In-situ monitoring of sub-surface and internal defects in additive manufacturing: A review

Abstract

Additive Manufacturing (AM), or 3D printing, processes depend on a user-defined set of optimized process parameters to create a component. Monitoring and control of AM processes in real-time can help achieve process stability and repeatability to produce high quality parts. By applying in-situ monitoring methods to the AM process, defects in the printed parts can be detected. In this review, application of both imaging and acoustic methods for the detection of sub-surface and internal defects is discussed. Imaging methods consist of visual and thermal monitoring techniques, such as optical cameras, infrared (IR) cameras, and X-ray imaging. Many studies have been conducted that prove the reliability of imaging methods in monitoring the printing process and build area, as well as detecting defects. Acoustic methods rely on acoustic sensing technologies and signal processing methods to acquire and analyze acoustic signals, respectively. Raw acoustic emission signals can correlate to particular defect mechanisms using methods of feature extraction. In this review, representation and analysis of the acquired in-situ data from both imaging and acoustic methods is discussed, as well as the means of data processing. Ex-situ testing techniques are introduced as methods for verification of results gained from in-situ monitoring data.

Keywords

• Real-time process monitoring
• In-situ monitoring
• Imaging methods
• Acoustic methods
• Defect detection
• Signal processing