What is it and How it works : Digital Twin Technology
Digital Twin Technology, a trending tech in field with IoT and Machine learning. In simple meaning Digital twin is just the virtual module of a product, asset, service or any process.
Digital Twin isn’t new, the concept is since 2002. Internet of Things is the reason of implementing Digital Twin with less efforts and cost. The combining of Virtual and Physical module allows to analyse the data and offers system monitoring for preventing downtime, determining problems even before they occurs and for planning for the future using Digital twin. Digital Twin Technology is basically creating a simulator of the product or a service and gather data and informations that are useful and needed by simulating it. This technology eliminates the scope of guesswork, it provides approximate results by simulation. The technology goes beyond looking at data; it creates virtual 3D models to understand how equipment will perform and then presents options to extend an asset’s life for better business outcomes. So we get that, Digital Twin is a Virtual Model of asset or product. Sometimes the Digital Twin is called as Virtual Twin, these are interchangeably used.
Also Read : Internet of Things explained
How it works?
The above discussion concludes that the Digital Twin or the Virtual Twin act as a bridge between the Virtual and Physical worlds. The Digital Twin has the smart components that are responsible for gathering data about all factors including real-time status, working condition, or position being integrated with a physical item. The smart components in contact with cloud based system receive and processes all the data. This input is then analysed against business and other contextual data. This can help to optimize the product’s performance.
A digital twin is a virtual representation of a product. It can be used in product design, simulation, monitoring, optimization and servicing and is an important concept in the industrial Internet of Things.
What the digital twin produces?
When bundling this data with intelligence, is a view of the each asset’s history and its potential future performance. This continuum of information leads to early warnings, predictions, ideas for optimization, and most importantly a plan of action to keep assets in service longer. The future of digital twin, Volkmann said, will be about sending commands to machines in response to those forecasts. “If you close the loop, with data and predictions, you can act directly on the asset itself,” he said.
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