## 4 Case Study  
Having provided a general overview of the method, we will now illustrate its practical application within a pharmaceutical plant. The line on which the DT will be developed is dedicated to packaging bottles containing drugs of biological origin, which can be processed in serialized and non-serialized ways. This flexibility is necessary due to the great heterogeneity of customers and destination countries of the drugs produced within the plant. This section of the paper will be structured following the steps described in the corresponding section of the methodology. These data were calculated utilizing the company's OEE collection system, obviating the necessity for implementing additional process monitoring systems. This is because the systems already employed were satisfactory for a comprehensive analysis and characterization of the process. The subsequent phase of the investigation entailed a detailed examination of the process history within the temporal scope delineated by the accessible data. Upon concluding the analysis, it was determined that 2023 would serve as the reference period, given the absence of significant alterations during this time frame. Once the preliminary operations had been completed, we proceeded with the data collection and analysis by examining the production line. It should be noted that the objective of the data collection was to gain insight into the dynamics, causes, and subsequent analysis of the calculation of the indicators that influence the line efficiency to outline their real production capacity. These data must be fully understood to gain each production line machine's specific and operational characteristics, including the extent of their interconnectivity. During these inspections, the characteristics of each machine were documented, including their operating parameters, nameplate capabilities, and any inherent limitations. However, this document will not include these details to respect the confidentiality of the company and the companies supplying the machinery. Subsequently, the bottleneck machine was successfully identified. The process is reproduced below in Figure 2 under the ASME notation guidelines to guarantee a transparent and intelligible representation of the digital model. Finally, the personnel necessary for the production line's optimal functioning and maximum operational performance were appointed. The introduction of personnel was contingent upon a meticulous examination of the roles and competencies indispensable for the productive operation of the line. The resulting digital model, created using the Siemens Tecnomatix Plant Simulation software, is illustrated below in Figure 3.  
Figure 3: Digital Twin. Figure 2: ASME representation process chart. The data implementation follows the instructions and protocols established by the software, with particular attention paid to the accuracy and consistency of the data. This process requires the accurate transposition of the real data into the virtual model, ensuring that all relevant variables and parameters are represented correctly and in detail. For the implementation of availability due to failures in the machine properties, and more specifically in the 'Failures' section, it is necessary to activate failures and add the calculated availability due to failures and the Mean Down Time (MDT) of the specific machine. This process must be repeated for each machine using the MDT and Mean Time Between Failures (MTBF) parameters calculated by the system to model the frequency of failures. The software will then be able to simulate failures during machine operations. The next step concerns the implementation of availability due to set-ups within the digital model. In this case, the availability due to set-ups was calculated for the entire line, as the available data do not allow for the availability due to set-ups of individual machines. To begin with, a thorough collection of set-up time data was carried out.