In-process adaptive defect correction for robotic hybrid LAAM

Summary

On-machine laser scanning and in-process adaptive dimension deviation (surface defect) correction strategy

• On-machine laser scanning measurement to generate point cloud data
• Point cloud processing
• Rapid surface defect identification
• Repair AM part surface defect based on point cloud data
• Automatic repairing AM toolpath generation

Currently in development:

• Localized surface defect identification
• Surface defect removal by robotic milling process
• Various stratagies for generating robotic milling toolpath pattern
• Robotic milling toolpath selection (decision-making)
• Hybrid process planning (surface defect repair by AM or SM)

Introduction

This is the code repository for a series of projects related to In-process adaptive defect correction for robotic hybrid LAAM

Table of Contents

• Rapid surface defect identification
• In-process adaptive dimension correction strategy for LAAM

Rapid surface defect identification

Citation

If you find our work useful in your research, please cite our paper:

Chen, L., Yao, X., Xu, P., Moon, S.K., Bi, G., 2021. Rapid surface defect identification for additive manufacturing with in-situ point cloud processing and machine learning. Virtual and Physical Prototyping 16, 50–67. https://doi.org/10.1080/17452759.2020.1832695

In-process adaptive dimension correction strategy for LAAM

paper entitled "In-process adaptive dimension correction strategy for laser aided additive manufacturing using laser line scanning"

Citation

If you find our work useful in your research, please cite our paper:

[Robotic milling toolpath generation]

• Currently under development
• Preliminary results: