Grant: Alliance Grants
University of Waterloo
$100,000.00
AI methods for CNC machines
FY 2024-25
Summary
The Canadian Machine Manufacturing industry is experiencing a boom due to reshoring, wherein industry move their manufacturing operations from international locations to Canada. The prediction is that the sector will see an annual growth of 5.5% in the coming years [1,2]. Although, the sector is on the verge of growth it faces some challenges such as lack of skilled labor, lack of labor with manufacturing knowledge and lack of youngsters vying to build a career in the domain. Such challenges could derail the potential growth.
Recent developments in technologies like Artificial Intelligence (AI) and Computer Vision offer a potential solution. The applicants have tested the feasibility of: developing an AI method that can sense anomalies on a metal cutting machine; developing a technique which can process a solid model of the part to be machined and identify machining features, tools required and other machining parameters automatically; and developing a camera based system that observes the machining process and detects anomalies. The current project is aimed at developing these methods and techniques and implementing them for use in the Canadian industry. With a boom of on-shoring in the offing, in the machine manufacturing sector, the above development will result in a strong growth - a great economic and competitive value to this Canadian sector.
This project will contribute to the training of 9 HQP: 3 PhD, 4 MASc and 1 undergraduate engineering co-ops. This work will be done jointly with Elliot Matsuura Canada Inc. and HURCO Inc.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
590456-2023
Name nom
Bedi, Sanjeev S
Department département
Mechanical Engineering and Mechatronics
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
100000
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
2109
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Mechanical systems and instrumentation
Research subject fr
Instrumentation et systèmes mécaniques
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
AI methods for CNC machines
Keywords
anomaly detection; chatter; cnc machines; feature recognition; graph neural networks; lstm neural networks; machining features; solid modelling; tool breakage; transfer learning
Application summary
The Canadian Machine Manufacturing industry is experiencing a boom due to reshoring, wherein industry move their manufacturing operations from international locations to Canada. The prediction is that the sector will see an annual growth of 5.5% in the coming years [1,2]. Although, the sector is on the verge of growth it faces some challenges such as lack of skilled labor, lack of labor with manufacturing knowledge and lack of youngsters vying to build a career in the domain. Such challenges could derail the potential growth.
Recent developments in technologies like Artificial Intelligence (AI) and Computer Vision offer a potential solution. The applicants have tested the feasibility of: developing an AI method that can sense anomalies on a metal cutting machine; developing a technique which can process a solid model of the part to be machined and identify machining features, tools required and other machining parameters automatically; and developing a camera based system that observes the machining process and detects anomalies. The current project is aimed at developing these methods and techniques and implementing them for use in the Canadian industry. With a boom of on-shoring in the offing, in the machine manufacturing sector, the above development will result in a strong growth - a great economic and competitive value to this Canadian sector.
This project will contribute to the training of 9 HQP: 3 PhD, 4 MASc and 1 undergraduate engineering co-ops. This work will be done jointly with Elliot Matsuura Canada Inc. and HURCO Inc.