Soundar R. T. Kumara — accepted AI-conference papers

2022

Spatiotemporal Monitoring of Melt-Pool Variations in Metal-Based Additive Manufacturing

Hui Yang, Siqi Zhang, Yan Lu, Paul Witherell, Soundar R. T. Kumara

RA-L 2022

Additive manufacturing (AM) provides a higher level of flexibility to build customized products with complex geometries, by selectively melting and solidifying metal powders. However, wide applications of AM beyond rapid prototyping are currently limited by its ability to perform quality assurance a

Cited by 11 Source ↗Scholar ↗

2021

Ontology-Driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing

Ruimin Chen, Yan Lu, Paul Witherell, Timothy W. Simpson, Soundar R. T. Kumara, Hui Yang

RA-L 2021

Additive manufacturing (AM) enables the creation of complex geometries that are difficult to realize using conventional manufacturing techniques. Advanced sensing is increasingly being used to improve AM processes, and installing different sensors onto AM systems has yielded more data-rich environme

Cited by 31 Source ↗Scholar ↗