Digital twins let us understand the present and predict the future

A digital twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making.

What this means is that a digital twin is a vital tool to help engineers and operators understand not only how products are performing, but how they will perform in the future. Analysis of the data from the connected sensors, combined with other sources of information, allows us to make these predictions.

With this information, organizations can learn more, faster. They can also break down old boundaries surrounding product innovation, complex lifecycles, and value creation.

Digital twins help manufacturers and engineers accomplish a great deal, like:
Visualizing products in use, by real users, in real-time
Building a digital thread, connecting disparate systems and promoting traceability
Refining assumptions with predictive analytics
Troubleshooting far away equipment
Managing complexities and linkage within systems-of-systems
Let’s look at some of these in more detail.
Use cases for digital twin: an engineer’s point of view
Let’s look at an example of digital twins in action. And since the primary users of digital twins are engineers, let’s use their perspective.
An engineer’s job is to design and test products – whether cars, jet engines, tunnels or household items – with their complete lifecycle in view. In other words, they need to ensure that the product they are designing is suitable for the purpose, can cope with wear and tear, and will respond well to the environment in which it will be used.
Creating real-world scenarios, virtually

The value of a digital twin: understanding product performance
Digital twins give businesses an unprecedented view into how their products perform. 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.
Unprecedented control over visualization, from afar
There are other advantages to a digital twin, too. One of the major ones is that digital twins afford engineers and operators a detailed, intricate view of a physical asset that might be far away. With the twin, there’s no need for the engineer and the asset to be in the same room, or even the same country.
A popular concept reliably creating better products.