Hitachi Rail Unveils Hagerstown: A Digital Factory Built on UDL

By Gianfranco Messina, Vice President of Digital Transformation, Hitachi Rail, and

Sudhanshu Gaur, Vice President, Mobility Innovation Lab, R&D Division, Hitachi America, Ltd.

Hitachi Rail’s new manufacturing facility in Hagerstown, Maryland, was conceived from the outset as a digital-first factory. Rather than layering technology onto legacy systems, it was built on a foundation called the Unified Data Layer (UDL). This allowed the site to avoid the inefficiencies that typically accumulate in industrial operations—disconnected systems, fragmented data, and reliance on manual workarounds, and a dependence on a few individuals to make sense of the data and translate it into actionable decisions.

As a result, Hagerstown is more than a state-of-the-art production site. It demonstrates how standardized data and preserved knowledge can enable faster problem-solving, shorter ramp-up times for new staff, and continuous learning across the entire product lifecycle.

The Broader Challenge

Hagerstown offers a glimpse of what’s possible when digital infrastructure is built in from the start. But most factories face a very different reality. Legacy—or brownfield—sites have evolved over years, shaped by changing customers, technologies, and vendors. The result is a patchwork of systems that rarely work together.

These sites generate vast amounts of data, but much of it remains underused. Information is scattered across incompatible systems, with inconsistent formats, units, and naming. Even identical product lines may run on different technology stacks. Making sense of the data—let alone using it for improvements—often depends on a handful of experts who know where to look and understand what it all means.

This fragmentation slows progress. Integration takes months, insights stay locked in silos, and digital upgrades rarely scale beyond local fixes.

What UDL Enables

UDL represents a new kind of industrial platform—shaped by Hitachi’s deep understanding of operational challenges across its own global manufacturing footprint and commitment to harnessing Generative AI (GenAI) in ways that deliver meaningful, scalable value. While many in the industry are directing GenAI toward narrowly defined applications, Hitachi is rethinking the foundation itself.

At the heart of this approach is UDL Context Studio, a capability that blends AI agents with human expertise to generate contextual intelligence. Data from Product Lifecycle Management, Manufacturing Execution, Supervisory Control and Data Acquisition, and Enterprise Resource Planning systems can be connected, interpreted, and applied—without the need to replace existing infrastructure. 

AI agents assist with data mapping and semantic alignment, while confidence scores guide when and where human input is required. Once validated, that knowledge is captured and reused—ensuring consistency, reducing redundancy, and accelerating application development.

This dramatically lowers the time and cost of scaling digital solutions. What once took months or even years of system integration can now be achieved in weeks. Instead of deploying applications line by line or factory by factory, UDL enables scale with consistency, traceability, and speed.

Imagine a GenAI-powered worker support tool that draws from design specs, production history, and maintenance records. Without a unified data foundation, replicating that tool across sites would demand custom integration at every step. With UDL, deployment becomes agile and repeatable—enabling faster returns, more adaptive systems, and smarter decisions from the ground up.

From Factory to Digital Thread

Our vision for UDL is for it to serve as the backbone of a true digital thread—connecting factory systems with operations, maintenance, and service across the entire product lifecycle. While this integration is still evolving, we are actively building toward it.

By closing the loop between manufacturing and field performance, UDL can unlock new business use cases—such as automated root-cause analysis—and make existing ones like predictive maintenance and quality assurance more accurate, timely, and cost-efficient. It enables insights to flow across phases, so that every part of the value chain learns from the others.

Enabling Scalable Intelligence

With UDL as the foundation, the future lies in scalable intelligence—where AI agents don’t just assist, but coordinate, adapt, and learn continuously. Updates will resemble software upgrades, not disruptive overhauls. As UDL extends across the product lifecycle, the opportunity is not just in connecting machines, but in enabling operations that improve themselves over time.

And manufacturing is only the beginning. Industries like healthcare, energy, transportation, utilities, and public infrastructure face many of the same challenges: aging systems, siloed data, and a reliance on individual experts to interpret and act on information. UDL brings a unified, contextualized layer across these domains—making it easier to connect systems, preserve institutional knowledge, and scale digital solutions with consistency and confidence.

Hagerstown demonstrates what this future can look like. It’s more than a new facility—it showcases what’s possible when organizations rethink their digital foundations. Ultimately, the power of UDL lies not just in data connectivity but in capturing and preserving the expertise organizations already have—ensuring it’s never lost as systems evolve and people change.