Process monitoring and inspection

With the rapid development of additive manufacturing (AM), the lack of assurance of part quality and repeatability has been a major obstacle to hinder the widespread adoption of AM technologies. Process monitoring and inspections are identified as effective approaches to improve the part quality and repeatability. This chapter gives an overview of key techniques to conduct studies on the process monitoring and quality control of AM processes. The signals, sensors, and systems involved in process monitoring and inspections are first discussed, especially for the optical, thermal, X-ray, and acoustic signals. Then, the signatures of monitored objects and process defects acquired from these signals are reviewed. Next, the quality control achieved by a closed-up monitoring system with feedback control is presented. The machine learning (ML) approach and its applications in quality and feedback control are mainly introduced. Finally, the associated standards and toolkits are also summarized, and the outlook on the process monitoring is outlined.