acceleration, torque, data from force/torque sensors, system information and diagnostic data.