| About this Abstract |
| Meeting |
MS&T23: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing: Equipment, Instrumentation and In-Situ Process Monitoring
|
| Presentation Title |
Implementing Statistical Process Control in Laser Powder Bed Fusion Metal Additive Manufacturing |
| Author(s) |
Venkatavaradan Sunderarajan, Suman Das |
| On-Site Speaker (Planned) |
Venkatavaradan Sunderarajan |
| Abstract Scope |
Robust statistical process control can address challenges that prevent widespread industrial adoption of Laser Powder Bed Fusion (LPBF) Metal Additive Manufacturing (AM). Vast amounts of heterogeneous data from multiple in-situ monitoring sensors capture process information in real-time across length and time scales. This work demonstrates an effective method to parse and analyze this data, extract valuable information, and apply multivariate statistics to develop control charts for monitoring the LPBF process. Post-build part characterization helps establish correlations between the part properties and process state measured in-situ. Appropriate process control measures and critical limits can then be implemented for each process variable (or any combination), commensurate with the tolerance in part property allowable depending on the end-use application. This work will also highlight the challenges associated with the scale and rate of heterogeneous in-situ data capture, along with steps to address the same with minimal loss of valuable process information. |