Quality of service
OPEX
CAPEX
Our client is a European rail network operator with responsibility for maintaining their existing network assets while concurrently investing in that network to meet the demands of future rail network users. They must constantly balance maintenance and other operating expenses (OPEX) on the present network against investment (CAPEX) in the future network, while maintaining service quality standards and remaining within budget constraints.
This rail network operator must produce a robust strategic asset investment plan that ensures that the operator will meet their KPIs while avoiding the impacts of hereto unforeseen cascading effects.
The client deployed a Prescriptive Simulation Twin, Cosmo Tech Asset, which they used to model and simulate their entire rail network. This digital twin not only included the physical rails and rolling stock that the operator maintains but also all of the associated infrastructure such as bridges, earthworks, electrical networks, signalling, and crossroads. This enabled the client to simulate under real conditions the dynamic behavior of their rail system and determine the optimal asset investment strategy to pursue.
By running simulations on our solution, the client was able to manage the trade-offs between operating expenditure and capital expenditure, and between cost, performance, and the risk of failure.
Cosmo Tech Asset allows for optimal decision making with all the silos of the company taken into account. Asset managers can visualize the cascading effects of their decision and unlock the hidden value in the rail network, helping them to deliver an asset investment planning strategy that balances OPEX, CAPEX, and risk.
Cosmo Tech’ Prescriptive Simulation Twin significantly accelerated the operators capacity to analyse different asset investment planning scenarios, and its capacity to test unlimited scenarios allowed for a greater range of investment planning alternatives to be assessed.
The rail network operator was able to choose the asset investment plan that was optimal in light of all of its constraints and which enabled it to achieve the KPIs for service quality, safety, and reliability that internal and external stakeholders demanded.
