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

Ford is applying Industry 4.0 smart manufacturing technologies in its re-tooled and new plants in Canada. This project aims to research, in cooperation with Ford, intelligent methods for recognizing patterns of machines 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. It will also investigate the contribution of workers-automation interactions to faults occurrence using data, and minimizing, and discovering possible correlations or trends. Manufacturers are keen to improve their competency and upskill/reskill their workforce in digitalization and applications of intelligent technologies to reap the benefits and remain competitive. Nine Highly Qualified Personnel (HQP) will be provided valuable knowledge and experiential learning experiences in a real manufacturing environment. The proposed industry-academia research collaboration is expected to produce intelligent technologies and digital twins (DT) products that could be commercialized and used in Ford factories and many other industries.

Faculty Supervisor:

Waguih ElMaraghy;Hoda ElMaraghy

Student:

Partner:

Ford Motor Company

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Windsor

Program: