Artificial Intelligence for Smart Manufacturing

Edited by Kim Phuc Tran ()

in Springer Series in Reliability Engineering from Springer, currently edited by Hoang Pham

Date: 2023
ISBN: 978-3-031-30510-8
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Chapters in this book:

Introduction to Smart Manufacturing with Artificial Intelligence

Kim Phuc Tran

Artificial Intelligence for Smart Manufacturing in Industry 5.0: Methods, Applications, and Challenges

Huu Du Nguyen and Kim Phuc Tran

Quality Control for Smart Manufacturing in Industry 5.0

Huu Du Nguyen, Phuong Hanh Tran, Thu Ha Do and Kim Phuc Tran

Dynamic Process Monitoring Using Machine Learning Control Charts

Xiulin Xie and Peihua Qiu

Fault Prediction of Papermaking Process Based on Gaussian Mixture Model and Mahalanobis Distance

Guojian Chen, Zhenglei He, Yi Man, Jigeng Li, Mengna Hong and Kim Phuc Tran

Multi-objective Optimization of Flexible Flow-Shop Intelligent Scheduling Based on a Hybrid Intelligent Algorithm

Huanhuan Zhang, Zhenglei He, Yi Man, Jigeng Li, Mengna Hong and Kim Phuc Tran

Personalized Pattern Recommendation System of Men’s Shirts

Guillaume Tartare, Cheng Chi and Pascal Bruniaux

Efficient and Trustworthy Federated Learning-Based Explainable Anomaly Detection: Challenges, Methods, and Future Directions

Do Thu Ha, Ta Phuong Bac, Kim Duc Tran and Kim Phuc Tran

Multimodal Machine Learning in Prognostics and Health Management of Manufacturing Systems

Sagar Jose, Khanh T. P Nguyen and Kamal Medjaher

Explainable Articial Intelligence for Cybersecurity in Smart Manufacturing

Ta Phuong Bac, Do Thu Ha, Kim Duc Tran and Kim Phuc Tran

Wearable Technology for Smart Manufacturing in Industry 5.0

Tho Nguyen, Kim Duc Tran, Ali Raza, Quoc-Thông Nguyen, Huong Mai Bui and Kim Phuc Tran

Benefits of Using Digital Twin for Online Fault Diagnosis of a Manufacturing System

Ramla Saddem and Dylan Baptiste

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DOI: 10.1007/978-3-031-30510-8

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