654cf0ed6e82513cfcfb · Ontology-driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing
Ontology-driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing
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
{
"title_en": "Ontology-driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing",
"designation": "",
"series": "",
"status": "",
"date": "2021-06-16",
"date_original": "June 16, 2021",
"url": "https://www.nist.gov/publications/ontology-driven-learning-bayesian-network-causal-inference-and-quality-assurance",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Ruimin Chen, Yan Lu , Paul Witherell , Timothy Simpson, Soundar Kumara, Hui Yang",
"abstract_excerpt_en": "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",
"id": "654cf0ed6e82513cfcfb",
"sources": [
"NIST Publications"
],
"source_records": [
{
"title_en": "Ontology-driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing",
"designation": "",
"series": "",
"status": "",
"date": "2021-06-16",
"date_original": "June 16, 2021",
"url": "https://www.nist.gov/publications/ontology-driven-learning-bayesian-network-causal-inference-and-quality-assurance",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Ruimin Chen, Yan Lu , Paul Witherell , Timothy Simpson, Soundar Kumara, Hui Yang",
"abstract_excerpt_en": "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"
}
],
"translation_state": "none"
}