| Group |
2020-19 |
Status |
completed |
| Title |
Automatic Optical Inspection (AOI) |
| Supervisor |
Wahab Hamou-Lhadj |
| Description |
Automatic Optical Inspection (AOI) is the process of automated visual inspection of a printed circuit board (PCB) and/or an assembly that aims to identify faults early in the manufacturing process.
In this project, the students will create an AOI system with a pre-defined inspection scope
that would come at significantly lower cost than the more advanced commercially available solutions.
The target group of this project are small businesses that are manufacturing low quantities of boards and would benefit from a low-cost automation of the inspection process.
The project requires skills in various areas including machine learning, signal processing, software development, electrical engineering, and possibly mechanical engineering at some extent.
|
| Requirement |
The students should have knowledge (or willing to acquire knowledge) in the following areas: software programming, signal processing, machine learning, electrical engineering, hardware design. |
| Tools |
The project requires the use of the following software/hardware tools:
Camera
PC
Python
OpenCV
Dlib
Access to a 3D printer and/or a milling machine
Multimeter
|
| Number of Students |
4 |
| Students |
Michael Lesko Krleza,
Chris Davies,
Gabriel Karras,
Ion Balan,
|
| Comments: |
wahab.hamou-lhadj@concordia.ca |
| Links: |
|