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Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order

Proceedings of FAIM 2024, June 23–26, 2024, Taichung, Taiwan, Volume 1

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Yi-Chi Wang

    1. Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan

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  2. Siu Hang Chan

    1. Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan

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    You can also search for this editor in PubMed   Google Scholar

  3. Zih-Huei Wang

    1. Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan

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  • Reports on research, theories, and practices in the field of automation and manufacturing
  • Identifies solutions and strategies for solving current issues in Industry 4.0
  • First volume of a 2-volume set

Part of the book series: Lecture Notes in Mechanical Engineering (LNME)

Included in the following conference series:

Conference proceedings info: FAIM 2024.

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About this book

This book reports on cutting-edge research and developments in manufacturing, giving a special emphasis to solutions for the Changing World Order. It covers applications of machine learning in manufacturing and advances in cyber-physical systems, human-robot collaboration, and machine tools and assembly systems.  It also reports on advances in logistics and supply chain, and lean manufacturing.  Based on the proceedings of the 33rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2024), held on June 23-26, 2024, in Taichung, Taiwan, this first volume of a 2-volume set provides academics and professionals with extensive, technical information on trends and technologies in manufacturing, yet it also discusses challenges and practice-oriented experience in all the above-mentioned areas.

Keywords

Table of contents (53 papers)

  1. Front Matter

    Pages i-xvi
    Download chapter PDF

  2. Machine Learning (ML)

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. A Nature-Inspired Concept Drift Adaptation Method for Industrial Data Stream Regression

      • Martin Trat, Philipp Bergmann, Andreas Ott, Jivka Ovtcharova
      Pages 3-13

    3. Surface Mounting Production Line Automatic Optical Inspection (AOI) False Call Classification with Machine Learning Algorithms

      • Zhenxuan Zhang, Priyank Thakkar, Sang Won Yoon, Daehan Won
      Pages 14-21

    4. Using Applied Machine Learning to Detect Cyber-Security Threats in Industrial IoT Devices

      • Ali Hosseinzadeh, Mohammad Shahin, F. Frank Chen, Mazdak Maghanaki, Tzu-Liang Tseng, Rasoul Rashidifar
      Pages 22-30

    5. Concrete Fault Detection Using Deep Learning: Towards Waste Reduction in Bridge Inspection

      • Mohammad Shahin, F. Frank Chen, Mazdak Maghanaki, Ali Hosseinzadeh, Shadi Firouzranjbar, Hamid Khodadadi Koodiani
      Pages 31-38

    6. A Hybrid Model for Solder Joint Height Prediction Based on Physical Knowledge and Machine Learning

      • Nieqing Cao, Abdelrahman Farrag, Jaewoo Kim, Daehan Won, Sang Won Yoon
      Pages 39-46

    7. OS4ML: Open Space for Machine Learning

      • Dennis Rall, Thomas Fraunholz, Tim Köhler, Florian Kratzer, Monika Mayer, Demas Schmorell et al.
      Pages 47-57

    8. Deep Hierarchical Reinforcement Learning CMP Run to Run Control

      • Andy Yendi Tsen, Tzu-Li Chen, Ko-Shu Hsu
      Pages 58-65

    9. A Physics-Informed Machine Learning Model for Mounting Optimization in Printed Circuit Boards

      • Jaewoo Kim, Abdelrahman Farrag, Nieqing Cao, Daehan Won, Yu Jin
      Pages 66-74

    10. Disassembly Work Analysis Using Motion Capture and Machine Learning

      • Taku Hayashi, Koki Karube, Masao Sugi, Tetsuo Yamada
      Pages 75-82

    11. Through the Lens of Explainability: Enhancing Trust in Remaining Useful Life Prognosis Models

      • Kaouther Benguessoum, Raoni Lourenço, Vincent Bourel, Sylvain Kubler
      Pages 83-90

    12. Discovering Dispatching Rules in a Semiconductor Fab Using Interpretable Machine Learning

      • Minsik Kim, Young-Suk Han, Josue Obregon, Jae-Yoon Jung
      Pages 91-97

    13. Digital Twin System Framework for Gripping Deformable Objects with Synthetic Data and Reinforcement Learning

      • Minho Choi, Dongjun Kim, Junhyuck Moon, Minji Kim, Jumyung Um
      Pages 98-106

  3. Cyber-Physical Systems (CPS)

    1. Front Matter

      Pages 107-107
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    2. Setup Operation Time Estimation System for the Adoption of Cyber-Physical Systems in High-Mix Low-Volume Production

      • Kotomichi Matsuno, Yasumasa Hasegawa, Nirmala Liyanaarachchi, Jiahua Weng, Ruriko Watanabe, Yoshitaka Tanimizu et al.
      Pages 109-116

    3. Defining Scalable Data Models for Operational Data Integration in Manufacturing Processes Within the Digital Product Passport Framework Through OPC UA and Asset Administration Shell

      • Samed Ajdinović, Nicolai Maisch, Marcel Dzubba, Armin Lechler, Oliver Riedel
      Pages 117-124

    4. Cybersecurity Awareness in Critical Sectors – a Systematic Literature Review

      • Julie Langedahl Leirmo
      Pages 125-132

    5. Digifacturing: Strategically Redefining Manufacturing for Micro-SMEs

      • Aagnesh Rajan, Aliyu M. Aliyu, Ashish Kumar Sahu, Faiz Iqbal
      Pages 133-142

    6. Designing a Resilient Hybrid-Modeled Digital Twin for Reliable Manufacturing Processes

      • Marcel Wagner, Fabio J. P. Sousa, Ricardo Halla, Orivaldo Vieira de Santana Júnior, Matthias Klar, Jan C. Aurich
      Pages 143-150
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Other volumes

  1. Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order

  2. Flexible Automation and Intelligent Manufacturing: Manufacturing Innovation and Preparedness for the Changing World Order

Editors and Affiliations

  • Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan

    Yi-Chi Wang, Siu Hang Chan, Zih-Huei Wang

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