Hitachi Vantara becomes customer zero for its own HMAX AI manufacturing overhaul

Hitachi Vantara becomes customer zero for its own HMAX AI manufacturing overhaul Hitachi Vantara achieved a 50 percent reduction in inventory and 77 percent reduction in order-to-ship lead times at a US storage array manufacturing site by using HMAX agentic AI - and has been rewarded with World Economic Forum "Global Lighthouse Factory” recognition. It is the second such award for Hitachi, following Hitachi’s Omika Works in Japan, which was designated a WEF “Lighthouse” in 2020. HMAX is a suite of AI-powered offerings designed to transform social infrastructure and industrial operations for Hitachi’s mobility (rail), energy, industry, and finance. The US Hitachi Vantara site, at Norman, Oklahoma, makes VSP enterprise storage arrays. Jun Abe, EVP and Head of Digital Systems & Services Sector, Hitachi, said: “The results achieved at the Norman site using Agentic AI are a practical example that is unique to Hitachi, combining our strengths in IT, OT (Operational Technology) and products. Going forward, we will provide the expertise and use cases gained through this initiative to customers around the world through HMAX, contributing to enhanced resilience and sustainable growth across industry as a whole.” The Norman plant needed to improve decision-making speed and optimize resource allocation for a complex product lineup comprising approximately 3,000 variants. This was attributed to global shifts in demand and increasingly customized customer requirements. Parent Hitachi Ltd. and Hitachi Vantara collaborated to introduce AI and digital technologies to include autonomous AI-driven decision-making and control applied to end-to-end supply chain operations from order receipt to shipment. The site became Hitachi Vantara’s in-house “Customer Zero” for HMAX. There were three specific AI initiatives; - AI-Driven Demand Forecasting and Optimization of Management Processes - AI uses business meeting data from the system to forecast monthly demand, improving demand forecast accuracy by approximately 19 percent. When requests