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Smart Additive Manufacturing: In-Process Sensing And Data Analytics For Online Defect Detection In Metal Additive Manufacturing Processes, Mohammad Montazeri

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

The goal of this dissertation is to detect the incipient flaws in metal parts made using additive manufacturing processes (3D printing). The key idea is to embed sensors inside a 3D printing machine and conclude whether there are defects in the part as it is being built by analyzing the sensor data using artificial intelligence (machine learning). This is an important area of research, because, despite their revolutionary potential, additive manufacturing processes are yet to find wider acceptance in safety-critical industries, such as aerospace and biomedical, given their propensity to form defects. The presence of defects, such as porosity, can …