Term of Award
Master of Science in Applied Engineering (M.S.A.E.)
Document Type and Release Option
Thesis (open access)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department of Manufacturing Engineering
Committee Member 1
Committee Member 2
Additive manufacturing processes allow for a great degree of flexibility in terms of part production. The process is autonomous once the part has started printing in that the operator generally does not need to intervene until the part is finished. One issue that this introduces, however, is an inability to determine part quality during the printing process. Once a part has started printing, the operator must either wait until the part is finished or regularly check on the part during the print to determine the part quality. Using data gathered from multiple sensors, a quality score can be used to estimate the part quality at any point during the printing process. The development of the score also observed several of the largest contributing ambient factors to both the surface roughness and the part porosity. The largest contributors to quality were the chamber temperature and the oxygen content for the surface roughness and porosity, respectively. Each build characteristic was plotted, and the best fit equations created the quality score. The score generated a zero to one hundred scale that can be easily viewed without intimate knowledge of the process.
Daigneault, Ryan, "The Development of a Holistic Quality Score Using In-Situ Monitoring of Laser Powder Bed Fusion" (2021). Electronic Theses and Dissertations. 2333.
Research Data and Supplementary Material