Tracking Ongoing Production in a Factory Business

• Problem: Lack of visibility on ongoing production – loss of productivity
• Objective: Identify and locate bins of screws at all times
• Proposed Solution: Passive UHF RFID technologies, initial testing in progress
• Technology Partners: To be confirmed Business
• Partners: VISQUE
• SDG Impact: Catalyst for the adoption of digital technologies in the manufacturing sector – Student training

Autonomous Robotics Using Artificial Intelligence for High-Diversity Production

• Challenges for SMEs dealing with high diversity in creating a fully automated production flow to compensate for labor shortages and reduce production costs to remain competitive globally.
• The objective is to create innovative solutions to address current and future manufacturing issues in the context of Industry X.0.
• The proposed solution is to generate robot programs using AI to perform tasks with high diversity.
• Impact: Automation of painting lines in the industry and commercialization of a product by Cadence and NeuroBotIA.
• Concordia, Prof. Rolf Wuthrich, Students, Soha Kabir and Zhaohan Zheng
• ÉTS, Prof. Lucas Hoff, Giuseppe Di Labbio, Jean-Pierre Kenné, Student, Rafael Brunet

Improvement of Planning and Assembly Processes for Cleanroom Walls

• Business Problem: Mecart manufactures cleanrooms and modular steel buildings. Manufacturing efficiency is generally linked to effective production planning and scheduling. This project is driven by the need to automatically schedule activities while allowing users to reschedule certain tasks without compromising the validity of the solution.
• Project Objective: Develop a tool for efficient (optimal resource use) and agile (providing good predictability and the ability to adjust based on contingencies) tactical planning. Implement a non-invasive augmented reality system to assist operators during assembly stages.
• Proposed Solution: In the first subproject, an automatic scheduling system with a constraint programming model and a Manufacturing Information System (MIS) is proposed to maintain the validity of the plan, along with a user interface to enhance the user experience using human-machine interaction and user experience (UX) concepts. In the second subproject, a non-invasive augmented reality system is implemented to assist welders/assemblers through real-time optimization.
• Partners: MECART
• SDG Impact: Student training, providing a solution to a common issue faced by many companies.
• Professors and Students Involved: Jonathan Gaudreault, Maha Ben Ali, Éloise Prévot, Ali Fradi, Jean-Thomas Sexton, Michael Morin, Marc-André Ménard, Ludwig Dumetz

Predictive Health Management System for Drones

• Business Problem: The unknown health status of drone components poses risks and costs.
• Project Objective: To monitor the health status and predict the remaining lifespan of drone components.
  Proposed Solution: Health prediction for batteries and motors based on machine learning.
• Partners: Vozwin Inc., McGill University, and Université de Sherbrooke
• SDG Impact: A platform for intelligent maintenance and operations planning.
• Professors: Yaoyao Fiona Zhao, Elaine Mosconi