FONCER – SDG Innovation Network

Program Overview

Master’s, PhD, and undergraduate internship

The originality of the proposed training is based on the exceptional environment offered to students. The universities will have operational factory-laboratories on their premises. Funded by the Canada Foundation for Innovation (CFI), these factories enable the actual manufacturing of goods using cutting-edge technologies compared to the industry. They will be operated by student teams. This training program is led by Université Laval’s Lab-Usine, which plays a central role in the implementation and coordination of activities.

In these factory-laboratories, research teams will develop and experiment with systems for design, configuration, manufacturing, and production control. Each student research project will be associated with a partner company and will aim to address a complex digital transformation issue, previously identified with the company. The solution will first be developed and tested within the training factory, then deployed with the student at the partner company. The skills and leadership developed by these students will make them the change agents needed by the manufacturing industry to drive its digital transition. Additionally, management science students will intervene transversally within these factories and with industrial partners to establish best practices and success factors for digital transformation.

Scientific and technical objectives

The training program aims to address the technological challenges of the manufacturing sector, particularly the transition to the fourth-generation manufacturing systems. These systems enable the design and production of customized products at costs comparable to mass production. This includes automated engineering based on artificial intelligence and mathematical models, as well as self-reconfigurable cyber-physical production systems with automatic production launch (real-time automated operations planning, monitoring, assisted control, augmented reality, etc.). Each student research project is associated with an industry partner and aims to address a complex digital transformation challenge previously identified with the company. The solution is first developed and tested within the training factory, then deployed by the student at the partner’s site.

Collaboration and professional development objectives

The training emphasizes the development of interdisciplinary skills and the strengthening of ties between academia and industry. Each student is paired with an industry partner for the entire duration of their program, promoting full immersion in real industrial challenges. This approach not only enables the development of concrete solutions but also trains professionals capable of leading digital transformation projects. Industrial internships, combined with experience gained in university factories, promote the acquisition of leadership, project management, and collaborative work skills, thereby preparing a new generation of engineers, scientists, and managers capable of meeting the needs of the manufacturing sector.

List of Ongoing and Completed Projects

Étudiantes/Étudiants	Responsable	Description
Abdelrahman Elsayed	Soumaya Yacout	Improving the maintenance of electric buses through Maintenance 4.0, 5G, and time synchronization.
Ahmed Daoud	Soumaya Yacout	Global condition monitoring and anomaly detection for Bombardier flights.
Charles Beaulieu	Jean‑François Lalonde	Automation of the electrostatic painting process in a dynamic industrial context with high diversity and low volume, using a robust method combining 6‑DOF object tracking and 3D alignment for 3D model coating and reconstruction.
Chloé Samuel	Jean‑François Audy	Improving the operational management of shared tools in a workshop using a digital twin.
Haitam Chaouki	Lucas Hof	Artificial intelligence modeling of electrostatic powder coating.
Hedir Oukassi	Soumaya Yacout	Digital twin for predictive maintenance of electric vehicles.
Jean-Thomas Sexton	Jonathan Gaudreault	Assisting welders and assemblers through real-time optimization and non-invasive augmented reality.
Lamyaa El Mahi	Soumaya Yacout	Local condition monitoring and anomaly detection for Bombardier flights.
Madina Ouali	Soumaya Yacout	Monitoring, analysis, and mitigation of anomalies and failures in electric vehicles (EVs): test bench experiments, data collection, and electric powertrain analysis.
Mehdi Lamouchi Chebbi	Tasseda Boukkeroub	Development of a digital twin of a critical piece of equipment for learning and predicting its future condition in order to enable proactive maintenance (LIFE case).
Omar Alkassas	Soumaya Yacout	Self-healing battery management system with online diagnostics and machine learning for electric vehicles.
Rafael Brunet	Lucas Hof	Development of an artificial intelligence model for powder coating application on a high‑diversity, low‑volume production line.
Soheila Kabir	Rolf Wuthrich	Improvement of glass micromachining through spark‑assisted chemical etching using software sensors based on artificial intelligence technologies.
Zhaohan Zheng	Rolf Wuthrich	Extension of glass micromachining by spark‑assisted chemical etching toward 6 degrees of freedom (6‑DOF).
Éloïse Prévost	Jonathan Gaudreault	Integrated software platform enabling the sharing of the same digital model at every stage of the manufacturing process.
Nan Jia Liang	Lucas Hof	Development of an intelligent fine‑sorting system at the end of the processing chain, combining artificial intelligence, vision, and robotics to improve recycling quality, reduce non‑recycled materials, and increase the operational efficiency of sorting centers facing current regulatory and industrial challenges.
Bechir Ben Daya	Jean‑François Audy	Develop and validate a decision‑oriented digital‑twin framework for port intralogistics to anticipate and mitigate bottlenecks, improve operational efficiency, and reduce carbon footprint through real‑time data exploitation and Industry 4.0 technologies.
Hadi Wehbi	Rolf Wuthrich	Integrate and demonstrate a connected, scalable, and distributed industrial software platform enabling real‑time collection, management, and exploitation of production data to accelerate the transition toward connected manufacturing in Québec.

Training Program for Leadership in Science and Engineering of Manufacturing Systems 4.0

CREATE direction

CREATE Program Committee

CREATE Operations Management Committee

List of Ongoing and Completed Projects