Grant: Alliance Grants
University of Windsor
$40,647.00
Faults Detection and Recovery in Automobile Engines Machining and Assembly Systems Using AI and Machine Learning
FY 2023-24
Summary
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.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
571096-2021
Name nom
ElMaraghy, Waguih WH
Department département
Mechanical, Automotive and Materials Engineering
Organization id
37
Institution établissement
University of Windsor
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2021
Award amount
40647
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
500
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Manufacturing processes and products
Area of application fr
Procédés et produits industriels
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Artificial intelligence (computer vision, use2603)
Research subject en
Intelligence artificielle
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Application title
Faults Detection and Recovery in Automobile Engines Machining and Assembly Systems Using AI and Machine Learning
Keyword
Adaptive Monitoring; Data Analytics; Digital Twin; Fault Detection; Industry 4.0; Intelligent Manufacturing; Machine Learning; Manufacturing Systems; Smart Manufacturing; Sustainable Manufacturing
Application summary
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.
