Rail Systems Engineering Modelling by Georgios Ardavanis (PhD)

Innovation is the key to success as it will improve our competitiveness by providing leading-edge technologies. We have to make sure we are always one step ahead of others when it comes to technology and know-how especially in the areas of energy efficiency, productivity, asset utilization, improvements in infrastructure and train availability, travel experience for passengers, and, last but not least, climate and environmental friendliness.

In the last couple years, I'm focused in the applied research of Rail Systems Engineering Modeling (RSEM). RSEM can enable the Design, Build, Operation and Maintenance (DBOM) cycle of railways to become much more efficient by decreasing the cost during the defects and liability period and therefore increase the project’s Return of Investment (ROI), Return of Equity (ROE).

Rail Systems Engineering Model (RSEM) is a monocentric model that is made to: (a) Facilitate the systems engineer’s dilemma on complexity and synchronization; (b) Facilitate the rail systems understanding with regards to system design, construction and engineering project management; (c) Aid in decision making (e.g. “what if scenarios”); (d) Explain, control and predict events; and (e) Save substantial money and time by identifying omissions and defects during the analysis and design stages. The main characteristics of the RSEM is that is used to enhance the Rail Systems Engineering (RSE) organization capabilities during the design, construction and the Verification and Validation (V&V) stages. This means that RSEM involves all the RSE domains along with their requirements. Additionally, RSEM includes additional functions such as trade studies, program and engineering changes, quantitative risk analysis and management. In RSEM there are actually four primary RSE domains:
1. The RSE Requirements Domain.
2. The RSE Behavior Domain.
3. The RSE Architectural Domain.
4. The RSE V&V Domain.

The abovementioned domains must be inter-related. It is RSEM’s objective to keep all these relationships, of the various databases, inside the RSEM’s monocentric database. Thus, a single model will be able to integrate all these different types of information into a single underline repository. This single model can help the rail systems engineer to perform accurate Rail Systems Engineering Analytics (RSEA) based on digital analytics.

RSEA help systems engineering models to harness their data and use them to identify new opportunities. RSEA also include the Search Engine Optimization (SEO) where the keyword search is tracked, and that data is used for engineering purposes. RSEA is generally divided into Exploratory Data Analysis (EDA), where new features in the data might be discovered, and confirmatory Data Analysis (CDA), where existing hypotheses are proven true or false.