Digital Twin
A virtual replica of a physical asset, process, or system that uses real-time data to simulate, predict, and optimize performance. Digital twins enable manufacturers to test scenarios, identify potential issues, and optimize operations without disrupting actual production.
RELATED TERMS
Industrial Internet of Things
The application of Internet of Things technology in industrial settings, connecting machines, sensors, and systems to collect and exchange data for improved manufacturing operations. IIoT enables real-time monitoring, predictive maintenance, and data-driven decision-making across the production environment.
Predictive Maintenance
A maintenance strategy that uses sensor data, analytics, and machine learning to predict when equipment is likely to fail, enabling repairs before breakdowns occur. Predictive maintenance reduces unplanned downtime and maintenance costs compared to reactive or time-based maintenance approaches.
Real-Time Monitoring
The continuous collection and display of production data as events occur, providing immediate visibility into equipment status, process conditions, and performance metrics. Real-time monitoring enables rapid response to problems and supports data-driven decision-making on the shop floor.
Machine Learning in Manufacturing
The application of artificial intelligence algorithms that learn from historical and real-time production data to improve manufacturing processes. Machine learning enables predictive maintenance, quality prediction, process optimization, and demand forecasting by identifying patterns humans might miss.