Predictive quality systems use data and analytics to anticipate and prevent defects in manufacturing processes. In practice, these systems ingest real-time and historical data (from sensors, machines, IIoT devices, quality inspections, ERP/MES records, etc.) and apply AI or machine‐learning models to spot patterns or anomalies that signal looming quality issues.