A digital twin is a virtual representation of a physical object, system, or process that mimics its behavior and characteristics. It is created by integrating data from various sources, including sensors on the physical object, human experts, and historical data, with artificial intelligence and software analytics. The digital twin is constantly updated with new information and can provide real-time insights into the performance of the physical counterpart. This technology can help businesses improve product quality, troubleshoot problems remotely, and gain valuable insights into customer usage patterns. By creating a digital twin, manufacturers can better understand the behavior of their products, identify potential faults, and make improvements to increase customer satisfaction and improve overall efficiency.
Digital twin refers to a digital replica of physical assets, processes and systems that can be used for various purposes.The digital representation provides both the elements and the dynamics of how an Internet of Things device operates and lives throughout its life cycle.
Digital twins integrate artificial intelligence, machine learning and software analytics with data to create living digital simulation models that update and change as their physical counterparts change. A digital twin continuously learns and updates itself from multiple sources to represent its near real-time status, working condition or position. This learning system, learns from itself, using sensor data that conveys various aspects of its operating condition; from human experts, such as engineers with deep and relevant industry domain knowledge; from other similar machines; from other similar fleets of machines; and from the larger systems and environment in which it may be a part of. A digital twin also integrates historical data from past machine usage to factor into its digital model.
In plain English, this just means creating a highly complex virtual model that is the exact counterpart (or twin) of a physical thing. The ‘thing’ could be a car, a tunnel, a bridge, or even a jet engine. Connected sensors on the physical asset collect data that can be mapped onto the virtual model. Anyone looking at the digital twin can now see crucial information about how the physical thing is doing out there in the real world.
Digital twins give manufacturers and businesses an unprecedented view into how their products are performing. A digital twin can help identify potential faults, troubleshoot from afar, and ultimately, improve customer satisfaction. It also helps with product differentiation, product quality, and add-on services, too.
If you can see how customers are using your product after they’ve bought it, you can gain a wealth of insights. That means you can use the data to (if warranted), safely eliminate unwanted products, functionality, or components, saving time and money.
