Papers

Paper titles:
Title 1: Deep learning-based 3D printer fault detection
- April 29, 2021: Submitted to ICUFN

Title 2: Deep learning-based fault prediction

Title 3: An inference time-efficient 3D printer fault detection using CNN
- KICS paper

Last Week's Progress

Title 1:
1. Waiting for the result

Title 2:
1. Searched and study-related works
Find motivation in previous studies

Title 3:
1. Introduction
2. Re-simulate
3. Collecting inference time of the other methods

This Week Todo's

Title 1:
1. Wait for the result

Title 2:
1. Study fault detection and prediction in general
2. Re-simulated fault prediction
3. Find motivation of the previous studies

Title 3:
1. Introduction
2. Re-simulate and collect inference time
3. Finish and submit on time

Project Progress

3D Monitoring Project

Last Week's Project

1. Search anomaly detection
2. Search and study fault diagnosis
3. Watched and study online tutorial for the 3D controller
4. Collect data (image and video) for the 3D printer

This Week's Project

1. Continue collecting data from the 3D printer
2. Survey related works
3. Actual test in FDM printer

Implementation:
1. Re-simulate fault prediction

Monthly Goals

1. Search and review related papers
- python and LabView integration
- Controlling the 3D printer
- Machine learning with the 3D printer
- Fault prediction

2. Learn more about machine learning and deep learning with Python
- Study for online tutorials
- Re-simulate what I learn

3. Journal paper
- Search and review related works
- Compare conventional and machine learning methods
- Start writing my journal

4. KICS paper
- Search and review related papers
- Compare conventional and machine learning methods
- Finish my paper on time

Annual Goals

1. Publish two or three conference paper (Domestic and International)
2. Publish at least one international journal