1st Edition
Computational Techniques for Smart Manufacturing in Industry 5.0 Methods and Applications
We are witnessing rapid development in computational technologies and its applications in industry, leading to the 5th industrial revolution. Industry 5.0 is characterized by the synergies between machines and humans, with an aim to add value to production by creating personalized products able to meet customers' requirements. These intelligent manufacturing systems have been sought in various sectors (e.g. automobiles, power supplying, chemistry) to realize data-driven innovations for delivering highly customizable products and services faster, cheaper, better, and greener. In an intelligent manufacturing system, computational techniques constitute a key issue for providing efficient decision support tools based on data measured through IoT and ubiquitous sensing mechanisms. In complex industrial production scenarios, these computational techniques enable the enhancement of the quality of products and their manufacturing processes as well as sustainability (i.e., minimization of environmental and social impacts), and reduce uncertainties related to human factors.
This book presents recent advancements in research, new methods and techniques, and applications of advanced computational technologies in intelligent manufacturing for modeling, simulating, optimization, decision making, etc. which are very typical problems in the manufacturing processes. It stimulates scientific exchange of ideas, and experiences in the field of intelligent manufacturing applications. Researchers and practitioners alike will benefit from this book to enhance their understanding of Industry 5.0 which focuses on combining human creativity and craftsmanship with the speed, productivity, and consistency of AI systems. Real-world case studies in various fields and practical applications are provided in each chapter.
Preface
Introduction to Computational Techniques for Smart 1 Manufacturing in Industry 5.0: Methods and Applications
Yishui Zhang, Rongyuan Wang, Mengna Hong, Zhenglei He, Zhenglei He and Kim Phuc Tran
Research and Application of Raw Paper Quality Prediction Model for Cardboard Papermaking Process
Jiwei Qian, Zhenglei He, Yi Man, Jigeng Li and Mengna Hong
Kriging Model Based Greenhouse Gas Emissions Model of Papermaking Wastewater Treatment Process
Hongze Zheng, Zhenglei He, Mengna Hong and Yi Man
Peculiarities of BPG-Based Automatic Lossy Compression of Noisy Images
Vladimir Lukin, Bogdan Kovalenko and Sergii Kryvenko, Victoriya Naumenko and Benoit Vozel
Recommendation and Design of Personalized Garments based on Intelligent Human-Product Interaction
Zhujun Wang, Xuyuan Tao, Xianyi Zeng, Yingmei Xing, Zhenzhen Xu and Pascal Bruniaux
A Probabilistic Neural Network-based Approach to Garment Fit Level Evaluation in 3D Digitalized Environment
Zhujun Wang, Yingmei Xing, Xianyi Zeng, Pascal Bruniaux and Xuyuan Tao
Explainable Machine Learning based Control Charts for High-Dimensional Non-Stationary Time Series Data in IoT Systems: Challenges, Methods, and Future Directions
Aamir Saghir, Kim Duc Tran and Kim Phuc Tran
Monitoring the Ratio of Two Normal Variables and Compositional Data: A Literature Review and Perspective
Thi Thuy Van Nguyen, Thi Hien Nguyen, Kim Duc Tran, C´edric Heuchenne and Kim Phuc Tranvi Computational Techniques for Smart Manufacturing in Industry 5.0
Energy Efficiency Scheduling of Flexible Flow Shop Using Group Technology
Zhiqiang Zeng, Le Gao, Zhiyong Hong and Wenyi Liang
Optimal Operation of Wind-solar-thermal Synergy Considering Carbon Trading and Energy Storage Systems
Chang Liu, Zhenglei He, Yi Man, Jigeng Li and Mengna Hong
Adaptive Dempster-Shafer Theory for Evidence-based Trust Models in Multiagent Systems
Xiangyao Liang, Ningkui Wang, Mengna Hong, Yi Man and Zhenglei He
Optimization Model of Raw Material Selection for Construction Material Manufacturing
Xiuli He, Rongyuan Wang, Mengna Hong and Zhenglei He
Research on Fault Diagnosis of Paper-making Industry based on Knowledge Graph
Qingyuan Zhang, Zhenglei He, Yi Man, Jigeng Li and Mengna Hong
Research on the Construction of Papermaking Process Model Based on Digital Twin
Yishui Zhang, Rongyuan Wang, Mengna Hong and Zhenglei He
Index
Biography
Kim Phuc Tran is a Senior Associate Professor (Maître de Conférences HDR, equivalent to a UK Reader) of Artificial Intelligence and Data Science at the ENSAIT and the GEMTEX laboratory, University of Lille, France. He has a Master of Engineering in Automated Manufacturing. He obtained a Ph.D. in Automation and Applied Informatics at the University of Nantes, and an HDR (Doctor of Science or Dr. Habil.) in Computer Science and Automation at the University of Lille, France. He has published more numerous papers in peer-reviewed reputed journals and proceedings of international conferences. He edited 3 books. He is an Associate Editor, Editorial Board Member, and Guest Editor for several international journals such as IEEE Transactions on Intelligent Transportation Systems and Engineering Applications of Artificial Intelligence. Kim Phuc Tran has supervised 12 Ph.D. students and 3 Postdocs. In addition, as the project coordinator (PI), he conducted a national project about Healthcare Systems with Federated Learning. He has been or is involved (PI, co-PI, or member) in 13 national and European projects. He is an expert and an evaluator for the Public Service of Wallonia (SPW-EER), Belgium, the Natural Sciences and Engineering Research Council of Canada, the ARN (Agence Nationale de la Recherche), the ANRT (Association Nationale de la Recherche et de la Technologie), and the CY Cergy Paris University, France. He received the Award for Scientific Excellence (Prime d’Encadrement Doctoral et de Recherche) from by the Ministry of Higher Education, Research and Innovation, France for 4 years from 2021 to 2025 in recognition of his outstanding scientific achievements. From 2017 until now, he has been the Senior Scientific Advisor at Dong A University and the International Research Institute for Artificial Intelligence and Data Science (IAD), Danang, Vietnam where he holds the International Chair in Data Science and Explainable Artificial Intelligence. His research interests include Explainable Trustworthy, and Transparent Artificial Intelligence; Ethical, and Human-centered Artificial Intelligence; Safety and Reliability of Artificial Intelligence; Statistical Computing; Intelligent Decision Support Systems; Digital Twins; and Applications of AI, Edge Computing, and Data Science in Industry 5.0.
Zhenglei He is an Assistant Professor of Automation and Intelligent Manufacturing at the State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, China. He holds a Ph.D. degree of Computer Engineering, Automation and Signal Processing from University of Lille, France. His research focuses on digital twin, knowledge graph, and modelling, simulation and optimization of manufacturing process via computational techniques for industrial sustanability. He has published more than 30 papers in SCIE peer-reviewed international journals and proceedings of international conferences. He contributed 4 book chapters. He is a board member of Advanced Materials & Sustainable Manufacturing, and the guest editor of Applied Science, International Journal of Computational Intelligent Systems, and Journal of Smart Environments and Green Computing etc. He has chaired / co-chaired special sections of International conferences of FLINS 2022, DSBFI2023, ISKE2023, GCPC 2023 etc. He has co-supervised 13 postgraduate students.
