Ever-increasing volumes of information have changed the way manufacturers operate. More and more, manufacturers are adopting digital twins to help their organizations shift to digital-driven asset management.
Last week, I shared how digital twins are transforming business through five use cases for digital twins in the Manufacturing industry. Today I’d like to share three production and predictive maintenance use cases for digital twins in manufacturing.
Production visibility
The data continuously collected from the IoT devices connected to production equipment creates a comprehensive image of the current state of that production system in operation. The digital twin allows real-time production data to identify where assets are under-performing or showing signs of stress.
Production optimization
Beyond visibility, real-time production data can be used to model production operations within the digital twin. Through direct connection between the twin and the physical asset, you can immediately change settings and configurations to optimize performance. In addition, digital twins can give access to performance details of similar equipment in other plant locations to model the best asset performance given capacity and environmental conditions.
Predictive maintenance
By reviewing historical data or comparing with a similar production system, a digital twin can advise you of failure in components and the anticipated wear on parts. This reduces the risk of unplanned downtime and the need for scheduled maintenance. The twin allows you to quickly change settings to increase the longevity of a component, schedule maintenance before the problem arises, or initiate the replenishment process where the part has to be replaced.
