AI-Enabled Industrial Analytics to Optimize Machine, Production and Quality Outcomes
Manufacturers face challenges such as defective products, on-time delivery slippage, excessive scrap and rework, unacceptable equipment downtime, and supply chain disruption. As the number of assets and production facilities increase, it becomes more difficult to diagnose and react to these challenges in a timely and scalable manner. Such difficulties can have cascading effects on production schedules and translate to higher production costs, lost profits, missed order fulfilment and reputational damage. Information silos and manual data collection add complexity to making near-real-time operational decisions.
Lumada Manufacturing Insights from Hitachi leverages AI and Machine Learning (ML) techniques to provide answers to these challenges, by connecting data from man, machines, method and materials for situational awareness.
By offering end-to-end solutions that encompass sensors, connectivity, data integration, event-driven alerts, forecasts and dashboard visualization, enabled by sophisticated analytics models, manufacturing organizations are able to realize transformative outcomes.
Lumada Manufacturing Insights builds on the intelligent manufacturing maturity model and empowers the digital innovation foundation essential to Manufacturing 4.0. It leverages AI and ML techniques, as well as 4M Industrial Analytics to provide machine, production and quality insights.
Lumada Manufacturing Insights provides answers for improving on-time delivery (planning and scheduling optimization), minimizing defective product, scrap, and rework (maximizing first-pass yield) and reducing unplanned equipment downtime (predictive and prescriptive maintenance), as well as quickly and effectively reacting to external factors such as supply chain disruptions upstream and downstream of the factory floor.
Lumada Manufacturing Insights offers end-to-end solutions to manufacturers in various stages of their digital transformation. Hitachi is ready to partner with customers in this journey.
Solution By: Hitachi Vantara