Paper titles:
Title 1: Deep learning-based 3D printer fault detection
(ICT Express - ICUFN)
Title 2: Deep learning-based fault prediction
Title 3: An inference time-efficient 3D printer fault detection using CNN
Title 1:
1. Improve the validation graph of my 4 pages paper
2. Changed the format (ICT Express Template)
Title 2:
1. Surveyed and study-related works
2. Compare conventional and machine learning methods
Title 3:
1. Searched and find the motivation in previous studies
2. Re-simulate fault prediction journals
1. Start writing my journal (Introduction)
2. Start writing my KICS paper (Introduction)
3. Study the paper and make ppt for my seminar
4. Search and study fault prediction in general and find motivation in previous studies
Implementation:
1. Resimulate previous fault prediction journals
3D Monitoring Project
1. Implemented LabVIEW integration in python (a simple function)
2. Searched and studied online tutorial for 3D printer control using LabVIEW + Python
3. Surveyed related papers
1. Implement LabVIEW integration in python
2. Search image processing related paper
3. Watch the online tutorial for LabVIEW integration in python for a 3D printer controller
1. Continue learning LabView
- Search for online tutorials
- attempt for hands-on implementation
- search how to integrate python and LabView
- attempt to integrate basic python codes with LabView
2. Search and review related papers
- python and LabView integration
- LabView and 3D printer integration
- Machine learning with the 3D printer
3. Learn more about machine learning and deep learning with Python
- Search for online tutorials
- implement what I learn
4. Start writing my journal paper
- Search a topic
- Search and review related papers
- Compare conventional and machine learning methods
5. Start writing my KICS paper
- Search and review related papers
- Compare conventional and machine learning methods
1. Publish two or three conference paper (Domestic and International)
2. Publish at least one international journal