What is a digital twin?

A digital twin of a physical object is a continually updated model providing information about the object, its environment and use. However, this is not a new concept. As early as 2002, Michael Grieves at the University of Michigan coined the term in relation to Product Life-cycle Management. Among the first organisations to apply the concept was NASA, which needed to solve issues relating to development and maintenance of systems which it was unable to continually communicate with. The advantage of digital twins is that they can be made constantly accessible, unlike their physical equivalents. In addition, you can ensure that all stakeholders receive the same information in real-time.

A growth in interest and development

A major need for streamlining and swift technical development of sensors, data storage and communication have made it possible to realise the concept. In both 2017 and 2018, digital twins featured on the Gartner top-ten list of the most important trends in technology. Within five years, they estimate that over one billion physical objects will have a digital twin.

Benefiting the entire life cycle

A digital twin can mirror products, processes, equipment and facilities, etc., providing support throughout the life-cycle, including development, installation, production, use and reuse. By gaining access to information about the use, condition, environment and context of a product, it is possible to identify when service is required or obtain valuable know-how for product innovation. Digital twins are extremely valuable for testing and evaluation of manufacturing processes and equipment in the development or operational phase, with suppliers able to follow the status and use and take a proactive approach to maintenance measures.

Digital twins at RISE IVF

We boast considerable expertise in modelling products, processes and systems, which is a key component of the digital twin. However, in order to accomplish live updated models, solutions for real-time data gathering in real-time, storage, analysis, access and visualisation are required. Key challenges include clarifying the need for information, which information should be handled and how it is to be processed. In 2018, projects at RISE IVF are developing methods and technology for storage and utilisation of information from various sources.

Digital twins in production

Companies today commonly have digital models of products and processes. However, there are no digital models for the production system. Although there are often 3D models for machinery, equipment and products, etc., the work required in order to model other elements such as walls, fencing, ventilation, command consoles, and tables, etc. is far too extensive.

3D scanning of plants

To address this issue, laser scanning technology can be used in which a highly accurate 3D description is swiftly generated (1–2 mm). The so-called point cloud can be used for visualisation, communication or measurement. Various modelling and simulation tools can be used to analyse and verify solutions by combining the point cloud with 3D models of new equipment and products, for example. Regular scanning of production enables a digital twin of its physical geometry to be created. This can be made easily available for all those who need it, including processors or suppliers. However, effective working methods are required to ensure the digital twin is accurate, which is a considerable challenge.