TWIN generator: AI-process to build a digital twin

Purpose and goal

The TWIN generator project aims to develop advanced AI solutions to create digital twins (DT) of industrial facilities. Using 3D scans and AI technologies, such as computer vision and generative design, the project aims to automate the process of documenting and creating DT for facilities, especially those lacking digital documentation. The goal is to improve efficiency in industry by reducing time and cost for commissioning and maintenance and promoting greener industrial solutions.

Expected effects and result

- Opportunity for companies to quickly and cost-effectively implement digital twin technologies, even for the elderly facilities that lack extensive documentation and 3D models. - Prediction of maintenance needs to avoid downtime, increase efficiency, reduce costs, and optimize energy use and emissions. - Contributes to several of the global goals of the 2030 Agenda by improving the monitoring, servicing and management of industrial facilities, reducing energy consumption, increasing efficiency and reducing environmental impact.

Planned approach and implementation

The project is divided into three parts. The first focuses on development of computer vision techniques to be able to identify components from a 3D scanned point cloud. A critical question is how a point cloud can be efficiently matched against an unorganized amount of 3D data. The second part deals with automatically generating 3D models in cases when specific models are missing. Third part is how the information and 3D models can be effectively combined to build interactive digital twins. The facility Zero Emission Center will be used to demonstrate the developed techniques.