Secure Machine Learning Framework for Defect Detection and Quality Enhancement in Injection Molding Processes

Abstract excerpt

Injection molding processes generate large volumes of heterogeneous process data that reflect complex and dynamic manufacturing conditions, directly influencing product quality. Conventional quality control approaches based on fixed statistical thresholds and operator experience often fail to ensure stable and secure operation under such variability, leading to increased defect rates and reduced process reliabilit...

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Identifiers and source

Literature Corpus work

da3f2b13-20d2-5626-8b4a-e37a81329f74

DOI

10.20944/preprints202512.2583.v1