How Digital Twin technology predicts the future in just 4 steps

From astrological predictions to scientific ones, predicting the future has always been one of men’s goals. And we don’t even need to be so philosophical. To know how much time will take until equipment needs maintenance, life expectancy, among many other examples, are things that we now know how to estimate. But have you ever wondered how the world could be if we had a technology that combines estimations and simulations??

Digital Twin technology is the closest thing we have to predict the future. Many industrial leaders already acknowledged that, and are looking for this kind of technology to solve long-known problems.?

For example, to avoid flooding in big cities you need to have a long water catchment system that will work efficiently. Just like it is necessary to build a power network throughout the city to ensure electricity distribution. Another example is highways - how they will connect the whole city and how to make it all work in harmony in such aggressive, hostile, or complex environments. That's a very holistic view of a city, and that's one of the points where Digital Twin has been applied in what we call “Smart Cities”?

How a Digital Twin Platform Works?

There are many levels of Digital Twin technology, such as Digital Models and Digital Shadows. Here, we are talking about the authentic Digital Twin - a constant flow of data from the virtual model to the digital one and vice-versa. One example of how a Digital Twin platform is built with stacks of technology which are enhanced by combining it with Artificial Intelligence and IoT sensors, for example.?

These stacks are composed of simulations, analytics, operational context, data, and 3D models. Having in mind the phases of the PLM, for a Digital Twin platform to work in the Operation and Maintenance phase, you will need the information from the Design and Engineering phase, such as documentation, technical drawings, and 3D models.??

In a 4 steps workflow

1. Data contextualization: all the data such as paperwork, 3D models, attributes from the industrial plant, spreadsheets, technical drawings, and documentation are uploaded and treated in the Digital Twin.? In this phase, all the documents are centralized and arranged so you can see what data do you need, for what operation, and where it is useful. In that way, you have a holistic vision of the industrial plant.
2. Input data: acquire all the asset management workflow itself, such as information from the inspection made in the field through mobile, sensors that were already used in the operation, even integrations with other systems such as CMMs and ERP systems, etc.?

3. Prediction Phase: the Digital Twin will process data with technologies from the Industry 4.0 movement, such as Artificial Intelligence, Machine Learning, or other algorithms and simulations.?

4. Analytics: In this phase, all the processed data will be analyzed by AI itself, and then it’s possible to integrate all of this Database/Systems, which will be the key to optimize the industrial process.??

In that way, all the data from the industrial plant will be available to the field operator. It is from the integration with other systems, and centralization of data in an authentic Digital Twin platform powered with Artificial Intelligence, that valuable insight is provided. Therefore, it makes it possible to predict the future, even by prescribing what is the best type of maintenance for each piece of equipment.?