Grant: Alliance Grants
University of Toronto
$386,000.00
Additive Manufacturing of Automotive Tooling Components: Defect Reduction, Process Optimization and Powder Development
EF 2022-23
Résumé
The manufacturing sector, particularly the automotive industries, suffers from supply chain disruptions due to pandemic related restrictions. Metal additive manufacturing (AM), also known as 3D printing, is a transformative approach to industrial production that enables the creation of components directly from computer aided design and avoids conventional moulding and machining. AM offers new opportunities to reduce lead times associated with procurement, fabrication, repair, and ultimately delivery of process related tooling in the automotive sector. However, three key hurdles currently prevent the mass adoption of AM, particularly for the directed energy deposition (DED) process in the automotive industries: (1) The formation of flaws and defects, such as pores, cracks, residual stresses, lead to inconsistent product quality and reduce product cycle times; (2) Optimal process parameters (e.g., laser power, spot size, scanning speed, and pre-and post-processing conditions) are needed to identify each tooling material to ensure the consistency of product quality; (3) The high cost of powder feedstock impedes the DED process towards mass production. The partnership in this proposal involves four research groups at the University of Toronto and three partner organizations - Magna International, Exco Engineering and NRC-Mississauga. This collaborative team will develop a closed-loop controlled laser-based DED system that can sense and predict defects and correct processing parameters adaptively for various materials and part geometries with little human input, thereby significantly improving the quality of AM parts for production. The team will also investigate and optimize the pre-and post-processing conditions for the DED tool steels and develop low-cost feedstock powders for the DED process. The two-year research program will train two postdoctoral fellows, four graduate students, and six undergraduate students, leading to the establishment of several subsequent major research projects between the University of Toronto and the partner organizations. The new results and related techniques will be transferred to the partner organizations, benefiting the manufacturing industries in Canada.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
570708-2021
Name nom
Zou, Yu Y
Department département
Materials Science and Engineering
Organization id
31
Institution établissement
University of Toronto
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2021
Award amount
386000
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
2003
Research subject group en
Materials science and technology
Research subject group fr
Science et technologie des matériaux
Research subject en
Metallurgy
Research subject fr
Métallurgie
Installment
inst:2;3
Partie
2
Nb partie
3
Application title
Additive Manufacturing of Automotive Tooling Components: Defect Reduction, Process Optimization and Powder Development
Application summary
The manufacturing sector, particularly the automotive industries, suffers from supply chain disruptions due to pandemic related restrictions. Metal additive manufacturing (AM), also known as 3D printing, is a transformative approach to industrial production that enables the creation of components directly from computer aided design and avoids conventional moulding and machining. AM offers new opportunities to reduce lead times associated with procurement, fabrication, repair, and ultimately delivery of process related tooling in the automotive sector. However, three key hurdles currently prevent the mass adoption of AM, particularly for the directed energy deposition (DED) process in the automotive industries: (1) The formation of flaws and defects, such as pores, cracks, residual stresses, lead to inconsistent product quality and reduce product cycle times; (2) Optimal process parameters (e.g., laser power, spot size, scanning speed, and pre-and post-processing conditions) are needed to identify each tooling material to ensure the consistency of product quality; (3) The high cost of powder feedstock impedes the DED process towards mass production. The partnership in this proposal involves four research groups at the University of Toronto and three partner organizations - Magna International, Exco Engineering and NRC-Mississauga. This collaborative team will develop a closed-loop controlled laser-based DED system that can sense and predict defects and correct processing parameters adaptively for various materials and part geometries with little human input, thereby significantly improving the quality of AM parts for production. The team will also investigate and optimize the pre-and post-processing conditions for the DED tool steels and develop low-cost feedstock powders for the DED process. The two-year research program will train two postdoctoral fellows, four graduate students, and six undergraduate students, leading to the establishment of several subsequent major research projects between the University of Toronto and the partner organizations. The new results and related techniques will be transferred to the partner organizations, benefiting the manufacturing industries in Canada.
