@inproceedings{20,
  author = {Deniz Ertay and Mohamed Naiel and Mihaela Vlasea and Kaan Erkorkmaz and Paul Fiegutha},
  title = {Melt Pool Geometry Modeling and Monitoring via In-Situ Vision System for Powder Fed Laser Fusion Process},
  abstract = {<p>Powder fed laser fusion (PFLF) is a metal additive manufacturing process where modelling and monitoring the geometry of the process are necessary to improve the accuracy and repeatability. In this work, an analytical lumped- parameter thermal and geometry models are presented, which predict the complex thermal behaviour and the geometric features of the PFLF process. The melt pool is monitored by a high dynamic range (HDR) camera during the process, which has an advantage of higher pixel depth and preferred in monitoring of the welding processes. Image processing techniques are used to detect the melt pool. The process signatures extracted with the HDR camera are used for the validation of the physics-based models and for the detection of process instability. The detected process instabilities will be used in planning post-processing in the future.</p>
},
  year = {2019},
  journal = {8th International Conference on Virtual Machining Process Technology (VMPT)},
  address = {Vancouver, Canada},
}