Privacy-preserving for assembly deviation prediction in a machine learning model of hydraulic equipment under value chain collaboration
Abstract Hydraulic equipment, as a typical mechanical product, has been wildly used in various fields. Accurate acquisition and secure transmission of assembly deviation data are the most critical issues for hydraulic equipment manufacturer in the PLM-oriented value chain collaboration. Existing dev...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-14835-1 |