Sigma Labs has released version 7.0 of PrintRite3D, its in-process quality assurance software for industrial 3D printing.
The new version now incorporates:
- Temperature monitoring and calibration, including a cooling rate metric and units/traceability for TEP to Celsius/Kelvin conversion
- Neural net machine learning recoater interaction detection, that allows users to automatically spot recoater interaction detection with higher diagnostic accuracy
- User facing machine learning predictive models, allowing testing and training of new users on in-process quality monitoring to correlate in process anomalies to post process NDT defects
- Multi-laser quality metrics, to monitor and alert users when lasers are coming into close contact and interacting
- Production framework, for visualizing of reference data and enabling statistical analysis of anomalies to detect build process trends and deviations
- 3D visualization diagnostics, provides usability enhancements and rapid cross-section analysis and easy comparison to CT
- User roles and login, data visualization authentication access for improved security.
This story uses material from Sigma Labs, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier.