Mission Critical Asset Performance Monitoring Using Industrial AI

Mission critical asset performance monitoring relies on data readiness and analytics availability. While the former requires high throughput ingestion capabilities and heavy downstream transformations of heterogenous data to create actionable information through different AI techniques (multi-domain sensor time-series data coupled with business data), the latter must deliver the resulting information in a timely manner with proper user experience through different interrogation techniques including GenAI. In the current presentation we discuss the continuous integration and improvement of the AI process to achieve effective decision making in the context of Prognostics and Health Management for higher asset reliability and availability.