From reactive to predictive rail operations with cognitive digital twins

Railways have remained one of the most reliable and safest means of transportation for decades. However, modern rail systems worldwide face growing challenges such as aging infrastructure, operational risks, capacity constraints, and rising sustainability expectations.

How can modern technologies like cognitive digital twins and the Internet of Things (IoT) help rail operators stay agile and responsive to different risks? What is the concept behind railway systems’ digital twins? Our blog post explores all this.

Rail sector trends and challenges

Rail systems are becoming increasingly complex, covering new areas, and connecting people and whole countries. This comes with a growing infrastructure and asset demands that must first be planned and then efficiently maintained.

With global warming remaining a significant issue, reducing carbon footprints and optimizing energy consumption are now essential priorities for rail operators worldwide.

All in all, rail transport operators must ensure effective rail yard management and address the following set of challenges:

• Monitoring and control: Look after rail assets and infrastructure conditions and overcome a lack of data-driven decision-making.
• Safety risks: Address operational risks, bridging the gap between process planning and real effectiveness.
• Maintenance: Implement predictive strategies to limit downtime, identify anomalies, and extend asset lifespan.
• Network optimization: Enhance network efficiency and maximize track capacity and fleet utilization.
• Environmental regulations: Meet safety, security, and green standards.
• Scalability: Enable rail systems’ growth to accommodate greater capacity and varied train fleets.

Digital twins in the rail industry: What are they?

Rail operators should embrace modern technologies to stay ahead of the competition. One such technology is digital twins, which are gaining popularity across industries.

A digital twin is a connected virtual replica of physical business operations or assets. Such a system mirrors existing infrastructure in real time. It ingests IoT sensor data and other digital signals to simulate physical behavior, monitor performance, and support predictive analytics.

Digital twins are transforming rail yard management by providing a dynamic, connected representation of physical assets, infrastructure, and operations across the industry. These connected models replicate the behavior, conditions, and performance of everything from rolling stock and signaling systems to stations, tracks, and passenger flows.

By continuously integrating data from sensors, IoT devices, and operational systems, digital twins offer rail operators real-time visibility and predictive insights. This enables them to monitor asset health, simulate scenarios, and proactively manage failures for more efficient rail yard management.

A cognitive digital twin: the HCLTech story

The concept of digital twins is clear now, but what is a cognitive digital twin? Let’s break it down with a real-world success story from HCLTech. This consulting company is leading a transformative shift through the power of cognitive digital twins and has built one for a major rail operator.

The concept of a cognitive digital twin extends beyond traditional models by embedding artificial intelligence, machine learning, and advanced simulation. In the context of rail yard management, this means creating a virtual environment that mirrors physical assets and processes, learns from them, adapts to changing conditions, and recommends smart actions.

HCLTech’s cognitive digital twin collected data from IoT sensors, asset management systems, geospatial platforms, and cloud-based services and fed it into a simulation powered by AnyLogic.

HCLTech’s digital twin solution for rail yard management provided oversight of employee shifts, departmental activities, service requests, and resource allocation. It enabled operators to track active roles, monitor service status, and visualize real-time spending.

With HCLTech’s rail twin for asset maintenance, engineers could identify track wear, monitor switch toggles, and schedule repair activities, all within a realistic, immersive simulation.

HCLTech presented this project of a cognitive digital twin at the AnyLogic Conference 2024. Watch the video below for a closer look at how HCLTech built this model and integrated simulation, IoT, and predictive analytics.

The benefits of embracing cognitive digital twins

Cognitive digital twins bring real business value, and the HCLTech story proved that. By enabling real-time monitoring, predictive analytics, and data-driven decisions, a leading rail operator achieved:

• 25–30% boost in rail asset performance.
• 20–30% reduction in maintenance costs.
• 10–30% improvement in planning efficacy.

The solution’s modular architecture enabled quick customization across rail yard management use cases. These include health monitoring of switches and signals, real-time occupancy tracking, logistics, and traffic disruption management.

Cognitive digital twins do not just support existing rail operations. They enable a shift toward a proactive and customer-centric future in transportation.