MPOFI: Multichannel Partially Observed Functional Modeling for Defect Classification with Imbalanced Dataset via Deep Metric Learning

arXiv:2404.03329v1 Announce Type: new
Abstract: In modern manufacturing, most of the product lines are conforming. Few products are nonconforming but with different defect types. The identification of defect types can help further root cause diagnosis of production lines. With the sensing development, continuous signals of process variables can be collected in high resolution, which can be regarded as multichannel functional data. They have abundant information to characterize the process and help identify the defect types. Motivated by a real example …

abstract arxiv classification continuous cs.lg dataset development diagnosis eess.sp functional identification manufacturing modeling modern product production products sensing stat.ml type types via