Papers

Paper titles:
Title 1: Deep learning-based 3D printer fault detection (ICUFN)
Title 2: Deep learning-based fault prediction
Title 3: An inference time-efficient 3D printer fault detection using CNN

Last Week's Progress

Title 1:
1. Submitted to ICUFN

Title 2:
1. Simulated fault detection
2. Studies related works and find motivation

Title 3:
1. Studied related works and find motivation on the paper
2. Started to write the introduction

This Week Todo's

1. Continue reading related papers
2. Study fault prediction in general
3. Continue writing my paper for KICS
4. Find motivation of the previous studies

Implementation:
1. Re-simulate fault prediction and compare conventional methods

Project Progress

3D Monitoring Project

Last Week's Project

1. Surveyed related works
2. Watched and studied online tutorial for LabVIEW integration in python
3. Studied online tutorial for the 3D printer controller

This Week's Project

1. Search different method to monitor the anomaly in the 3D printer
2. Study and implement 3D monitoring for anomaly detection
3. Collect the data (image) for the 3D printer

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