Faults Detection and Recovery in Automobile Engines Machining and Assembly Systems Using AI and Machine Learning

点击翻译按钮获取中文摘要

The Ford automobile engine plant in Windsor was re-tooled recently to build new engines used in Ford's F-series trucks. The engine production system contains advanced machining and assembly lines. These complex systems encounter faults and breakdowns during operation, which result in delays and waste of valuable time and resources and could disrupt the supply chain. This project aims to research, in cooperation with Ford, smart methods for recognizing patterns of faults and their causes and develop recovery strategies based on artificial intelligence (AI) and Machine Learning (ML) using data analytics, neural networks, and deep learning methods. Ford is already implementing fourth industrial revolution (I4.0) smart manufacturing technologies and the current research project will support the digital transformation and intelligence of manufacturing plants at Ford and beyond. The manufacturing sector in Canada contributes up to 1.7 million full-time, well-paying jobs all across the country. Manufacturing represents more than 10% of Canada's GDP. The planned research helps Canada's manufacturing sector be competitive with the industrial world as new enabling technologies of intelligent manufacturing emerge. Large, medium, and small manufacturers are keen to improve their competency and upskilling/reskilling their workforce in digitalization and applications of smart technologies to reap their benefits and remain competitive. The proposed research collaboration is also expected to produce intelligent technologies and will createsignificant opportunities for training highly qualified personnel (HQP) in real-world applications of I4.0 and AI in manufacturing. It will provide valuable knowledge and experiential learning in a manufacturingenvironment, where trained HQPs are in short supply in Canada, and create future employment opportunities.