picture about auto digital twins
Digital Twin

Auto Digital Twins: facilitating the implementation of digital twins in industry

Innovation that improves productivity in many sectors

  • Project file code: AEI-010500-2022b-47
  • Project funding agencies: Ministry of Industry, Trade, and Tourism of the Government of Spain, AEI Cluster, Next Generation Program of the European Union, and Recovery, Transformation, and Resilience Plan

Initiative financed by the Ministry of Industry, Trade, and Tourism within the program of support to the AEI to contribute to the improvement of the competitiveness of the Spanish industry, and with the support of the European Union through the Recovery, Transformation and Resilience Plan

logo de proyecto financiado por la unión europea
logo del plan de recuperación transformación y resiliencia
Client
Industrial research and SMEs
Industry
Research
Services
AI / Augmented reality
Technology
Evergine / Point Cloud
A consortium including Plain Concepts, Deuser, and TycheTools will develop this project to advance a technology now limited by the barriers to entry of digitization, the lack of tools to automate data tagging, and the difficulty of managing data.
picture about auto digital twins and factories
01

Goal

Create a tool that drives the implementation of beautiful digital twins in the industry. Auto Digital Twins is an ambitious project that, through the generation of 3D models and massive automatic labeling, seeks to promote this technology that makes companies more productive and eliminates the need for physical models.

Thus, the aim of the project's three phases is to facilitate the labeling of 3D elements (so far of the high cost) that are part of industrial infrastructures.

Phase 1: Point Cloud to 3D automation. The Spot robot will be used with the Leica sensor to scan an industrial facility, and a point cloud will be obtained. Artificial intelligence algorithms will be implemented on point clouds to recognize complex objects, and once identified, a 3D model will be accepted.

Phase 2: synthetic data generator. Given the lack of data to recognize objects, a synthetic generator capable of creating massively labeled virtual scenarios will be developed, and artificial intelligence models will be trained with them.

Phase 3: advanced capabilities. In this phase, the aim is for the system to be able to recognize the materials of objects (PVC, aluminum, steel, iron, and rubber) from texture detection, as well as their behavior (for example, the direction and speed of movement of a conveyor belt roller).

picture about evergine and auto digital twins
02

Impact

Auto Digital Twins seeks to provide Spanish SMEs in the industrial sector with a tool that automates the data capture process. In this way, it accelerates the digitization and modernization of corporate infrastructures and continues to advance in the new paradigm of Industry 4.0.

Evergine, Plain Concepts' 3D industrial graphics engine for professional projects, will be very useful in driving this project. Evergine stands out for this project for its animation system that links the object, skeleton, and morphing animations of 3D elements; it's photometric lighting; the visualization of 3D particles to improve the visual effects of applications; or the simulation of movements such as collisions.

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