Hyster-Yale Materials Handling and NTT Data announce breakthrough physical AI solution in manufacturing

Hyster-Yale Materials Handling, Inc. (HYMH) and NTT DATA announced a breakthrough application of physical AI that embeds new intelligence directly into manufacturing processes. This approach leverages sensor data to enable machines and systems to perceive, understand and act in real-time within real-world operations.

Bringing this capability into practice introduces AI-driven quality assurance directly into HYMH’s manufacturing operations. This co-developed approach represents a first-of-its-kind use case of how physical AI can be applied in an industrial assembly environment by embedding intelligence into production workflows, helping to safeguard that products are built to consistently high standards.

NTT DATA designed and developed the solution at HYMH’s manufacturing facility in Berea, KY, integrating vision sensors, edge AI that processes data on-site, and advanced analytics into a critical assembly workflow.

Together with partner Archetype AI, NTT Data in collaboration with HYMH, adapted a physical AI model that analyzes assembly activity against expected production steps, validating that all parts are installed and assembly stages are completed, flagging deviations before the product moves to the next stage. By validating quality throughout the assembly process, the solution helps identify and address potential issues before products leave the factory floor.

This initiative demonstrates a step-change in how AI can be applied in manufacturing environments. Combined with edge computing, the solution can run locally so all processing happens on-site, enabling faster rollout and quicker time-to-value. Early results showed that physical AI cuts deployment timelines from months to weeks when compared with legacy techniques, accelerating adoption and iteration across manufacturing operations.

“Our confidence in physical AI continues to grow, and we’re starting to see the countless benefits that AI can bring to our global manufacturing operations,” said Barbara Binda, Director of Global Manufacturing Innovation, Hyster-Yale Materials Handling. “Working with NTT DATA allows us to leverage how physical AI can help our production teams maintain high-quality standards and deliver the most reliable products to our clients.”

"This deployment shows what physical AI looks like in real production environments, not as a concept, but with tangible impact on the factory floor,” said Shahid Ahmed, Global Head of Edge Services, NTT DATA. "By combining real production data with physical AI models at the edge, we’re helping leading manufacturers like HYMH deliver high quality products, support frontline workers and apply AI in ways that deliver real-world outcomes.”

As manufacturers accelerate automation, demand is rising for physical AI that can operate safely in complex environments, driving efficiency, quality and resilience. NTT DATA is uniquely positioned to deliver this capability at scale, combining industry expertise with end-to-end services to integrate AI across IT and operational technology environments, enabling intelligent, data-driven operations.

Today’s news builds on a longstanding collaborative relationship between NTT DATA and HYMH. Together, the companies are advancing more adaptive and intelligent manufacturing processes and exploring how physical AI can be scaled to drive repeatable, high-quality production outcomes.