The PRECINET feasibility study is aimed at testing the approach of using artificial intelligence to detect pollution (grease and loose parts) in industrial piping, along with the possibility of incorporating AI into a video endoscope available in the market.
The project involved the creation of a tool that can measure the interaction between a human hand and the environment.
It led to the development of the multiphysics instrumentation of a glove and tests in operating conditions.
As part of the RACOSOUD project, high-performance tools for data processing, including those incorporating AI-based models, have been used in order to use the physical measurements collected during the welding process. The study was devoted to the resistance welding process.
The AUTO RX feasibility study is aimed at testing several approaches for putting in place a system that uses artificial intelligence to assist decisions based on digital X-ray images. The study compares two techniques adapted to limited image bases with a standard approach.
Designed to address the need for a collaborative robot that can handle heavier loads than those available in the market, SybXL is an innovative heavy payload (35 kg) cobot that is the result of collaboration between CEA-List and industry. While not all the challenges relating to the design of such a cobot have been met to date, major scientific advances have been made, such as a double-acting cable cylinder which synchronises the axes or a balancing system with multiple springs.
Comparative study of the players of Industry 4.0.
