In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

HIGHLIGHTS

• who: Aniruddha Gaikwad from the Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, USA have published the article: In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning, in the Journal: (JOURNAL)
• what: To overcome this challenge the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size velocity and shape characteristics of droplets in DoD-LMJ process. As an example, the different shapes of droplets observed in the DoD-LMJ experiments . . .
  

   

  

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