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

位于温莎的福特汽车发动机工厂最近进行了重新装备，以生产用于福特f系列卡车的新发动机。发动机生产系统包含先进的机加工和装配线。这些复杂的系统在运行过程中会遇到故障和故障，导致延误，浪费宝贵的时间和资源，并可能破坏供应链。该项目旨在与福特合作，研究识别故障模式及其原因的智能方法，并利用数据分析、神经网络和深度学习方法，基于人工智能（AI）和机器学习（ML）开发恢复策略。福特已经在实施第四次工业革命（I4.0）智能制造技术，目前的研究项目将支持福特及其他公司制造工厂的数字化转型和智能化。加拿大的制造业为全国贡献了170万个全职高薪工作。制造业占加拿大GDP的10%以上。随着智能制造新技术的出现，计划中的研究有助于加拿大制造业在工业世界中具有竞争力。大、中、小型制造商都渴望在数字化和智能技术应用方面提高自己的能力，提高员工的技能/再培训，以获得收益并保持竞争力。拟议的研究合作也有望产生智能技术，并将为在工业4.0和人工智能在制造业的实际应用中培养高素质人才（HQP）创造重要机会。它将在制造业环境中提供有价值的知识和经验学习，在加拿大训练有素的hqp供不应求，并创造未来的就业机会。

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.