Porosity Quantification for Additive Manufacturing How-to Using Dragonfly

In this application note, we demonstrate porosity analysis in a cube of additively manufactured metal. The video shows the workflow for a reliable segmentation and analysis. This information can drive manufacturing quality up, something that drives your business success. If you see the value of this for your manufacturing or quality control efforts, get your own 30 day trial of @ORSDragonfly software today: https://www.theobjects.com/dragonfly/...

Read and see more here: https://orss.ca/AM4

★ Read and see more about Dragonfly on our website https://www.theobjects.com. If you would like to see a specific analysis in our next application notes, please get in touch, especially if you can provide the data. We also offer commercial image analysis services!

Get Dragonfly Today! Go to https://www.theobjects.com/dragonfly/...

Let's Connect
◦ Twitter-   / orsdragonfly3d  
◦ LinkedIn:   / object-research-systems  
◦ ORS Website: ORS Website: https://www.theobjects.com
◦ Sales-related inquiries: [email protected]
◦ Support: [email protected]

About ORS
Object Research Systems (ORS) develops deep learning powered 3D visualization and image analysis software. Dragonfly and Dragonfly Cloud, ORS’ flagship products, provide innovators from leading universities or industries, an advanced machine learning and neural networks based segmentation engine. Dragonfly's quantification tools then provide powerful options for counting, measuring, and characterizing image features, such as pores, fibers, grains, and much more. Its user-friendly experience translates its powerful and accurate quantitative findings in high-impact visuals. The ability to build fully automated workflows also enables reproducible results.

#industrialinspection #nondestructivetesting #NDT #nondestructiveevaluation #NDE #qualitycontrol #engineering #3d #imaging #XRM #Xraymicroscopy #Dragonfly #porosity #pores #cracks #wallthickness #thickslabmode #meshoutput #Xray #inspection #CTismorethanNDT