- Part and Process Monitoring and Control for Additive Manufacturing
Awards
Author(s):
- Lequn Chen
Email:
- CHEN1189@e.ntu.edu.sg
Category:
- Engineering
Institution:
- Nanyang Technological University
Region:
- Asia
Winner Category:
- Highly Commended
Year:
- 2020
Abstract:
- Surface monitoring and melt pool control are two crucial methodologies for maintaining and improving quality in laser-aided additive manufacturing (LAAM). Surface monitoring is the fundamental step towards surface defects identification, while melt pool width control is to improve process robustness and stability to avoid defects during LAAM process. However, current surface monitoring technologies are unable to provide in-situ monitoring feedback, which makes it difficult to identify defects in the early stage; existing melt-pool control solutions are also not sufficient enough to maintain process robustness in strong melt pool dynamics and speed inconsistency situation for manufacturing bulky and complicated parts. This paper presents novel solutions to solve both problems. For surface monitoring, we present two different vision-based surface monitoring devices integrated into a robot-based LAAM system, with in-situ point cloud processing capability: one using low-cost CMOS camera with a 2D laser profiler while the other one using high accuracy micro-epsilon sensor. During the LAAM process, both devices are capable of automatically extracting point cloud data of the fabricated part surface regularly without process intermittence. For melt-pool control, we introduce a new design of an adaptive PID controller with automatic gain adjustment to deal with uncertainties such as speed inconsistency situation. Multiprocessing programs are used when executing the proposed monitoring and control system. Experimental results of two surface monitoring devices and simulation results for the adaptive PID controller are presented to verify the effectiveness of proposed solutions for surface monitoring and melt pool control.
Attached Documents: