Maximizing Digital Twin Value Through Targeted Decision Improvement
- Published
- Source
- AutomationWorld.com
In modern manufacturing plants, data is abundant, yet many digital twin projects fail to deliver actionable insights. The key issue lies in the disconnect between having data and answering critical operational questions. Instead of pursuing comprehensive virtual replicas, teams should focus on improving specific decisions with tailored digital twins that connect to live operational data.
Digital twins are often mischaracterized as needing to be elaborate 3D models of entire facilities. However, the most effective digital twins are simple, fit-for-purpose models that accurately reflect a particular process and its current state. By concentrating on decisions that carry significant operational or financial implications, organizations can create valuable digital twins that enhance decision-making.
To ensure success, it is crucial to define the decision and its consequences before integrating data. Existing control systems and historian data can be leveraged to build trustworthy models without starting from scratch. This disciplined approach allows manufacturers to maximize the utility of their digital twins while avoiding the pitfalls of overly ambitious integration projects.
Original report
A Digital Twin Is Only As Useful As The Decision It Improves
AutomationWorld.com · John ParragaThis briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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