Robotics Grad Student at Arizona State University | Ex - Deputy Manager - Analytics | Data Scientist | Machine Learning Blogger | Robotics and AI Enthusiast
🔍 Ensuring Quality in Additive Manufacturing: Porosity Detection in Thermal Melt Pool Images In the dynamic world of additive manufacturing (AM), techniques like Laser Powder Bed Fusion (LPBF) and Direct Energy Deposition (DED) are revolutionizing how we build components, layer by layer, using thermal energy to fuse material powders. However, one of the critical challenges in maintaining the quality and integrity of these manufactured parts is detecting porosity — those unwanted voids or gaps within the material that can severely compromise its mechanical properties. Detecting porosity in thermal melt pool images is essential for improving the reliability and strength of 3D printed parts. Advanced imaging and analysis techniques are being developed to identify and address these imperfections, ensuring that the final products meet stringent quality standards. Learn more about the importance of porosity detection and the latest advancements in this area in my latest Medium blog post. Click the link below to read the full article: 📖 [Porosity Detection in Thermal Melt Pool Images](https://lnkd.in/gQ_BpQ9w) #AdditiveManufacturing #3DPrinting #LaserPowderBedFusion #DirectEnergyDeposition #QualityControl #ManufacturingExcellence #PorosityDetection #Engineering #Innovation
