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Grant: Alliance Grants

University of Regina

$30,000.00

Real-time Machine State Identification using Machine Learning in Open-pit Mining

EF 2024-25

Résumé
Within the specific context of open-pit mining in Canada, RIGID ROBOTICS stands at the forefront of research and development in new data analytics for sustainable and optimized mining practices. In this field, sensors play a pivotal role in optimizing operational efficiency, safety, and environmental sustainability. Various sensor modalities have been developed and are poised for strategic deployment to enhance different facets of mining operations. The research focus is directed towards three sensor modalities: Environmental Sensors for continuous monitoring of air and water quality, as well as noise levels, ensuring compliance with environmental regulations; Equipment Health Monitoring Sensors for real-time monitoring of machinery health, enabling predictive maintenance to reduce downtime and enhance overall operational reliability; and Vehicles and Fleet Management Sensors for improved navigation, collision avoidance, and efficient fleet management within the mining site. The objective is to concentrate on defining the State Machine associated with different operational points in RIGID ROBOTICS and undertaking process optimization through the identification of optimal state machine transitions based on factors such as cost, power consumption, safety, machine downtimes, and overall operational mission times.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
591160-2023
Name nom
Mehrandezh, Mehran M
Department département
Engineering and Applied Science, Faculty of
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
30000
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
202
Area of application group en
Natural resources (economic aspects)
Area of application group fr
Ressources naturelles (aspects économiques)
Area of application en
Mineral resources ( prospecting, exploration, mining, extraction, processing)
Area of application fr
Ressources minérales (prospection, exploration, mines, extraction et préparation)
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
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
Real-time Machine State Identification using Machine Learning in Open-pit Mining
Keywords
ai; automation in mining; behavior trees; computer vision; digitized open-pit mining; heavy machineries; machine learning; mechatronics; mining; state machines
Application summary
Within the specific context of open-pit mining in Canada, RIGID ROBOTICS stands at the forefront of research and development in new data analytics for sustainable and optimized mining practices. In this field, sensors play a pivotal role in optimizing operational efficiency, safety, and environmental sustainability. Various sensor modalities have been developed and are poised for strategic deployment to enhance different facets of mining operations. The research focus is directed towards three sensor modalities: Environmental Sensors for continuous monitoring of air and water quality, as well as noise levels, ensuring compliance with environmental regulations; Equipment Health Monitoring Sensors for real-time monitoring of machinery health, enabling predictive maintenance to reduce downtime and enhance overall operational reliability; and Vehicles and Fleet Management Sensors for improved navigation, collision avoidance, and efficient fleet management within the mining site. The objective is to concentrate on defining the State Machine associated with different operational points in RIGID ROBOTICS and undertaking process optimization through the identification of optimal state machine transitions based on factors such as cost, power consumption, safety, machine downtimes, and overall operational mission times.