What is digital twins and how to use it in asset management?

The world scenario today is one of accelerating digital transformation processes. The change in consumption, work, life and behavior habits are shaping the new technologies that emerge day after day, always looking to make our day to day easier.

?In this context, a new technology gaining strength is the digital twin, which aims to create a virtual replica faithful to a physical object so it can provide all perspectives and important data for a product, process, service. or machine.

?Multiple technologies have emerged in recent years critical to driving the advancement of smart manufacturing and the Industrial Internet of Things. This includes advanced analytics, artificial intelligence (AI) and machine learning (ML), operational intelligence, advanced robotics, cyber-physical systems and additive manufacturing.

While each technology is changing the face of manufacturing today, research by the ARC Advisory Group suggests that Industrial IoT, connected smart assets and especially the digital twin are having the most immediate and significant impact on how companies implement technologies. According to Gartner's IoT Implementation Survey, organizations implementing IoT already use digital twins (13%) or plan to use it within a year (62%).

In this context, digital twin is nothing more than the concept that effectively materialized this whole idea. By means of a virtual model of a physical object, designers, engineers, among other professionals, can accurately dimension what the final result of a project and its entire life cycle will be, based on a simulation.

From this concept, mobile devices, equipment and a multitude of common products in people's lives can be tested by those who will actually consume them, making usability, efficiency and compatibility with needs much more precise.

Today, manufacturing engineers are merging virtual engineering models with physical equipment in an environment that enables operational performance improvement and predictive equipment maintenance.

Benefits of digital twins:

? Lower maintenance costs through predictive maintenance: digital twins allow companies to understand potential sources of failure so companies can minimize non-value added maintenance activities;

? Improved Productivity: Gartner research predicts that industrial companies can see a 10% improvement in effectiveness through digital twins. This is due to reduced downtime due to predictive maintenance and improved performance through optimization;

? Faster turnaround times: IDC claims that companies that invest in digital twin technology will see a 30% improvement in cycle times for critical processes, including production lines. This is due to improved optimization thanks to digital twins;

? Testing before manufacturing: Companies can use digital twins to understand the viability of upcoming products;

? Greater customer satisfaction: this would lead to happier customers who receive higher quality products without delay.

By using digital twins that represent the product and production systems, manufacturers can reduce the time and cost associated with assembling, installing and validating factory production systems. And implementing digital twins for asset management often provides quantifiable benefits for maintaining equipment in the field.

There are different technologies involved in the concept of digital twin, however, the Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning, are perhaps the ones that most mark the features of the digital twin.

At the enterprise level, IoT, AI and ML support the digital twin to be even more efficient. The IoT, for example, allows more products, equipment and devices to be interconnected, communicating and informing engineers.

Similarly, Artificial Intelligence and Machine Learning power optimizations within enterprise environments. That's because digital twins have the ability to learn from situations. Complex calculations are performed while sensors capture information, conditioning the machine to make the best decisions and to seek the optimal point in operations.

An integral component of a production system digital twin is the virtual model of real-world products, assets and processes. Virtual modeling provides manufacturing engineers with the ability to simulate and model both the virtual and the physical, simultaneously or separately.

This digital twin system modeling approach allows them to understand the holistic nature of their assets and production systems within the overall manufacturing ecosystem.

In addition, we are seeing the emergence of powerful digital twin development tools offered by vendors that will enable manufacturers to understand exactly how their plant systems and equipment work and decide to improve product performance and quality through human intelligence. and artificial. Next week, we will see the practical applicability of digital twins.

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