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Industry 4.1


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       Library of Congress Cataloging‐in‐Publication Data is applied for

      Hardback: 9781119739890

      Cover Design: Wiley

      Cover Image: © Fan‐Tien Cheng

      Editor Biography

      Soon after Fan‐Tien Cheng graduated from the department of Electrical Engineering of National Cheng Kung University (NCKU) in 1976, he got in the Chung Shan Institute of Science and Technology (CSIST), Taiwan, ROC, serving as Research Assistant at the most basic level and then got promoted to Senior Scientist in 19 years. Then he went back to NCKU to start his teaching career and devoted the knowledge and practices he had learned in CSIST to the research domains of production improvement, manufacturing automation, and e‐manufacturing for industries such as semiconductor, TFT–LCD, solar cell, machine tool, and aerospace to help achieve the goal of enhancing the industry competitiveness by successfully improving manufacturing processes and lowering production cost.

      Professor Cheng has devoted himself to the academic research and industrial applications of the Intelligent Manufacturing and Industry 4.0 for the past decades and his accomplishments are eminent. Among them, the academic and applied research of Automatic Virtual Metrology (AVM) are especially unmatched worldwide. More than 40 journal papers related to VM had won him dozens of patents from Taiwan ROC, USA, Japan, China, Germany, and Korea; and 54 technology transfers had been successfully executed on several high‐tech industries such as semiconductor (TSMC, UMC, ASE, and SUMCO), TFT–LCD (Innolux and CPT), solar cell (Motech); and traditional industries like aerospace (AIDC), machine tool industry (FEMCO/FATEK), blow molding machine (ChumPower), and carbon fiber (FPC), as well as foundations, constituted as a juristic person (ITRI and MIRDC).

      Some of Professor Cheng’s honors and awards include 2011 Award for Outstanding Contributions in Science and Technology, Executive Yuan, Taiwan, ROC, three times ofMinistry of Science and Technology(MoST) Outstanding Research Award (2006, 2009, 2013), three times of the National Invention and Creation Award ofMinistry of Economic Affairs(MoEA) (2011, 2012, 2018), University‐Industry Economic Contribution Award from MoEA, Industry‐University Cooperation Award for College Teachers, Ministry of Education (MoE), NCKU Chair Professor since January 2009, 17th TECO Award from TECO Technology Foundation, 2010, 2013 IEEE Inaba Technical Award for Innovation Leading to Production (for contributions to the development of the AVM System), 2014 Outstanding Research Award of Pan Wen Yuan Foundation, and 2015 20th Outstanding Achievement Award of The Phi Tau Phi Scholastic Honor Society. Moreover, Professor Cheng won IEEE Fellow since January 2008, two times of IEEE ICRA Best Automation Paper Award (1999 and 2013) as well as CASE 2017 Best Application Paper Award. He is currently in his second‐term of President of Chinese Institute of Automation Engineers (CIAE) since 2017. Besides, he is the Senior Editor of the IEEE T‐ASE since October 2017. Furthermore, he is honored to be the IEEE CASE Conference Steering Committee Chair since September 2020.

      List of Contributors

      1 Fan‐Tien Cheng, Director/Chair Professor, Intelligent Manufacturing Research Center/Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan, ROC

      2 Min‐Hsiung Hung, Professor, Department of Computer Science and Information Engineering, Chinese Culture University, Taipei, Taiwan, ROC

      3 Yu‐Chen Chiu, Specialist, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      4 Yu‐Ming Hsieh, Associate Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      5 Hao Tieng, Associate Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      6 Haw‐Ching Yang, Professor, Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan, ROC

      7 Yu‐Chuan Lin, Secretary General, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      8 Chin‐Yi Lin, Postdoctoral Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      9 Chao‐Chun Chen, Professor, Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan, ROC

      10 Hung‐Chang Hsiao, Professor, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, ROC

      11 Kuan‐Chou Lai, Professor, Department of Computer Science, National Taichung University of Education, Taichung, Taiwan, ROC

      12 Hsien‐Cheng Huang, Deputy Director, e‐Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      13 Yu‐Yong Li, Postdoctoral Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

      Preface

      In the era of global competition, improving productivity and increasing yield of the manufacturing industries through information and communication as well as cloud computing technologies, big data analytics, and cyber‐physical systems (CPS) are the common goals for the manufacturers worldwide. For instance, Germany proposed Industry 4.0 in hopes to construct Smart Factory so as to enhance its global competitiveness and continue to take the lead in manufacturing. The Advanced Manufacturing Partnership issued by the United States aimed to regain the leadership in international manufacturing competitiveness for attracting the manufacturing industries back to the United States. Chinese government brought out the plan called “Made in China 2025” in 2015, where the guidelines and strategies of becoming one of the countries with strong manufacturing power by 2025 were clearly stated. Facing the United States‐China trade war that began in 2018, even though Chinese government stopped to mention Made in China 2025 in public to not intensify the conflict, they claimed that their goals of enhancing Intelligent Manufacturing have not been changed. Adjustments on the strategies in accordance with the international trend would be made, which is considered as the new version of Made in China 2025.

      The current Industry 4.0 related technologies emphasize on productivity improvement but not on quality enhancement; in other words, they can only keep the faith of achieving nearly Zero‐Defects (ZD) state without realizing this goal. The key reason for this inability is the lack of an affordable