Online semisupervised learning approach for quality monitoring of complex manufacturing process
Data-driven quality monitoring is highly demanded in practice since it enables relieving manual quality inspection of the product quality. Conventional data-driven quality monitoring is constrained by its offline characteristic thus being unable to handle streaming nature of sensory data and nonstat...
Main Authors: | , , , |
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Other Authors: | |
Format: | Journal Article |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/153757 |