Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

An Industry 4.0 Maturity Model Proposal Based on Total Quality Management Principles: An Application to an Automotive Parts Manufacturer

Kerem Elibal and Eren Özceylan
IEEE Transactions on Engineering Management 71 10815 (2024)
https://doi.org/10.1109/TEM.2024.3397555

Machine learning-based techniques for fault diagnosis in the semiconductor manufacturing process: a comparative study

Abubakar Abdussalam Nuhu, Qasim Zeeshan, Babak Safaei and Muhammad Atif Shahzad
The Journal of Supercomputing 79 (2) 2031 (2023)
https://doi.org/10.1007/s11227-022-04730-x

Production quality prediction of multistage manufacturing systems using multi-task joint deep learning

Pei Wang, Hai Qu, Qianle Zhang, Xun Xu and Sheng Yang
Journal of Manufacturing Systems 70 48 (2023)
https://doi.org/10.1016/j.jmsy.2023.07.002

Development of a virtual quality gate concept based on high-potential tests for lithium-ion battery cell manufacturing

Chao Zhang, Gabriela Ventura Silva, Tim Abraham and Christoph Herrmann
Procedia CIRP 120 1119 (2023)
https://doi.org/10.1016/j.procir.2023.09.135

A Modified Lasso Model for Yield Analysis Considering the Interaction Effect in a Multistage Manufacturing Line

Taewon Heo, Youngju Kim and Chang Ouk Kim
IEEE Transactions on Semiconductor Manufacturing 35 (1) 32 (2022)
https://doi.org/10.1109/TSM.2021.3121026

Application of machine learning and data mining in manufacturing industry

Zheng Song and Shu Luo
Frontiers in Computing and Intelligent Systems 2 (1) 47 (2022)
https://doi.org/10.54097/fcis.v2i1.2966

Quality monitoring in multistage manufacturing systems by using machine learning techniques

Mohamed Ismail, Noha A. Mostafa and Ahmed El-assal
Journal of Intelligent Manufacturing 33 (8) 2471 (2022)
https://doi.org/10.1007/s10845-021-01792-1

Attention Mechanism-Based Root Cause Analysis for Semiconductor Yield Enhancement Considering the Order of Manufacturing Processes

Min Yong Lee, Yeoung Je Choi, Gyeong Taek Lee, Jongkwan Choi and Chang Ouk Kim
IEEE Transactions on Semiconductor Manufacturing 35 (2) 282 (2022)
https://doi.org/10.1109/TSM.2022.3156600

Managing and Implementing the Digital Transformation

Baris Ördek, Yuri Borgianni and Eric Coatanea
Lecture Notes in Networks and Systems, Managing and Implementing the Digital Transformation 525 61 (2022)
https://doi.org/10.1007/978-3-031-14317-5_6

Commonality Analysis for Detecting Failures Caused by Inspection Tools in Semiconductor Manufacturing Processes

Dae Woong An, Seung Kim, Hyun Kyu Kim and Chang Ouk Kim
IEEE Transactions on Semiconductor Manufacturing 35 (4) 596 (2022)
https://doi.org/10.1109/TSM.2022.3201654

Data-driven Analysis of Product Property Propagation to Support Process-integrated Quality Management in Manufacturing Systems

Marc-André Filz, Sebastian Gellrich, Felix Lang, et al.
Procedia CIRP 104 900 (2021)
https://doi.org/10.1016/j.procir.2021.11.151

Virtual Quality Gates in Manufacturing Systems: Framework, Implementation and Potential

Marc-André Filz, Sebastian Gellrich, Artem Turetskyy, Jacob Wessel, Christoph Herrmann and Sebastian Thiede
Journal of Manufacturing and Materials Processing 4 (4) 106 (2020)
https://doi.org/10.3390/jmmp4040106

Prediction of Press-Fit Quality via Data Mining Techniques and Artificial Intelligence

Rene Cruz Guerrero, Maria De Los Angeles Alonso Lavernia and Isaias Simon Marmolejo
IEEE Access 7 159599 (2019)
https://doi.org/10.1109/ACCESS.2019.2950642