Hitachi Physical AI for Industrial Equipment Diagnosis and Railway Traffic Management

Title

Hitachi Physical AI for Industrial Equipment Diagnosis and Railway Traffic Management

Content

Physical AI, the branch of artificial intelligence that controls robots and industrial machinery in the real world, has a hierarchy problem. At the top, OpenAI and Google are scaling multimodal foundation models. In the middle, Nvidia is building the platforms and tools for physical AI development. Hitachi is making the argument that industrial manufacturers cannot train machines to navigate the physical world without first understanding it. Hitachi has deployed an AI system with Daikin that diagnoses malfunctions in commercial air-conditioner manufacturing equipment, trained on equipment maintenance records, procedure manuals, and design drawings. With East Japan Railway (JR East), Hitachi has built an AI that identifies the root cause of malfunctions in the control devices running the Tokyo metropolitan areas railway traffic management system, and then assists operators in formulating a response plan. In December 2025, Hitachi published findings from two projects presented at ASE 2025 addressing the time and effort required to write and adapt control software. In the automotive sector, Hitachi and its subsidiary Astemo developed a system using retrieval-augmented generation to automatically produce integration test scripts for vehicle electronic control units (ECUs), reducing integration testing man-hours by 43%. Hitachi Vantara is positioning itself as an early adopter of NVIDIA RTX PRO Servers for agentic and physical AI workloads. The IWIM concept is designed to connect Nvidias open-source Cosmos physical AI development platform with specialised Japanese-language LLMs and visual language models via the model context protocol (MCP).