Sectors
Digital transformation in manufacturing and process industry
Services
Research and Development under Contract
Departments
Computer Vision, Interaction and Graphics
Competences
Artificial intelligence, machine learning, and decision support systems
Computer vision and image processing
FRAMEWORK
The Augmanity project aims to address some of the main current challenges for the industry, taking into account the following parameters:
- Develop relevant technologies that make industrial workplaces more attractive in the future
- Optimize the definition of work tasks in order to minimize or eliminate health problems arising from intensive work, improving ergonomics
- Reduce monotonous activities and eliminate demotivation associated with “junk activities”
- Develop technologies suitable for a new workforce that is more prepared for the new digitalization paradigm
- Use intelligent tools to measure or promote employee performance, motivation and appreciation
- Make the most of the integration of cyber-physical systems and ultra-connectivity in the industrial value chain
- Meeting these challenges considering energy efficiency, green and smart industries in the future
PROPOSED SOLUTIONS
- Develop smart and interactive devices
- Create external assistance systems, such as exoskeletons adapted to relevant activities
- Apply artificial vision to anticipate internal logistics traffic congestion, optimizing routes, ensuring that the operator has an optimized route or one that can be done automatically
- Develop technologies, based on Augmented and Mixed Reality, with a view to improving the way employees operate and solve problems
- Create Human Resources platforms, with different data sources combined to measure the performance, motivation and appreciation of employees
- Using IIoT/5G technology to connect networks of sensors and equipment on assembly lines
CCG/ZGDV CONTRIBUTION
The CVIG Department represents the CCG/ZGDV in this project, through automatic optical inspection applied to the company AAPICO (partner of this project).
This technology involves 2D cameras to identify image-based defects in automotive parts and 3D cameras to measure the correct sizing of the part:
- Software prototype for detecting dimensional and surface defects in cast iron parts
- DL model container for segmenting and detecting surface defects in cast iron parts
- 3D alignment algorithms to detect dimensional defects in point clouds of cast iron parts