Grant: Applied Research and Development Grants - Level 1
Conestoga College Institute of Technology & Advanced Learning
$25,000.00
Prototyping an AI-powered robotic picker for sorting shredded aluminum
FY 2018-19
Summary
eCycle Solutions operates multiple asset recovery and electronics and electrical equipment recycling facilities*across Canada. eCycle Solutions is privately held, Canadian owned with over 400 employees and 300 metric*tonnes of daily processing capacity, with over 350,000 sq/ft of warehousing and processing space across all sites.*Traditionally, at Waste Electrical and Electronic Equipment (WEEE) recycling facilities, outdated waste electronics*are shredded in order to liberate their materials. The objective is to then separate these shredded pieces based*on their material type to produce pure commodities. To accomplish this, a variety of sorting technologies are used*to separate these materials, however, contamination is prevalent due to inefficiencies in these technologies. To*address this contamination, workers manually remove pieces from the material stream. This process is labourintensive,*time-consuming, monotonous, repetitive, and not cost effective.*Conestogas proposed solution for this project is to develop a pick-n-place robot as a mechanical picker, which*is capable of sorting shredded waste electronics utilizing a Convolutional Neural Network (CNN). The CNN will*""train"" the robot so that it will mimic the capability of the human operator and ""learn"" based on experience. This*will result in increased purity rates and processing speeds, and will enable much of the labour force to deployed to*other tasks, which will lead to reduced processing costs, and increased profitability.
Program
Applied Research and Development Grants - Level 1
Location
Ontario, Canada
Recipient Type
Other
Type
Grant
Source
NSERC's Awards Data
As published
Application id
531437-2018
Name nom
Fennessy, Barbara
Department département
Conestoga's Applied Research and Innovation
Organization id
22147
Institution établissement
Conestoga College Institute of Technology & Advanced Learning
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
25000
Program id
CARD1
Program name en
Applied Research and Development Grants - Level 1
Program name fr
Subventions de recherche et développement appliquée - niveau 1
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1561
Committee name en
Applied Research and Development Grants
Committee name fr
Subventions de recherche et développement appliquée
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
1504
Research subject group en
Environmental engineering
Research subject group fr
Génie de l'environnement
Research subject en
Solid waste management (including radioactivity)
Research subject fr
Gestion des déchets dangereux (y compris radioactivité)
Partie
1
Nb partie
1
Application title
Prototyping an AI-powered robotic picker for sorting shredded aluminum
Keyword
NSERC
Application summary
eCycle Solutions operates multiple asset recovery and electronics and electrical equipment recycling facilities*across Canada. eCycle Solutions is privately held, Canadian owned with over 400 employees and 300 metric*tonnes of daily processing capacity, with over 350,000 sq/ft of warehousing and processing space across all sites.*Traditionally, at Waste Electrical and Electronic Equipment (WEEE) recycling facilities, outdated waste electronics*are shredded in order to liberate their materials. The objective is to then separate these shredded pieces based*on their material type to produce pure commodities. To accomplish this, a variety of sorting technologies are used*to separate these materials, however, contamination is prevalent due to inefficiencies in these technologies. To*address this contamination, workers manually remove pieces from the material stream. This process is labourintensive,*time-consuming, monotonous, repetitive, and not cost effective.*Conestogas proposed solution for this project is to develop a pick-n-place robot as a mechanical picker, which*is capable of sorting shredded waste electronics utilizing a Convolutional Neural Network (CNN). The CNN will*""train"" the robot so that it will mimic the capability of the human operator and ""learn"" based on experience. This*will result in increased purity rates and processing speeds, and will enable much of the labour force to deployed to*other tasks, which will lead to reduced processing costs, and increased profitability.