Smart Battery Manufacturing Research and Development Assistant based on Augmented Reality Technology and powered with the ARTISTIC project Computational Models

ERC (European Research Council)HORIZON-ERC-POCID: 101069244
EC Contribution
€1,500
Consortium Size
1 orgs
Start Year
2022
Summary

The SMARTISTIC project aims at developing and demonstrating a first prototype of a smart and interactive Augmented Reality (AR) software designed to assist in the decision-making of battery scientists, engineers and operators while they are working in electrode formulation and manufacturing in laboratories or in production lines. The software will be usable from tablets and AR glasses by touch gesture and hand gesture respectively. The software will blend holograms with the real world manufacturing equipment. Such holograms will be powered with the unique physical and machine learning (ML) models developed and validated experimentally in my ERC CoG ARTISTIC project and which can predict the impact of manufacturing parameters on the final electrode properties. By interacting with the holograms and without the need of programming skills, a user can in real-time create databases from her/his ongoing experiments, launch computations for analysis of experimental results, or request ML predictions about the impact of her/his intended formulation and manufacturing process on the electrode properties. She/he can also use the software to analyze possible deviations between the experimental results and the predictions to identify more easily factors that could explain unexpected experimental results. The prototype will be developed by accounting for the users' needs and from the observation of work situations. Once developed, we will perform tests and demonstrations to assess the software usability and ergonomics for its improvement while used in real situations. They will be carried out in the battery manufacturing platform of our laboratory and in companies and in institutes which already manifested interest in our proof of concept. The assessments will permit improving the software to ensure its wide acceptance. We will also analyze the IP, technology transfer and market opportunities to valorize the intended software, also thanks to networking activities.

Consortium (1)

Project Results (5)

Source: CORDIS, the EU research results database.

Publications (5)
Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction
Advanced Energy Materials· 2024DOI
Diego E. Galvez-Aranda, Tan Le Dinh, Utkarsh Vijay, Franco M. Zanotto, Alejandro A. Franco
Breaking down the Barriers between the Digital and the Real: Mixed Reality applied to battery manufacturing R&D and Training
ChemRxiv (preprint)· 2023DOI
Lucie Denisart, Javier F. Troncoso, Emilie Loup-Escande, Alejandro A. Franco
Combining Virtual Reality with Mixed Reality for Efficient Training in Battery Manufacturing
Batteries & Supercaps· 2023DOI
Lucie Denisart; Diana Zapata‐Dominguez; Xavier David; Aubin Leclere; Romain Lelong; Chaoyue Liu; Jiahui Xu; Emilie Loup‐Escande; Alejandro A. Franco
Computational Model for Predicting Particle Fracture During Electrode Calendering
Batteries & Supercaps· 2023DOI
Jiahui Xu; Brayan Paredes‐Goyes; Zeliang Su; Mario Scheel; Timm Weitkamp; Arnaud Demortière; Alejandro A. Franco
Mesoscopic Model of Extrusion during Solvent-Free Li-Ion Battery Electrode Manufacturing
Batteries & Supercaps· 2023DOI
Brayan Paredes-Goyes; Franco Zanotto; Victor Boudeville; Sylvie Grugeon; Loic Dupont; Alejandro A. Franco