# Digitalization and Dynamic Criticality Analysis for Railway Asset Management
## 4 Case Study
### Scenario and Application
The data collection process started by obtaining information from various sources, such as maintenance records, asset inventories, and sensors installed on the railway infrastructure. These data were transformed and standardized to ensure their consistency and usefulness, converting them into standard formats that the asset management system could use. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Step** & **Description** & **Source** & **Process** \\ \hline  & Import Tables: The information on the maintainable assets shall & & \\  & be provided in spreadsheets. The information necessary to & & \\  & calculate the criticality will be extracted from these tables. An & Spreadsheets & Extraction of data from various tables. \\  & outline of the relationships between the tables and the final & & Creation of the master table structure. \\  & structure of the master table is presented. & & \\  & Initial Master Table Load: Import existing data into the inventory & & \\  & table to determine which assets are maintainable. Generate a new & Inventory System & Generation of a relationship table to identify the maintainable assets in the \\  & relationship table to identify the maintainable assets. & & \\  & Relationship Table: Specialties generate tables to provide & Inventory system, & Creation of the relationship table for \\  & information on maintainable assets and their selected level & & specialties, obtaining information on \\  & of intervention. & & \\  & Database queries: Execute database queries using SQL to & & \\  & integrate the system’s base tables, such as inventory, attribute & & \\  & source, and relationship tables. This execution will allow the final & & \\  & extraction of assets, asset classes, failure frequency, and attributes. & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Detailed Steps for the Creation and Population of the Master Board. Similarly, data capture would be carried out for the rest of the characteristics, such as:  
* Type of substation
* Slope height and distance
* Maximum altitude (altitude)
* Type of high-voltage line
* If the maintainable asset is located in a tunnel
* If the maintainable asset is on a curve
* If the maintainable asset is located in an environmentally protected area
* If the maintainable asset is at an upper step
* Unavailability time (UT) and failure frequency (FF) for each station or route
* Average hourly traffic  
Data collection was a comprehensive process that involved obtaining information from multiple sources, transforming it into standard formats, and integrating real-time data for a more dynamic and accurate analysis of railway assets' criticality. Once the data were collected and linked, customized business rules were implemented for each type of asset in railway systems. An example of the rules applied is shown in Figure 3, where four levels of severity are defined: low, half, high, and inadmissible, specifically for one of the safety factors. In this case, the severity is determined based on the value of multiple attributes of the assets, such as  
* Class: Classification of the asset according to its function or criticality in the railway network. * Type_Via: The type of track where the asset is located, which can influence criticality and the risk of failure. * Track Device: Track-installed devices that can modify the behavior of the asset or influence its probability of failure. * Severity levels:
* The figure classifies the different conditions of the assets according to their criticality, using a severity scale. This multi-tiered approach allows maintenance or mitigation actions to be prioritized based on the associated risk. * A low level of severity implies that the asset presents a low security risk, while an inadmissible level would indicate a high risk that needs to be addressed urgently. * Attributes that influence severity:
* Class: This attribute classifies the asset according to its operational importance. High-class assets can have a greater impact on the operation if they fail.