REAL-TIME MONITORING AND GAUSSIAN PROCESS-BASED ESTIMATION OF THE MELT POOL PROFILE IN DIRECT ENERGY DEPOSITION

Jiaqi Lyu, Javid Akhavan, Youmna Mahmoud, Ke Xu, Chaitanya Krishna, Prasad Vallabh, Souran Manoochehri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

A comprehensive understanding of the melt pool behavior during directed energy deposition (DED) has become essential in identifying process anomalies and controlling the process quality. Previous studies focused on predicting the melt pool characteristics by solely using the process parameters, in this study we use real-time melt pool images to predict the melt pool characteristics. A CMOS camera is used to capture coaxial images of the melt pool during the deposition of single-track prints to improve the prediction model. Multiple regression models are trained and compared to estimate the melt pool profile (width, depth, and height) as a function of process parameters (namely, the laser power, the powder feed rate, and the scanning speed) and features from the ellipse fitting of the real-time melt pool images. A novel image processing algorithm is proposed to extract the major axis, minor axis, and tilt. The sensitivity analysis demonstrated that combining process parameters and coaxial images can improve the prediction performance. The Gaussian Process regression showed the best performance among all the employed regression models.

Original languageEnglish
Title of host publicationAdditive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering
ISBN (Electronic)9780791887233
DOIs
StatePublished - 2023
EventASME 2023 18th International Manufacturing Science and Engineering Conference, MSEC 2023 - New Brunswick, United States
Duration: 12 Jun 202316 Jun 2023

Publication series

NameProceedings of ASME 2023 18th International Manufacturing Science and Engineering Conference, MSEC 2023
Volume1

Conference

ConferenceASME 2023 18th International Manufacturing Science and Engineering Conference, MSEC 2023
Country/TerritoryUnited States
CityNew Brunswick
Period12/06/2316/06/23

Keywords

  • Direct energy deposition
  • Gaussian process regression
  • Image processing
  • Melt pool profile
  • Real-time monitoring
  • SS316L

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