Enterprise Asset Management

Can rail live up to expectations? Various regions and governments worldwide have unveiled large-scale plans to develop rail, the least emission-intensive mode of transport.

India, for example, recently announced that it had electrified 95 percent of its rail network (compared to 56 percent in the European Union) as part of its goal to achieve net zero emissions by 2030. The EU has set ambitious objectives of its own: doubling high-speed rail use by 2030 and doubling rail freight traffic by 2050.

Achieving these objectives is often viewed as a matter of adding more—more investments, more railways, more trains. However, with operating costs accounting for approximately 80 percent of the total cost of ownership (TCO) of rolling stock and railways, better maintenance will actually be the heart of the matter.

For large operators, maintenance consumes a budget comparable to the GDP of a small country. For instance, in 2018, France’s SNCF spent 2.7 billion euros on maintaining its rolling stock. In an era of rail liberalization, reducing these costs or increasing availability rates by even a few percentage points can have a significant impact. Three digital technologies are poised to help.

Centralizing Data and Maintenance Management in a Single Location

Optimizing maintenance and operations requires a strong foundation: an enterprise asset management platform that aggregates data from multiple sources, serves as a single source of truth, and enhances maintenance practices.

Such a platform can deliver critical results in several areas: 

-       It helps break down data silos between interconnected processes - for example, between parts inventory, warranty management, purchasing and budgeting, or between work schedules, work permits and management of contractors.

-       It centralizes multiple sources of data of different nature, including the Internet of Things. Sensors such as wheel impact load detectors (WILD) can provide a wealth of information and detect problems that range from damage to alignment to excessive temperature. They are a tremendous source of intelligence, particularly when they feed machine learning algorithms to make sense of the data they generate.

-       It enables companies go beyond traditional maintenance practices (corrective, scheduled and preventative maintenance) toward more efficient, data-driven strategies, including condition-based and predictive maintenance. For example, using HxGN EAM, a leading asset management platform, major rail operators have leveraged data and machine learning algorithms to predict asset failures and support real-time decision-making—an approach proven to reduce equipment downtime by 30-50 percent and increase its lifespan by 20-40 percent.

-       For operators and Entities in Charge of Maintenance (ECM), it serves as a central repository for compliance, ensuring traceability of maintenance activities.

-       Lastly, it transforms ways of working to make workers more productive. Repetitive clerical tasks can be automated, schedules optimized based on resource availability, and native mobile applications ensure that field workers have access to comprehensive asset information.

Visibility Across the Trains’ Complete Lifecycle: The Case of Stadler

Centralizing all data related to maintenance and operations across the entire lifecycle can drive transformative efficiency gains.

Take the example of Stadler Rail Group. Headquartered in Switzerland, the company initially specialized in train manufacturing, becoming the global leader in the rack-and-pinion vehicle market and a developer of high-speed trains like the SMILE, which can reach speeds of up to 250 km/h.

With the increasing privatization of regional rail worldwide, Stadler saw an opportunity to expand into rail vehicle maintenance—a sector with its own set of challenges, including stringent and evolving compliance requirements and the importance of warranty management.

Today, all maintenance activities at Stadler Rail are recorded and tracked in HxGN EAM, enabling the company to map a new train fleet and define maintenance activities in a single system. For Stadler, which combines manufacturing and maintenance, a particularly promising outcome is having visibility across a train’s and a fleet’s complete lifecycle—from the assembly line to the maintenance workshops. Today, this ability to vouch for the entire lifecycle enables Stadler to take on the role of certified Entity of Charge of Maintenance as defined by EU regulations.

Asset Performance Management Optimizes Operations to Meet Service-Level Objectives

The use of data extends further: as train operators face increased competition, they are turning to advanced maintenance strategies like asset investment planning (AIP) and asset performance management (APM) to ensure that their maintenance practices meet their economic goals.

HxGN APM, Hexagon’s recently launched asset performance management platform, helps transportation companies adopt a data-driven approach to one of their most critical challenges: aligning maintenance practices with quality, availability, and cost targets.

The platform employs an advanced analytical and optimization engine that continually assesses the risk of asset failure and aligns maintenance, inspections, and monitoring activities with the asset’s actual condition, health, and criticality. This approach removes guesswork from decision-making and risk management, allowing companies to focus resources where they are most needed.

Asset Investment Planning (AIP) builds on this approach to optimize investments and repair-or-replace decisions. Both strategies are crucial in rail, a sector where asset maintenance can consume up to 20 percent of a company’s total revenue. Investment decisions—such as whether to repair or replace an asset, upgrade equipment, or expand services—can have costly consequences if not grounded in data and shaped by accurate assumptions.

The benefits are substantial: in continental Europe, the average age of rolling stock coaches is 33 years. Extending asset longevity, predicting failures before they occur, and optimizing investments are central to operating companies’ need to do more with less. For large fleets, these are literally billion-dollar questions— and digital technologies can bring billion-dollar answers.