NTT DATA and Hyster-Yale Materials Handling (HYMH) have implemented a physical AI solution at a lift truck manufacturing facility in Berea, Kentucky. The system embeds intelligence directly into the assembly process to provide real-time quality assurance by monitoring production workflows.

The solution integrates vision sensors and edge computing to process data on-site. Developed in collaboration with Archetype AI, the model analyses assembly activities against expected production steps to verify that all components are correctly installed. The system flags deviations before a product moves to the next stage of the manufacturing line.

The companies reported that the use of physical AI and edge computing reduced deployment timelines from months to weeks compared to traditional techniques. By processing data locally, the system avoids the latency associated with cloud-based analysis, allowing for immediate intervention on the factory floor.

“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 at NTT DATA, Inc. He noted that the system helps manufacturers deliver high-quality products while supporting frontline workers through data-driven outcomes.

The initiative is part of a broader collaboration between the two companies to modernise industrial assembly. HYMH, which manufactures the Hyster and Yale brands, intends to use the technology to maintain high-quality standards across its global manufacturing operations as it increases its use of automation.