Grant: Collaborative Research and Development Grants
University of Ontario Institute of Technology
$22,333.00
Coordinate Metrology and Defected Zone Detection for High Contrasting Surfaces
FY 2019-20
Summary
The research collaboration between the research teams from the University of Ontario Institute of Technology (UOIT) led by professor Barari and Bluewrist Inc. started by a NSERC Engage funded project on reducing noises in laser scanning of planar surfaces. The results of the Engage project have been very promising and satisfactory. Bluewrist is expanding its products and activities in the field of automated and robotics inspection and is accepting more challenging task serving various industries. Using the achievements of the NSERC Engage project and considering the new technical challenges in the company, this CRD proposal is prepared. The proposal focuses on solving two complex technical problems in automated laser scanning of the products. The developed solutions are aimed to represent a high level of flexibility in measuring contrasting surfaces with regional characteristics in light reflection, and also will be able to detect and specify the defected zones in the measured surfaces. Bluewrist Inc. is a Canadian - based company focused on automated measurement, production quality control, robotics, and machine vision. Bluewrist's main products include in-line dimensional measurement system, robotic guidance system, automation engine, and communication software. Bluewrist has focused on industrial metrology for advanced manufacturing, and data collection methods for digital manufacturing and Industry 4.0 solutions. In this research collaboration Dr. Barari's research team work collaboratively with Bluewrist's experts to develop robust and reliable solution for laser scanning of high contrasting surfaces and determination of the defected zone using the laser scanning 3D data points. The project's objectives are selected following a term of NSERC Engage project and according to the actual needs of company in conducting high level international projects. This research results in training of highly qualified personnel in digital manufacturing and inspection. It also results in improving the productivity and quality in various Canadian manufacturing industries, including automotive part assembly, material handling, inline dimensional inspection, and industrial robotics.
Program
Collaborative Research and Development Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
531197-2018
Name nom
Barari, Ahmad
Department département
Automotive, Mechanical and Manufacturing Engineering
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2018
Award amount
22333
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
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
1702
Research subject group en
Design and manufacturing
Research subject group fr
Conception et fabrication
Research subject en
Advanced manufacturing
Research subject fr
Méthodes de fabrication avancées
Installment
inst:2 - 2
Partie
2
Nb partie
2
Application title
Coordinate Metrology and Defected Zone Detection for High Contrasting Surfaces
Keyword
NSERC
Application summary
The research collaboration between the research teams from the University of Ontario Institute of Technology (UOIT) led by professor Barari and Bluewrist Inc. started by a NSERC Engage funded project on reducing noises in laser scanning of planar surfaces. The results of the Engage project have been very promising and satisfactory. Bluewrist is expanding its products and activities in the field of automated and robotics inspection and is accepting more challenging task serving various industries. Using the achievements of the NSERC Engage project and considering the new technical challenges in the company, this CRD proposal is prepared. The proposal focuses on solving two complex technical problems in automated laser scanning of the products. The developed solutions are aimed to represent a high level of flexibility in measuring contrasting surfaces with regional characteristics in light reflection, and also will be able to detect and specify the defected zones in the measured surfaces. Bluewrist Inc. is a Canadian - based company focused on automated measurement, production quality control, robotics, and machine vision. Bluewrist's main products include in-line dimensional measurement system, robotic guidance system, automation engine, and communication software. Bluewrist has focused on industrial metrology for advanced manufacturing, and data collection methods for digital manufacturing and Industry 4.0 solutions. In this research collaboration Dr. Barari's research team work collaboratively with Bluewrist's experts to develop robust and reliable solution for laser scanning of high contrasting surfaces and determination of the defected zone using the laser scanning 3D data points. The project's objectives are selected following a term of NSERC Engage project and according to the actual needs of company in conducting high level international projects. This research results in training of highly qualified personnel in digital manufacturing and inspection. It also results in improving the productivity and quality in various Canadian manufacturing industries, including automotive part assembly, material handling, inline dimensional inspection, and industrial robotics.
