Automated porosity segmentation in laser powder bed fusion part using computed tomography: a validity study

Keyphrases

• 3D Volume 25%
• Aerospace 25%
• Analytical Method 25%
• Broad Adoption 25%
• Computed Tomography 100%
• Controlled Porosity 25%
• Convolutional Neural Network 50%
• Deep Learning Convolutional Neural Network 25%
• Deep Learning Segmentation 25%
• Defect Analysis 25%
• Defect Detection 25%
• Image Analysis 25%
• Image Segmentation 25%
• Induced Porosity 25%
• Laser Powder Bed Fusion (L-PBF) 100%
• Laser Scanning Confocal Microscopy 25%
• Manufacturing Process 25%
• Microscopic Examination 25%
• Multiscale Pores 25%
• Neural Network 25%
• Otsu Thresholding 25%
• Over 75 25%
• Pore Morphology 25%
• Pore Segmentation 50%
• Pore Size 25%
• Porosity 100%
• Porosity Analysis 50%
• Quality Control 25%
• Reliability Assessment 25%
• Repeatability 75%
• Scanning System 50%
• Segmentation Algorithm 50%
• Segmentation Method 50%
• Ti-6Al-4V (Ti64) 25%
• Validation Studies 100%
• Variance Component Estimation 25%

Engineering

• Confocal Microscopy 20%
• Convolutional Neural Network 60%
• Deep Learning Method 20%
• Defect Detection 20%
• High Resolution 20%
• Image Analysis 20%
• Laser Powder Bed Fusion 100%
• Manufacturing Process 20%
• Metrics 20%
• Multiscale 20%
• Porosity 100%
• Quality Control 20%
• Reliability Assessment 20%
• Repeatability 60%