Automatic Process Mapping for Ti64 Single Tracks in Laser Powder Bed Fusion

Using an unsupervised convolutional neural network classifier, an automated workflow to generate the process map for printing Ti-6Al-4 V with laser powder bed fusionLaser Powder Bed Fusion (LPBF) with minimal human supervision is proposed. Single scan vectors using a range of laser powers and scan speeds were printed on a bare Ti-6Al-4 V baseplate, which were then imaged using optical microscopy without further material preparation steps. After resizing and thresholding, the resulting dataset was used to train the neural network into automatically differentiating the tracks into categories. Post-analysis reveals that the model can differentiate between commonly observed track morphologies and map out the viable processing window automatically for the alloy.