Digital twin

Digital twins and AI are no longer just a futuristic image – they are now shaping the business and operations of many industrial enterprises. Still, their most important role is to provide the information about equipment condition and security risks that no human can gather. By combining digital technology with AI, companies can tackle traditional equipment issues in new ways and more efficiently.

The digital twin technology creates virtual copies of production sites, manufacturing and business processes, and enterprise assets. Paired with AI, it allows enterprise operators to find valuable information in production data that can be used to improve processes. These two technologies allow you to capture almost everything that is happening at the enterprise, and thanks to this information, operators can make effective decisions and improve performance.

The digital twins of products are essential for implementing PLM (Product Lifecycle Management). Along with the Industrial Internet of Things, PLM is an integral attribute of the Smart Factory. It features the creation and use of digital models of material flows, so there is a digital twin of the whole production system rather than a separate product. All the above technologies are approaches to implementing the concept of the Fourth Industrial Revolution (Industry 4.0). While traditional industries rely on numerous field tests to verify the achievement of the required product characteristics, Industry 4.0 aims to conduct multiple tests on a digital twin and then pass field tests at the first attempt.

System functionality:

  • Reducing the demand for staff in hazardous or remote areas;
  • Significantly more data on assets – have a new look at your production and optimize performance;
  • Uninterrupted operation of the factory due to accurate failure prediction and asset maintenance.

The digital twin of a production object includes:

  • Geometric and structural model of the object;
  • A set of calculated data on parts, assemblies and the whole product;
  • Mathematical models describing physical processes in the object;
  • Information about manufacturing processes and the combination of separate elements in a product;
  • Product life cycle (PLC) management system.