[HTML][HTML] Machine learning for semiconductors
DY Liu, LM Xu, XM Lin, X Wei, WJ Yu, Y Wang, ZM Wei - Chip, 2022 - Elsevier
Thanks to the increasingly high standard of electronics, the semiconductor material science
and semiconductor manufacturing have been booming in the last few decades, with massive …
and semiconductor manufacturing have been booming in the last few decades, with massive …
Production quality prediction of multistage manufacturing systems using multi-task joint deep learning
A multistage manufacturing system with multiple manufacturing stages is the key and main
production mode for enterprises to achieve lean production. Due to the variation …
production mode for enterprises to achieve lean production. Due to the variation …
Uncertainty utilization in fault detection using Bayesian deep learning
Up to now, extensive literature on the usage of deep learning in manufacturing can be
found. Though, actual usage of deep learning in manufacturing sites is somehow restrained …
found. Though, actual usage of deep learning in manufacturing sites is somehow restrained …
[HTML][HTML] Machine learning applications on IoT data in manufacturing operations and their interpretability implications: A systematic literature review
A Presciuttini, A Cantini, F Costa… - Journal of Manufacturing …, 2024 - Elsevier
Industry 4.0 has transformed manufacturing with real-time plant data collection across
operations and effective analysis is crucial to unlock the full potential of Internet-of-Things …
operations and effective analysis is crucial to unlock the full potential of Internet-of-Things …
Unsupervised anomaly analysis-based manufacturing quality test and grading method for combine harvesters
X Ni, K Liu, X Zhou, X Mao, D Chen, S Wang - Computers and Electronics in …, 2023 - Elsevier
Manufacturing quality tests mainly depend on manual methods, and most quality
evaluations rely on the quality evaluation intervals, which lacks quantitative means for …
evaluations rely on the quality evaluation intervals, which lacks quantitative means for …
Data-manifold-based monitoring and anomaly diagnosis for manufacturing process
F Zhang, J Zhang, J Ma - Journal of Intelligent Manufacturing, 2023 - Springer
Aiming to solve the problems of the inaccurate dimension reduction of high-dimensional
data and insufficient information utilization in traditional manufacturing process monitoring …
data and insufficient information utilization in traditional manufacturing process monitoring …
Rule-based visualization of faulty process conditions in the die-casting manufacturing
Die-casting is a popular manufacturing process that produces precise metal parts with
excellent dimensional accuracy and smooth cast surfaces. Recently die-casting process …
excellent dimensional accuracy and smooth cast surfaces. Recently die-casting process …
Ensemble learning-enabled early prediction of dimensional accuracy for complex products during investment casting
Investment casting is a complex process with multiple procedures. Predicting the
dimensional accuracy of products and identifying defect parts at the early manufacturing …
dimensional accuracy of products and identifying defect parts at the early manufacturing …
[HTML][HTML] Towards autonomous learning and optimisation in textile production: data-driven simulation approach for optimiser validation
R Kins, C Möbitz, T Gries - Journal of Intelligent Manufacturing, 2024 - Springer
The textile industry is a traditional industry branch that remains highly relevant in Europe.
The industry is under pressure to remain profitable in this high-wage region. As one …
The industry is under pressure to remain profitable in this high-wage region. As one …
质量4.0: 概念, 基础架构及关键技术
刘虎沉， 王鹤鸣， 施华， 尤建新 - 科技导报, 2023 - kjdb.org
质量4.0:概念,基础架构及关键技术 首页 编委会 期刊简介 期刊介绍 数据库收录及获奖 发展历程
未来愿景 开放获取 作者服务 投稿指南 投稿须知 投稿说明 论文加工费 学术不端检测 同行评议 …
未来愿景 开放获取 作者服务 投稿指南 投稿须知 投稿说明 论文加工费 学术不端检测 同行评议 …