Digital Twin — definition
Digital twin is a virtual model of a physical machine, line or facility that is kept synchronised with real operational data to support simulation, monitoring or predictive analysis.
Digital twins range in fidelity from simple data-linked 3D models to detailed physics-based simulations used to test control logic or predict maintenance needs before physical changes are made. Applications include virtual commissioning, where control software is validated against a simulated machine before connecting to real hardware.
Why it matters to industrial buyers
Digital twins can reduce commissioning risk and downtime by allowing control logic and process changes to be tested virtually before deployment on physical equipment.
Key reference points
Virtual commissioning
Virtual commissioning against a digital twin is commonly used to validate PLC logic before connecting to physical hardware.
Fidelity range
Digital twin fidelity ranges from basic data visualisation models to detailed physics-based simulations.
Commonly confused with
simulation model
A standalone simulation model is typically static and used once; a digital twin maintains ongoing data synchronisation with the physical asset.
How it is used in practice
A digital twin of a bottling line allowed engineers to test a new changeover sequence virtually before implementing it on the physical machine.
Frequently asked questions
Does every automated line need a digital twin?
No, digital twins are typically justified for complex or high-value lines where simulation reduces significant commissioning or downtime risk.
How is a digital twin kept synchronised?
Through continuous data feeds from sensors and control systems, commonly via industrial IoT connectivity.
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Related terms
Manufacturing Execution System (MES)
Manufacturing Execution System (MES) is software that manages and tracks production orders, work-in-progress, quality data and material consumption on the shop floor in real time.
Industrial Internet of Things (IIoT)
Industrial Internet of Things (IIoT) refers to networks of connected sensors, devices and machines that collect and exchange operational data to support monitoring, analytics and automation across a facility.
Predictive Maintenance
Predictive maintenance is a maintenance strategy that uses condition data, such as vibration, temperature or current signatures, to estimate equipment health and schedule maintenance before failure occurs.
Commissioning
Systematic process of testing, adjusting and verifying that installed equipment and systems operate together as designed before handover to operations.
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Reference content only. Global B2B Group is independent of equipment manufacturers and financing institutions; definitions are provided for education and do not constitute engineering, financial or legal advice.