Industrial IoT · Glossary
Digital Twin
A digital twin is a live digital replica of a physical asset, process, or facility, continuously updated with sensor and operational data. It lets teams simulate changes, predict failures, and optimize performance without touching the physical system.
Industrial digital twins range from single-asset models to plant-wide simulations tied to historians and MES data. Value concentrates where physics-based models meet real-time data: energy optimization, predictive maintenance, and operator training.
In practice
In the industrial IoT sector, engineers and data analysts use digital twins to monitor machinery in real time, allowing them to simulate scenarios and assess the impact of potential changes. This informs decisions around maintenance schedules, resource allocation, and operational efficiency. By optimizing asset performance and predicting failures before they occur, companies can significantly reduce downtime and maintenance costs, ultimately leading to improved productivity and profitability.
Where Digital Twin shows up on MarketScale
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