Machine Learning for industrial applications: A comprehensive literature review

M Bertolini, D Mezzogori, M Neroni… - Expert Systems with …, 2021 - Elsevier
Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …

Toward intelligent industrial informatics: A review of current developments and future directions of artificial intelligence in industrial applications

D De Silva, S Sierla, D Alahakoon… - IEEE Industrial …, 2020 - ieeexplore.ieee.org
Research, the universal pursuit of new knowledge, is embarking on a fresh journey into
artificial intelligence (AI). ature reports that AI arose nine places to the fourth-most popular …

[HTML][HTML] Degradation curves integration in physics-based models: Towards the predictive maintenance of industrial robots

P Aivaliotis, Z Arkouli, K Georgoulias… - Robotics and computer …, 2021 - Elsevier
Predictive maintenance has been proposed to maximize the overall plant availability of
modern manufacturing systems. To this end, research has been conducted mainly on data …

Business analytics in Industry 4.0: A systematic review

AJ Silva, P Cortez, C Pereira, A Pilastri - Expert systems, 2021 - Wiley Online Library
Abstract Recently, the term “Industry 4.0” has emerged to characterize several Information
Technology and Communication (ICT) adoptions in production processes (eg, Internet‐of …

Decision-based virtual metrology for advanced process control to empower smart production and an empirical study for semiconductor manufacturing

CF Chien, WT Hung, CW Pan… - Computers & Industrial …, 2022 - Elsevier
Virtual metrology (VM) has been employed to improve the performance of advanced process
control for semiconductor manufacturing. A number of VM models have been proposed to …

Virtual metrology in semiconductor manufacturing: Current status and future prospects

V Maitra, Y Su, J Shi - Expert Systems with Applications, 2024 - Elsevier
Abstract Advanced Process Control (APC) has become an increasingly pressing issue for
the semiconductor industry, particularly in the new era of sub-5nm process technology. To …

A deep learning model for identification of defect patterns in semiconductor wafer map

Y Yuan-Fu - 2019 30th Annual SEMI Advanced Semiconductor …, 2019 - ieeexplore.ieee.org
The semiconductors are used as various precision components in many electronic products.
Each layer must be inspected of defect after drawing and baking the mask pattern in wafer …

DeepVM: A Deep Learning-based approach with automatic feature extraction for 2D input data Virtual Metrology

M Maggipinto, A Beghi, S McLoone, GA Susto - Journal of Process Control, 2019 - Elsevier
Abstract Industry 4.0 encapsulates methods, technologies, and procedures that transform
data into informed decisions and added value in an industrial context. In this regard …

[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 …

Soft metrology based on machine learning: a review

M Vallejo, C De La Espriella… - Measurement …, 2019 - iopscience.iop.org
Soft metrology has been defined as a set of measurement techniques and models that allow
the objective quantification of properties usually determined by human perception such as …