Course Schedule
*The deadline for submission of assignments is one week from the date of posting.
|
Week
|
Subjects
|
Exercise
|
Assignments*
|
|
1
|
01. Introduction
|
01. Installation of Python and Pycharm
|
LR 1
|
|
2
|
02. Smart manufacturing
|
02. File load/save/plot/filtering
|
HW1
|
|
3
|
03. Sensors for smart manufacturing
|
03. Data acquisition
|
HW2
|
|
4
|
04. Machine vision
|
04. Feature extraction
|
HW3
|
|
5
|
05. Application of machine vision in manufacturing
|
05. Feature-based signal classification using ML
|
HW4
|
|
6
|
Exam 1
|
|
LR 2
|
|
7
|
06. Statistical data analytics on sensor data
|
06. CNN-based signal classification
|
HW5
|
|
8
|
07. Modeling manufacturing processes
|
07. Image load/save/plot/filtering
|
HW6
|
|
9
|
08. AI and predictive analytics
|
08. LCD defect detection using pattern comparison
|
HW7
|
|
10
|
09. Prognostics
|
08. LCD defect detection using FFT
|
HW8
|
|
11
|
Exam 2
|
|
LR 3
|
|
12
|
10. Sensors to monitor LPBF process
|
10. Feature-based pore detection
|
HW9
|
|
13
|
11. Machine vision techniques to monitor LPBF process
|
11. CNN-based pore detection
|
HW10
|
|
14
|
12. AI techniques to monitor LPBF process
|
Present Project Proposal
|
HW11
|
|
15
|
Project Presentations (10:30am-12:30pm on 12/5)
|
Present Project (Final)
|
|
|
16
|
|
|
|