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Since the term “Industry 4.0” was coined in Germany in 2011, industries worldwide have been investing in the development of smart factories that are more efficient and better adaptive to digital transformation to enhance their service‐oriented and customized‐supply capabilities.

To take Industry 4.0 a step further, Professor Fan‐Tien Cheng proposed the upgraded version of Industry 4.1, core to which is the realization of Zero Defects, a solution taking advantage of the newly developed Intelligent Factory Automation (iFA) System Platform to address the production quality issue that has received relatively scant attention in Industry 4.0. To put into practice Zero Defects as well as in response to the Intelligent Manufacturing Industry Innovation policy of the Taiwan, ROC government, he further established the Intelligent Manufacturing Research Center (iMRC) at National Cheng Kung University (NCKU) in 2018.

As NCKU’s President, I always take great pride in the achievements of all my colleagues and students. In the latest Times Higher Education (THE) Impact Rankings 2020, NCKU is ranked first in Taiwan, ROC, second in the Asia region, and 38^th globally. It excels especially in “Industry, Innovations, and Infrastructure,” one of United Nation’s 17 Sustainable Development Goals (SDGs), and earns the 10^th place worldwide. Professor Cheng’s innovative research has played a critical role in this intense competition because, as I understand it, his Industry 4.1 and Intelligent Manufacturing are key to NCKU’s success in the SDG of “Industry, Innovations, and Infrastructure” and NCKU’s continuous leadership in the Engineering field.

As NCKU is accelerating its research momentum, especially in disciplines of traditional strengths like Intelligent Manufacturing and Engineering, I am glad that Professor Cheng is willing to share his valuable research and industry‐university cooperation experiences in this book, one that will become an important reference not only for students but professors and researchers alike, and not only at NCKU but in industries and higher education worldwide whose focus is Intelligent Manufacturing.

This book not only details the essentials that have paved the way from Industry 4.0 to Industry 4.1 but also provides numerous practical industrial application cases in different manufacturing industries. It thus offers readers a comprehensive perspective of what they are and will be facing in the industry. I am sure this book is fundamental – a must‐have indeed – for researchers, engineers, and focused students in the fields of, among others, Intelligent Manufacturing and Industry 4.1.

Huey‐Jen Su

President, National Cheng Kung University (NCKU)

Industry 4.0 is a confluence of trends and technologies for the fourth industrial revolution. It has been “pushed” by the digital revolution over the past many decades and the recent Internet of Things (IoT); and “pulled” by demand from customers for high quality and customized products at reasonable prices and lead times. With (i) the ubiquitous connection and interaction of machines, things, and people; (ii) the integration of cyber and physical systems; and (iii) the emerging of disruptive technologies such as big data, machine learning, artificial intelligence, 3D printing and robotics, the ways we design and manufacture products and provide services are undergoing fundamental changes.

Although much R&D progress has been made, industries have been slow to develop effective holistic Industry 4.0 strategies. From a recent survey of 2000 C‐suite executives by Deloitte (https://www2.deloitte.com/content/dam/insights/us/articles/us32959‐industry‐4‐0/DI_Industry4.0.pdf), only 10% of the executives surveyed indicated they had long‐range strategies to leverage new technologies that reach across their organizations. This is not surprising since creating and implementing holistic Industry 4.0 strategies are complicated, and require deep understanding, sharp vision, inspirational leadership, and resolute persistence. Among those with comprehensive Industry 4.0 strategies, the results have been impressive: 73% of those with a strategy report success in protecting their businesses from disruption, versus 12% of those with more scattershot approaches; 61% of those with Industry 4.0 strategies report that they have developed innovative products and services, versus 12% of those lacking strategies; and 60% of those with Industry 4.0 strategies report that they have found growth opportunities for existing products and services, versus 8% of those lacking strategies. Those companies with strategies also are growing more financially, and making more progress investing in technologies that have a positive societal impact.

Consider specifically a key area of Industry 4.0, the quality of products and processes. It is well‐known that a host of methods and processes such as Statistical Process Control (SPC), Zero Defect Manufacturing (ZDM), Six Sigma Methodologies, Preventive Maintenance (PM), Continuous Improvement (Kaizen), Total Quality Management (TQM), etc., have been around for years and are contributing to the quality of products and processes. Integrating the digital revolution, the Internet of Things, big data, machine learning, and artificial intelligence to raise the quality of products and processes to a new level and with practical and scalable implementations, however, remains a major challenge for scholars, practitioners, and C‐suite executives alike.

This book “Industry 4.1 – Intelligent Manufacturing with Zero Defects” focuses on improving the quality of products and processes, and is the culmination of the brilliant but down‐to‐the‐earth efforts of the team led by Professor Fan‐Tien Cheng over the past many years. The efforts started with Virtual Metrology. In view of the incompatible paces of fast production and slow metrology, 100% inspection is impossible, and sample inspection has been the practice. With the advancements in sensing, metrology, analytics and Industry 4.0 technologies, the team innovatively integrated physical metrology with its cyber counterparts, Virtual Metrology (VM). The resulting Automatic Virtual Metrology (AVM) system presented in this book is capable of predicting the quality of a product based on machine parameters, sensor data in the production equipment, and off‐line sampling measurements. It also provides on‐line and real‐time total inspection of all work pieces to timely detect abnormalities during production. As a result, the sampling rate of real measurements can be cut down, the production costs can be reduced, and the goal of nearly zero defects of deliverables can be achieved.

Effective implementation of Automatic Virtual Metrology, however, is not easy, especially if we want it to be scalable to large factories and transferrable to other companies and other industries. Major infrastructure needs to be established efficiently and flexibly. Based on the team’s successful research, development, implementation, and redeployment at many factories and across multiple industries, this book methodically presents the essential infrastructure components. The content includes data collection and management and feature extraction; communication standards; computation infrastructure of cloud, edge, Internet of Things and big data; container‐related software development, deployment, and management technologies of Docker and Kubernetes; the overall architecture of the advanced manufacturing “Cloud of Things” framework, and the specific design and implementation of key components such as cyber‐physical agents, big data analytics application platform, the automated construction scheme for manufacturing services, and AVM and other servers.

Extending the ideas, methods, and infrastructure presented above, the book then focuses on Intelligent Predictive Maintenance (IPM). Predictive maintenance, sometimes known as “condition‐based maintenance,” is to monitor the performance and conditions of equipment during operations to predict when equipment performance is deteriorating and when equipment is going to fail, followed by scheduled or corrective maintenance. Intelligent Predictive Maintenance presented in this book detects the abnormality of key components of manufacturing tools based on advanced fault detection and classification techniques and predicts their Remaining Useful Lives (RUL) using time series prediction algorithms. Factory‐wide implementation is then discussed to improve tool availability and prevent unscheduled down of manufacturing tools.

Since modern manufacturing facilities are generally capital intensive, it is critical to have consistently high yields to justify the investment and to have a positive bottom line. Intelligent Yield Management (IYM) presented in this book is a closely related cousin of Intelligent Predictive Maintenance, with the purpose to effectively detect root causes that affect the yield. It consists of data collection and management; statistical, big data, and machine learning tools for defect and yield analysis; and timely resolution of issues discovered while maintaining the requisite quality and reliability standards. The kernel of the above is the “Key‐variable Search Algorithm” (KSA), which includes new root‐cause search methods for solving the high‐dimensional variable selection problem, and modules for checking the quality of input data and for evaluating the reliability of search results.

The current Industry 4.0‐related technologies emphasize productivity improvement but not on quality enhancement. They can have the faith of achieving nearly Zero‐Defect Manufacturing but without effective methods to achieve it. By developing and implementing the novel methods, technologies, and infrastructure presented above, zero defects of products can be effectively achieved. This is what is defined as Industry 4.1 in the book. The actual deployment cases in seven industries, including flat panel display, semiconductor, solar cell, automobile, aerospace, carbon fiber, and blow molding, are presented in the final Chapter 11. The ingenuity is outstanding, the effort is tremendous, and the impact is far‐reaching and long‐lasting.

Since many acronyms are used throughout the book, readers are advised to have Abbreviation Lists handy when reading the book. Beyond this point, I sincerely hope that you enjoy reading the book, and delightfully discover the wonderful world of Industry 4.1.

Peter B. Luh

Board of Trustees Distinguished Professor

SNET Professor of Communications & Information Technologies

Dept. of Electrical & Computer Engineering

University of Connecticut

Since Germany brought up Industry 4.0 in 2012, the trend of Intelligent Manufacturing has boomed globally. By integrating the innovative information‐and‐communication technologies such as IoT, Cloud, Big Data, AI, etc., various Cyber‐Physical Systems are developed to promote factory process optimization, yield improvement, efficiency enhancement, and cost reduction. Besides, in response to changes in consumers' habits, Zero Defects, High Variety Low Volume, and Rapid Change have become mandatory indicators for Intelligent Manufacturing.

Advanced Semiconductor Engineering Inc. (ASE), is the leading provider of independent semiconductor manufacturing services in assembly and test. ASE develops and offers complete turnkey solutions in IC packaging, design and production of interconnect materials, front‐end engineering test, wafer probing, and final test. In 2011, ASE started to vigorously promote Intelligent Manufacturing and established over 15 lights‐out factories in response to changes in the global industrial environment. Moreover, ASE also collaborated with various top universities in Taiwan, ROC for R&D of IoT, Cloud, Big Data, and AI technologies, which have cultivated more than 400 professionals in the automation field via co‐hosting educational trainings and industry programs to improve the automation capability within ASE.

ASE began the industry‐university collaboration with Prof. Fan‐Tien Cheng in 2014. Initially, we implemented Automatic Virtual Metrology (AVM) to achieve total inspection in an efficient and economic way so as to reduce the measurement cost. The project was a great success, and ever since then Prof. Cheng has become one of our major collaborators. The subsequent cooperation includes Intelligent Yield Management (IYM), Intelligent Predictive Maintenance (IPM), Advanced Manufacturing Cloud of Things (AMCoT), and Scheduling, which can be said to be the practical applications of all the research essence of Prof. Cheng on the production line.

The Industry 4.1 proposed by Prof. Cheng aims at Zero Defects, it applies AVM to accomplish total inspection and utilizes IYM to find the root causes of a yield loss. In addition to enhancing production efficiency, it also improves product yield and makes products close to Zero Defects, which is a great step forward in the realm of Industry 4.0.

Although Intelligent Manufacturing is a hot subject nowadays, it is challenging for the enterprises to actually carry it out; many enterprises still struggle to realize the vision of Intelligent Manufacturing. The implementation of novel technologies isn’t the only core for Intelligent Manufacturing, the shaping of the ecological chain of the automation industry and the cultivation of talents are also important factors.

As the development of hardware like sensor, microcontroller, Automatic Material Handling System (AMHS), and robot is coming to a mature state gradually, the focus of Intelligent Manufacturing has shifted to the software. The cloud‐based technologies such as Big Data and AI application modules draw more attention to the researchers and professionals at present. The technologies introduced in this book are a series of automation technologies developed upon IoT, Cloud, Big Data, and AI. Aside from explaining through the theories in detail, it also includes hands‐on application cases in various industries. This is a book worth reading for both industrial professionals and scholars, and I highly recommend these materials for Intelligent Manufacturing education.

Michael Lee

Vice GM of ASEKH MIS Center

Former Plant Manager of ASE Testing and Wafer Bumping Plants

Former Executive Secretary of ASE Security Committee

Former Committee Member of ASE Automation Committee

By the time we established the Precision Machinery Research & Development Center (PMC) in 1993, the board of directors agreed to my suggestion of focusing our efforts on two fields of expertise, IT and total quality control, to speed up our competitiveness on machine tools made in Taiwan, ROC.

Back then, we were totally unaware that IT could even be developed outside our expertise realm to missions such as Apollo 13 by NASA through digital twins.

However, we began to appreciate our choice of focusing on IT when the U.S. National Science Foundation announced the development of Cyber‐Physical Systems in 2006. I am glad to report that PMC was the first organization in Taiwan, ROC to join the IMS Center founded by Prof. Jay Lee while he was a professor at the University of Wisconsin‐Milwaukee before he moved to Cincinnati. Our affiliation with the IMS center guided us to recognize the worth of Industry 4.0 initiated by Germany later in 2013.

In the meantime, virtual metrology (VM) has emerged as a key tool for controlling complex process such as semiconductor device manufacturing. VM utilizes mathematical models to estimate quality variables that may be difficult or expensive to measure using readily available process information.

Professor Fan‐Tien Cheng, the Editor and leading author of this book, realized that if VM can be fully automated, the quality of a process can be monitored without processing interruption. His team applied their Automatic Virtual Metrology (AVM) to the chemical vapor deposition for a thin film transistor liquid display manufacturing process in Taiwan, ROC. Since AVM allows the possibility of acquiring Zero‐Defects production, he claimed that AVM should be coined into Industry 4.1, i.e., one step ahead of the original Industry 4.0.

In 2013, his team began to expand AVM into the semiconductor packaging process in cooperation with the ASE group. The success of AVM implementation was then followed by the integration of Intelligent Predictive Maintenance (IPM) and Intelligent Yield Management (IYM) into their production lines through the Intelligent Factory Automation (iFA) platform Professor Cheng developed.

In the meantime, the iFA platform was applied to the machining of aluminum alloy wheels at FEMCO Machine Tool Manufacturing Co., Ltd. in Chiayi, Taiwan, ROC. Their success has helped FEMCO to export numerous similar systems to worldwide automobile wheel manufactures. In addition to the semiconductor and automotive industries, his team has deployed these systems constituting Industry 4.1 to many other manufacturing enterprises such as TFT‐LCD, solar cell, jet engine case machining, plastic bottle blow molding, machine tools, 3D metal printing, and thermal process for making carbon fibers.

Professor Cheng and his team aim to upgrade the manufacturing industries to achieve Zero Defects through the implementation of Industry 4.1. This book is the embodiment of their dedication on the advanced technologies that pave the way from Industry 4.0 to Industry 4.1. I highly recommend this practical book to those who are interested in or preparing themselves to take parts in the manufacturing industries, they can see a whole picture of the industry evolvement with actual on‐site application cases.

Kuo‐Chin Chuang

Ph.D. of Materials Sci. and Eng., Massachusetts Institute of Technology (MIT)

Honorary Chairman, Taiwan Association of Machinery Industry (TAMI)

Former Chairman, Far East Machinery Co, Ltd. (FEMCO)

Chairman, LOGICOM, Inc.