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- research-articleNovember 2024
Deep learning-based quality prediction for multi-stage sequential hot rolling processes in heavy rail manufacturing
Computers and Industrial Engineering (CINE), Volume 196, Issue Chttps://doi.org/10.1016/j.cie.2024.110466Highlights- We spatially align the isochronous data obtained from multi-stage rolling process.
- A TFL model was crafted and effectively predicted the multiple quality indicators.
- TFL use a Double-layer architecture to capture the transfer state ...
Traditional quality control practices in heavy rail manufacturing primarily rely on experiential knowledge and numerical simulations. However, these methods come with significant drawbacks, including high costs, safety concerns, and limited ...