Imbalanced Data Classification via Generative Adversarial Network with Application to Anomaly Detection in Additive Manufacturing Process. (arXiv:2210.17274v2 [cs.LG] UPDATED)

Supervised classification methods have been widely utilized for the quality
assurance of the advanced manufacturing process, such as additive manufacturing
(AM) for anomaly (defects) detection. However, since abnormal states (with
defects) occur much less frequently than normal ones (without defects) in the
manufacturing process, the number of sensor data samples collected from a
normal state outweighs that from an abnormal state. This issue causes
imbalanced training data for classification models, thus deteriorating the
performance of detecting abnormal states in the …

additive manufacturing anomaly anomaly detection application arxiv classification data data classification detection generative adversarial network manufacturing network process