Hitachi America R&D is engaged in research activities that leverage big data analytics, internet of things, artificial intelligence (AI), machine learning and other technologies. These activities are designed to provide the foundation for new solutions that help organizations optimize operations, improve productivity and efficiency and solve unique challenges. Our research is focused on four key areas: asset lifecycle management, optimized manufacturing, predictive maintenance and finance.
At Hitachi America, our R&D team is expanding the boundaries of operational excellence through new technologies and solutions that drive new levels of operational efficiency and environmental sustainability.
Our Solutions
- Unified Data Layer (UDL): Turning Industrial Complexity into Scalable Intelligence
- Trusted Industrial AI: Intelligence Built for the Front Line
- AI-Powered Grid Optimization for Clean Energy Systems
- Predictive Maintenance: Preventing Downtime Before It Happens
- Human-Centric Manufacturing: Digital Tools Designed Around Workers
Unified Data Layer (UDL): Turning Industrial Complexity into Scalable Intelligence
Hitachi’s Unified Data Layer (UDL) redefines how industrial data is connected, understood, and applied. Rather than forcing costly system replacements or brittle point integrations, UDL creates a standardized, contextualized foundation across existing PLM, MES, SCADA, and ERP systems—preserving both data and the operational knowledge embedded within them.
At the core of UDL is Context Studio, where AI agents work alongside human experts to map, align, and interpret data semantically. Confidence scoring ensures that human judgment is applied where it matters most, while validated knowledge is captured and reused—eliminating redundant effort and reducing dependence on a handful of specialists.
The result is speed and scale. What once required months or years of custom integration can now be achieved in weeks. Digital applications—such as GenAI-powered worker support, quality analytics, or predictive insights—can be deployed consistently across lines, factories, and regions, without re-engineering each environment.
More than a data platform, UDL is the backbone of a true digital thread, enabling continuous learning across the product lifecycle. By connecting design, manufacturing, operations, and service, UDL allows organizations to move beyond isolated improvements toward systems that learn, adapt, and improve over time.
Trusted Industrial AI: Intelligence Built for the Front Line
Hitachi’s industrial AI is designed to earn trust where it matters most—on the shop floor. In environments defined by safety, precision, and uptime, AI must support workers without overruling their judgment or disrupting proven workflows.
Hitachi embeds AI directly into frontline tools, enabling natural-language interaction, guided diagnostics, AI-assisted inspections, and intuitive control of robots and remote systems. Technicians can describe problems in their own words, receive contextual guidance drawn from operational knowledge, and remain fully in control of decisions. Across use cases, the AI learns continuously from human feedback, improving accuracy while preserving expertise.
What sets this approach apart is partnership. Hitachi’s systems make recommendations, not decisions; they are transparent, adaptive, and deployed alongside workers—not over them. The result is AI that feels less like software and more like a trusted colleague, helping teams work faster, safer, and with greater confidence at the point of work.
AI-Powered Grid Optimization for Clean Energy Systems
As utilities integrate large volumes of distributed energy resources, electrified transportation, and renewable generation, managing the electricity distribution grid has become exponentially more complex. Climate-driven disruptions—such as heat waves, wildfires, and extreme weather—only heighten the need for more advanced planning and operational intelligence.
Hitachi’s AI-powered grid optimization solution addresses this challenge by combining high-fidelity distribution system modeling with intuitive, visual analytics. The platform simulates how generation, storage, loads, and grid assets interact under real-world conditions, enabling utilities and regulators to evaluate reliability, resilience, and sustainability impacts before changes are deployed.
By automating data access and scenario analysis, the solution replaces slow, manual workflows with a collaborative digital workspace. Engineers and planners can rapidly assess the effects of new DER interconnections, electric vehicle charging, and infrastructure investments—reducing analysis time from weeks to hours and improving decision quality.
Designed with an open, extensible architecture, the solution supports consistent treatment of DERs, helps identify congestion and voltage risks early, and enables smarter investment planning. It provides a shared foundation for collaboration across utilities, regulators, researchers, and policymakers—accelerating progress toward grid resilience and long-term carbon-neutral energy goals.
Predictive Maintenance: Preventing Downtime Before It Happens
Hitachi’s predictive maintenance solution applies AI and machine learning to move maintenance from reactive response to proactive prevention. By analyzing historical and near–real-time operational data—such as fault codes, usage patterns, and repair history—the solution identifies early signals of potential failures days or weeks before they occur.
Originally co-developed with Penske, the solution builds on AI-guided diagnostics to continuously monitor assets at scale and detect anomalies that indicate emerging issues. Instead of waiting for breakdowns, organizations can schedule targeted maintenance in advance—reducing unplanned downtime, extending asset life, and improving service reliability.
The platform integrates seamlessly with existing connected asset and telemetry systems, transforming data that was previously underutilized into actionable insight. Maintenance teams receive clear, prioritized alerts that support faster, more confident decision-making—without requiring deep analytical expertise.
The result is a measurable improvement in operational resilience: fewer disruptions, more predictable schedules, lower maintenance costs, and a better experience for both operators and end customers. While proven in fleet operations, the same approach applies across asset-intensive industries such as manufacturing, energy, and transportation—anywhere uptime is critical and failures are costly.
Human-Centric Manufacturing: Digital Tools Designed Around Workers
Hitachi’s human-centric manufacturing solution puts frontline workers at the center of digital transformation. Rather than asking people to adapt to technology, the approach designs technology to adapt to how work is actually done—on the shop floor, under real constraints, and with real human judgment.
By co-creating solutions with operators, manufacturers can close skills gaps, accelerate onboarding, and improve quality without increasing workforce strain. Wearable technologies, augmented reality guidance, collaborative robots, and GenAI-powered assistants support workers in real time—enhancing precision, safety, and confidence while preserving human decision-making.
A defining feature of this approach is deep engagement with workers throughout design and deployment. Frontline feedback shapes functionality, usability, and even new use cases, ensuring tools are trusted, adopted, and continuously improved. GenAI further extends this model by enabling natural-language interaction, personalized guidance, and adaptive training—making advanced capabilities accessible to workers at every skill level.
The result is higher productivity, faster learning, and more resilient operations. Human-centric manufacturing doesn’t replace people—it amplifies their expertise, helping manufacturers do more with fewer workers while building a more engaged, future-ready workforce.
Technologies Behind the Solutions
At Hitachi America Research and Development Division (R&D), we recognize that the Internet of Things (IoT) edge is critical to every industrial IoT solution. That’s why we are developing innovative IoT edge, core analytics and platform solutions. We leverage our decades of experience in IT, operational technology (OT), and products and systems to discover new answers to society’s challenges. Our collaborative, multidisciplinary teams create solutions with our customers and for our customers.
At Hitachi America R&D, we focus on innovation and innovative solutions. Our talent set is unmatched. In addition, the Hitachi group companies have a worldwide reach. We can tap into those global resources whenever needed. And the Hitachi Global Insights Lab brings together a team of researchers and designers from around the world to support technology innovation in several research centers. Together, we are innovating to create advanced solutions that will benefit the world.
IoT Edge Solutions
Focusing on all major aspects of the IoT edge, our solutions are tailored to solve industrial IoT problems and have been deployed in real-world use cases in manufacturing, transportation and other sectors. These solutions feature:
- Scalable and modular architecture: Our multitiered, remotely managed edge architecture accommodates use cases with single or multiple edge nodes. The loosely coupled architecture adds flexibility to the system to allow for location-agnostic services such as data storage, compute and visualization.
- Distributed analytics orchestration: Microservices-based architecture allows seamless distribution of analytics anywhere across the IoT fabric, from sensors to edge to cloud.
- Ubiquitous connectivity: Our solutions support multiple industrial connectivity protocols, and our advanced connectivity solutions provide noninvasive data extraction from digital displays.
- Flow management: We offer structured and unstructured data flow management and data lake storage in a common format, based on compute, network and application constraints.
- Inference sensing: Solutions based on sensor fusion (such as acoustic/vibration/camera/OT data) render edge analytics solutions in real time.
- Security: Sensing-layer security analyzes the behavior of all data sources and alerts stakeholders when potential security breaches are detected.
IoT Edge/Core Analytics
Deploying solutions based on artificial intelligence (AI) presents challenges, such as managing data collection and building and deploying models from edge to core. To address these, Hitachi America R&D has built an architecture for flexible deployment of analytical solutions in the cloud or on edge servers. The architecture uses docker images that can be deployed entirely on cloud virtual machines, entirely on edge servers or in a hybrid model with images on both.
IT Platform
Hitachi’s IT platform is fundamental to integrating IT with OT. We integrate AI/analytics and IoT/edge technologies on the IT platform to uncover unprecedented insights. The IT platform is high-performance, agile, flexible and reliable, with integrity from edge to core configured through hybrid cloud solutions. Application developers can leverage Hitachi AI/analytics and edge solutions to focus on development, while cloud operators can focus on maintaining their services nonstop without increasing operating cost.
Hitachi America R&D continues to work on collaborative creation with customers to understand their challenges, validate ideas and create solutions that overcome both business and social challenges.
Industrial AI is the application of Artificial Intelligence and Machine Learning (AI & ML) to address the opportunities and challenges presented in Industry 4.0. This is an important area of research that is gaining prominence due to the ever-increasing number of connected equipment and corporations trying to utilize the latest technologies to enhance their industrial operations.
At Hitachi America Research and Development Division (R&D), we have developed several AI based methods for the following areas:
- Maintenance and Repair Analytics: This includes performance monitoring, remaining useful life estimation, failure prediction, and maintenance recommendations.
- Operation Optimization: This includes operation monitoring, operator profiling, activity time prediction, and scheduling recommendation.
- Quality Enhancement: This includes quality monitoring, batch quality prediction, and operating envelop recommendation
We have successfully applied many of our research results to a wide array of verticals such as manufacturing, mining, mobility, energy and healthcare.
Besides investigating the use of AI&ML to real world use cases, we are also investigating several fundamental research topics, such as new deep learning architectures for machine sensor data, knowledge extraction from industrial corpus, use of deep reinforcement learning for industrial applications, hybrid modeling of industrial equipment and processes, decision making under uncertainty. The ultimate goal of this research is to achieve an end-to-end optimization and automation of industrial operations. Hitachi America R&D is emerging as a leader in Industrial AI with a track record of patent applications, contributions to the research community and the completion of successful real-world applications. Come join us as we revolutionize Industry 4.0.
A thorough understanding of the manufacturing process is key to keeping production quality up and costs down. That’s why today’s manufacturers are turning to end-to-end value chain solutions to improve and modernize product design, prototyping, manufacturing, and maintenance, repair and update (MRU) capabilities.
The Hitachi America Research and Development Division (R&D) is tapping into Hitachi’s extensive IT and operational technology (OT) experience to co-create value chain solutions with our customers. Our end-to-end manufacturing value chain solutions focus on rapid prototyping, smart manufacturing and MRU development. The solutions apply advanced technology to address the dynamic changes affecting manufacturing industries globally.
Our solutions include:
- Rapid prototyping: Hitachi helps customers achieve the best design and prototyping solutions. We use advanced computational tools; our profound knowledge of materials, process, property and performance from static to dynamic; and field-proven experience in virtual manufacturing to accelerate design and production. Our prototyping solutions use the latest augmented reality/virtual reality and three-dimensional printing (3DP)/additive manufacturing technology to streamline the prototyping process and keep costs down.
- Production process innovation: We have developed and implemented innovative new technologies to support production. Our solutions include basic incoming raw material analysis, failure root cause analysis and manufacturing process innovation. For example, some of our process innovations include digital casting, high-speed precision machining, cutting-edge fluid spray technology for machining, high-accuracy bending and forming, and high-speed fusion and solid-state welding. Product quality is assured with destructive and non-destructive testing and inspection, and intelligent production traceability systems help optimize the supply chain.
- On-demand MRU: We combine physics-based component degradation and failure models with component and structure sensing and monitoring solutions to provide on-demand maintenance and repair. And the utilization of 3DP/additive manufacturing technology enables on-site repair and upgrades.
- Co-simulation design testing: Hitachi has developed SimXpand (a registered trademark of Hitachi America, Ltd.), the first co-simulation platform developed to test large-scale, complex, system-level designs across industries. SimXpand applies innovative process automation and high-performance computing cloud technology to ease and speed the coordinated use of multiple, heterogeneous simulation applications. The platform requires fewer manual inputs from users, which dramatically elevates the design team’s ability to tangibly and materially drive value for the business.
Hitachi America R&D has 30 years of proven experience in product design, development, manufacturing process technology advancement and production-line problem-solving with industrial organizations. Our end-to-end manufacturing value chain solutions help manufacturers optimize processes, save money, and improve the value and quality of their products, to the benefit of all.
Distributed ledger technologies (DLTs) are emerging as the leading solution for securing and certifying business data. DLTs, also referred to as blockchain systems, are based on Hyperledger and similar platforms and are generally regarded as immutable. But their data can be manipulated if someone can access all of the system’s nodes, or servers.
Hitachi America Research and Development Division (R&D) has developed a blockchain-based notary system to address that loophole and ensure digital trust. The Hitachi solution manages a blockchain system shared among companies and organizations that have a private ledger that requires independent verification. To ensure privacy of business data, only the Merkle proofs (the mathematically hashed proofs of the data) are stored in the notary service. When data needs to be verified, it is first confirmed against the original system to determine the Merkle proof output, which is then confirmed by Hitachi’s notary system.
Hitachi America R&D is a leader in blockchain technologies and conducts continuous research to make the technology practical for everyday business use cases. Going forward, such solutions will provide a totally secure and private way for companies to certify their business data and ensure a more digitally secure future for all.
