Grant: Alliance Grants

Quality control forms a critical task in manufacturing involving analysis of complex patterns to ensure that the consumers receive quality products, while also reducing product wastage due to erroneous rejection of otherwise good product. With the global smart manufacturing and intelligent automation market projected to more than double between 2021 to 2028, there is an urgent need to develop reliable machine learning models for production monitoring. While use of artificial intelligence (AI) and machine learning (ML) for quality control has been studied, there is a need to focus on high-throughput manufacturing units that operate under extremely low margin of error, where even a fraction of a percent improvement can lead to significant impacts on the environment as well as on the revenue. Moreover, changes in manufacturing processes and products over time can lead to significant loss of performance while the AI model adapts to the new data. To address these challenges, our partnership with Apple Canada Inc. will build AI-powered defect identification models for intelligent manufacturing which can adapt to changing environment and products, while leveraging the defect profiles observed in the past. Tackling high-impact problems at the cutting-edge of contemporary machine learning practice, the project will train HQP in high demand skills in AI/ML, specifically deep learning, and transfer learning on real-world problems. Furthermore, with Apple aiming to increase its research footprint in Canada, the collaboration will also directly generate exceptional employment opportunities for the HQPs and contribute to making Canada a leader in AI/ML technologies, at the forefront of the intelligent manufacturing revolution.