| About this Abstract |
| Meeting |
MS&T21: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing of Metals:
ICME Gaps: Material Property and Validation Data to Support Certification
|
| Presentation Title |
Capturing and Analyzing In-situ Data within the Directed Energy Deposition Process with DEDSmart |
| Author(s) |
Michael Juhasz, Melanie Lang |
| On-Site Speaker (Planned) |
Michael Juhasz |
| Abstract Scope |
Within the various AM processes, there are several process parameters that determine the resultant geometry and part quality of a build. In certain systems, the data from the builds remain locked away in a closed box. But can this data be useful for the end-users? At FormAlloy, we know so. Along with developing and integrating their fleet of in-process sensors and closed loop control features, FormAlloy internally developed their data logging capability known as DEDSmartTM for their directed energy deposition systems. All DEDSmartTM data is automatically generated post build and contains all the parameters and process signatures on a time scale. The data sets provided can be linked to post-process evaluations to enable machine learning possibilities and defect detection algorithms. Join FormAlloy as they discuss how their DEDSmartTM data was used to link defects that were observed post-build to anomalies that were found within the process parameters and their signatures. |