A review of data mining applications in semiconductor manufacturing
For decades, industrial companies have been collecting and storing high amounts of data
with the aim of better controlling and managing their processes. However, this vast amount …
with the aim of better controlling and managing their processes. However, this vast amount …
Predictive maintenance in Industry 4.0: A systematic multi-sector mapping
Industry 4.0 is strongly intertwined with big data streaming flows from intelligent sensors and
machinery installed in industrial facilities. Failures can disrupt production and lead the …
machinery installed in industrial facilities. Failures can disrupt production and lead the …
A prescriptive maintenance system for intelligent production planning and control in a smart cyber-physical production line
Don't just predict problems–prescribe a solution: that's the premise behind prescriptive
maintenance (PsM). Better and more data, coupled with Artificial Intelligence, Simulation …
maintenance (PsM). Better and more data, coupled with Artificial Intelligence, Simulation …
Semiconductor manufacturing process improvement using data-driven methodologies
H Chowdhury - 2023 - preprints.org
The paper investigates into the intricacies of semiconductor manufacturing, a highly complex
process entailing a wide array of subprocesses and diverse equipment. Semiconductors are …
process entailing a wide array of subprocesses and diverse equipment. Semiconductors are …
Proactive buildings: A prescriptive maintenance approach
Prescriptive maintenance has recently attracted a lot of scientific attention. It integrates the
advantages of descriptive and predictive analytics to automate the process of detecting non …
advantages of descriptive and predictive analytics to automate the process of detecting non …
[HTML][HTML] Context-aware recommendations for extended electric vehicle battery lifetime
Electric vehicles are a means of reducing CO 2 emissions in transportation. However, the
sustainability of electric vehicle batteries is affected by battery health degradation, which …
sustainability of electric vehicle batteries is affected by battery health degradation, which …
Exploring machine learning for semiconductor process optimization: a systematic review
As machine learning (ML) continues to find applications, extensive research is currently
underway across various domains. This study examines the current methodologies of ML …
underway across various domains. This study examines the current methodologies of ML …
Integrated prescriptive maintenance and production planning: a machine learning approach for the development of an autonomous decision support agent
Abstract Machine Learning (ML) practice represents a vital construct for developing
intelligent Cyber-Physical Production Systems (CPPS) capable of making timely …
intelligent Cyber-Physical Production Systems (CPPS) capable of making timely …
An attention-based method for remaining useful life prediction of rotating machinery
Y Deng, C Guo, Z Zhang, L Zou, X Liu, S Lin - Applied Sciences, 2023 - mdpi.com
Data imbalance and large data probability distribution discrepancies are major factors that
reduce the accuracy of remaining useful life (RUL) prediction of high-reliability rotating …
reduce the accuracy of remaining useful life (RUL) prediction of high-reliability rotating …
Electron Energy-Loss Spectroscopy Method for Thin-Film Thickness Calculations with a Low Incident Energy Electron Beam
In this study, the thickness of a thin film (tc) at a low primary electron energy of less than or
equal to 10 keV was calculated using electron energy-loss spectroscopy. This method uses …
equal to 10 keV was calculated using electron energy-loss spectroscopy. This method uses …