Grant: Alliance Grants
École de technologie supérieure
$40,422.00
Development of optimal joint strategies and an intelligent decision model for lockout/tagout, maintenance and production in a smart manufacturing context
FY 2024-25
Summary
This four-year research project aims to develop a strategic and operational implementation plan for an intelligent approach to integrate safety management processes of production systems in factories. Such safety protocol management is needed for e.g. equipment maintenance operations in manufacturing plants. The involved graduate students will develop novel safety management strategies using Artificial Intelligence, based on available, practical data. Two industrial partners in the field of manufacturing and safety management, Conformit and Cascades, will be involved in this study. Intelligent instruction and decision tools for joint safety management, production and maintenance optimization will be developed, implemented and validated using Cascades cardboard and paper plant as testbed.
The strong involvement of experts at both industrial partners, their vast client portfolio and strategic planning will allow to efficiently transfer the knowledge achieved by this research project to other manufacturing plants across Canada and beyond to increase the safety of workers.
Program
Alliance Grants
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
577072-2022
Name nom
Hof, Lucas LA
Department département
Génie mécanique
Organization id
53
Institution établissement
École de technologie supérieure
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2022
Award amount
40422
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
1604
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Manufacturing
Research subject fr
Fabrication
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
Development of optimal joint strategies and an intelligent decision model for lockout/tagout, maintenance and production in a smart manufacturing context
Keywords
advanced manufacturing systems; artificial intelligence; decision support tool; hazardous energy control; industry 4.0; intelligent process monitoring; joint optimization policies; lockout/tagout (loto); predictive maintenance; smart manufacturing
Application summary
This four-year research project aims to develop a strategic and operational implementation plan for an intelligent approach to integrate safety management processes of production systems in factories. Such safety protocol management is needed for e.g. equipment maintenance operations in manufacturing plants. The involved graduate students will develop novel safety management strategies using Artificial Intelligence, based on available, practical data. Two industrial partners in the field of manufacturing and safety management, Conformit and Cascades, will be involved in this study. Intelligent instruction and decision tools for joint safety management, production and maintenance optimization will be developed, implemented and validated using Cascades cardboard and paper plant as testbed.
The strong involvement of experts at both industrial partners, their vast client portfolio and strategic planning will allow to efficiently transfer the knowledge achieved by this research project to other manufacturing plants across Canada and beyond to increase the safety of workers.
