On high-speed trains, decor management contributes to guaranteeing high comfort standards and a travel experience consistent with the premium positioning of these services.
In a context characterized by large passenger volumes, tight rail maintenance cycles and thousands of heterogeneous components to repair and replace, the traditional balance between efficiency and customer experience necessarily requires process digitalization and the adoption of advanced technologies – starting with Artificial Intelligence.
In this article, we explore how innovation has been applied to train decor management and analyze how NetCom and Hitachi accelerated all the activities and made them more efficient through AI-based solutions.
The Challenges of Decor Management on High-Speed Trains
In the railway context, decor maintenance includes all the activities that keep the train’s interior and exterior environments in the best possible condition. This includes furnishings, seats, panels, headrests, tables, upholstery, lighting elements, and everything that, in general, makes the travel experience pleasant for passengers.
A Structured Process, not a Single Activity
Décor maintenance does not correspond to a single operation but to a process composed of several coordinated phases.
- Scheduling of interventions
- Detection of components to repair or replace (inspection, or check-in)
- Communication with warehouses
- Management of logistics teams and maintenance teams
- Supplier management
- Final verification (check-out)
- Detailed reporting to management
In the past, these rail maintenance activities were managed manually and in a fragmented way, using different tools and paper-based forms. The result was a non-uniform workflow and, in some phases, a process heavily dependent on the experience of individual operators. Making an inexperienced resource autonomous – especially in inspection activities – was long and labor-intensive.
The most significant part of the complexity lies precisely in the inspection phase, or check-in. In this phase, the operator must accurately identify the components to restore or replace, moving within an environment that contains at least 1,500 decor components, often available in multiple variants and repeated several times across different compartments.
This means distinguishing components that are visually similar but technically different—an activity that historically required years of experience and a deep knowledge of the specific models and layouts of the fleet.
From Process Complexity to Technological Solutions: EWMS and AI
On Frecciarossa trains, decor maintenance is entrusted by Trenitalia to Hitachi, which uses an EWMS (Extra Warranty Management System) platform to standardize and control the entire process.
NetCom handled the integration of the solution, adapted it to operational workflows, and manages the system continuously, transforming an activity traditionally fragmented into a coherent, monitorable, and uniform digital cycle across the entire fleet.
EWMS, the Rail Maintenance Platform that Supervises the Process
The complexity surrounding decor maintenance requires a management system capable of orchestrating all process phases end-to-end, ensuring continuity between intervention scheduling, inspections, material management, technical team activities, and closure of tasks.
The EWMS platform performs this role precisely, offering a single framework that connects all involved stakeholders, automates repetitive operations, and provides reliable data for analysis and reporting.
Innovative Check-In thanks to Artificial Intelligence
The highest level of innovation emerged in the check-in phase, where the goal was to enable operators to perform inspections quickly, uniformly, and independently of their level of experience.
All inspection activities were redesigned to be performed via tablet – a device easily distributed to personnel. The EWMS-integrated application allows operators to detect components to restore or replace using different modes, adapting to any situation.
- The most innovative element is the ability to automatically recognize objects through artificial intelligence functions. The app uses Object Detection models trained to identify specific train components simply by framing them with the tablet’s camera.
This advanced approach improves over time through machine learning as the system acquires more examples, expands the recognition dataset, and refines material classification.
In practice, the more the system is used, the more accurate the algorithm becomes, reducing ambiguity, accelerating inspections, and making the process increasingly independent from the operator’s visual memory or direct experience.
- Alternatively, operators can select the component from a complete photographic catalog, including variants and specific configurations. This is the most immediate method when the object is clearly visible and easily recognizable.
- Components can also be identified using QR codes applied to furnishings – a fast and precise solution for the most accessible elements.
- For parts difficult to frame with the camera or located in complex areas, the app provides a graphical environment based on technical drawings of the carriages, allowing operators to select components directly from the digital representation of the interior.
The use of AI and machine learning techniques for decor maintenance can be considered part of the 20 use cases currently considered to have the highest potential in the railway sector (McKinsey). Despite the value estimated for the entire industry – between 13 and 22 billion dollars per year – large-scale adoption remains limited.
In this context, the initiative implemented on Frecciarossa trains represents one of the most advanced examples of operational application of artificial intelligence.
The Benefits: More Speed, More Quality
Digitalizing the entire process of managing decor components has already produced – and continues to produce – immediate benefits for both operators and management.
The standardization of workflows and automation of repetitive phases reduced downtime, identification errors, and delays previously caused by fragmentation, manual procedures, and the absence of end-to-end visibility. The impact on operational capacity is clear: in the last month alone, 2,000 maintenance interventions were carried out on Frecciarossa trains – a significantly higher volume compared to the past.
Naturally, this growth is not linked to an increase in resources but to process efficiency: inspections are faster, communication with warehouses and teams is immediate, material preparation is more accurate, and reporting is generated automatically.
Netcom, Hitachi And Trenitalia: the Technological Integration
Projects of this nature do not simply involve adopting a platform, but require extensive analysis, configuration, and integration work.
In the case of Frecciarossa, NetCom supported Hitachi Rail STS S.p.A and Trenitalia throughout all activities needed to transform EWMS into a customized, on-board operational tool, tailored to team needs and the complexity of the rolling stock.
One of the most demanding tasks was mapping cabin components. Every element – seats, panels, tables, pictograms, etc. – was photographed and classified by type, variant, and position within the carriages. This work required months of on-board activity and extreme precision, because even small mistakes can compromise operator adoption of the system.
Another challenge involved connectivity. During maintenance operations, trains are often located in areas with no Wi-Fi or mobile coverage. NetCom therefore designed a synchronization system that allows the app to function offline while minimizing storage requirements, considering that any tablet has physical limits in memory and computing capacity.
Alongside technical configuration, NetCom trained inspection personnel, transferring skills related to tablet use and gathering feedback to improve the user experience. Currently, support is continuous, with 24/7 involvement to promptly address issues and update the system according to real operational needs.