Manufacturers are unifying industrial data with SymphonyAI’s industrial data operations platform, IRIS Foundry, to optimize their operations, increase the performance of their equipment, and provide actionable insights with AI-powered analysis.
SymphonyAI’s predictive AI models use unified and trusted industrial data to augment decision-making, providing operators with setpoint recommendations to increase throughput or lower energy consumption. As operators become comfortable and provide feedback to the models, the set points can then automatically extend down to the DCS for closed-loop control.
Moreover, IRIS generative AI copilot, powered by Azure’s OpenAI service, reduces unplanned downtime by analyzing equipment performance with predictive AI models.
With unified data, manufacturers achieve granular traceability of individual production lines, as well as holistic operational visibility across the enterprise for insights into overall equipment effectiveness, inventory optimization scheduling, and more.
Manufacturers gain actionable KPIs to create tailored visualizations to measure and forecast performance. They can perform impact analysis that identifies critical paths and include causes and recommended actions.
Each use case is underpinned by an intelligence layer known as the asset and performance knowledge graphs. These interconnected graphs represent the relationships between equipment and performance, allowing manufacturers to seamlessly diagnose how equipment and processes impact one another.
Manufacturers are using SymphonyAI to increase throughput, reduce energy consumption, and empower their teams with AI.