Course Schedule
*The deadline for submission of assignments is one week from the date of posting.
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Week
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Subjects
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Exercise
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Assignments*
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1
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01 Introduction to smart manufacturing
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01 Installation of Python and Pycharm
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LR 1
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2
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02 Smart Manufacturing
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02. File load/save/plot/filtering
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HW1
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3
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03 Sensors for smart manufacturing
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03. Data acquisition
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HW2
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4
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04 Machine vision
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04. Feature extraction
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HW3
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5
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05 Application of machine vision in manufacturing
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05. Feature-based signal classification using ML
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HW4
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6
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Exam 1
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LR 2
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|
7
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06 Statistical data analytics on sensor data
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06. CNN-based signal classification
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HW5
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8
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07 Modeling manufacturing processes
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07. Image load/save/plot/filtering
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HW6
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|
9
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08 AI and predictive analytics
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08. LCD defect detection using pattern comparison
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HW7
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10
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09 Prognostics
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08. LCD defect detection using FFT
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HW8
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11
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Exam 2
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LR 3
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12
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10 Sensors to monitor LPBF process
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10. Feature-based pore detection
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HW9
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13
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11 Machine vision techniques for LPBF
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11. CNN-based pore detection
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HW10
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14
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12 AI techniques to process LPBF sensor data
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Project updates 1
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HW11
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15
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13 Data-driven process control of LPBF
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Project updates 2
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HW12
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16
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Project Presentations
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