Industry 4.1 (eBook, ePUB)

Intelligent Manufacturing with Zero Defects
Redaktion: Cheng, Fan-Tien

• Format: ePub

Produktbeschreibung

Industry 4.1 Intelligent Manufacturing with Zero Defects Discover the future of manufacturing with this comprehensive introduction to Industry 4.0 technologies from a celebrated expert in the field Industry 4.1: Intelligent Manufacturing with Zero Defects delivers an in-depth exploration of the functions of intelligent manufacturing and its applications and implementations through the Intelligent Factory Automation (iFA) System Platform. The book's distinguished editor offers readers a broad range of resources that educate and enlighten on topics as diverse as the Internet of Things, edge computing, cloud computing, and cyber-physical systems. You'll learn about three different advanced prediction technologies: Automatic Virtual Metrology (AVM), Intelligent Yield Management (IYM), and Intelligent Predictive Maintenance (IPM). Different use cases in a variety of manufacturing industries are covered, including both high-tech and traditional areas. In addition to providing a broad view of intelligent manufacturing and covering fundamental technologies like sensors, communication standards, and container technologies, the book offers access to experimental data through the IEEE DataPort. Finally, it shows readers how to build an intelligent manufacturing platform called an Advanced Manufacturing Cloud of Things (AMCoT). Readers will also learn from: * An introduction to the evolution of automation and development strategy of intelligent manufacturing * A comprehensive discussion of foundational concepts in sensors, communication standards, and container technologies * An exploration of the applications of the Internet of Things, edge computing, and cloud computing * The Intelligent Factory Automation (iFA) System Platform and its applications and implementations * A variety of use cases of intelligent manufacturing, from industries like flat-panel, semiconductor, solar cell, automotive, aerospace, chemical, and blow molding machine Perfect for researchers, engineers, scientists, professionals, and students who are interested in the ongoing evolution of Industry 4.0 and beyond, Industry 4.1: Intelligent Manufacturing with Zero Defects will also win a place in the library of laypersons interested in intelligent manufacturing applications and concepts. Completely unique, this book shows readers how Industry 4.0 technologies can be applied to achieve the goal of Zero Defects for all product

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 560
• Erscheinungstermin: 19. Oktober 2021
• Englisch
• ISBN-13: 9781119739913
• Artikelnr.: 62803208

Autorenporträt

Fan-Tien Cheng, PhD, is Director of the Intelligent Manufacturing Research Center at the National Cheng Kung University in Taiwan, ROC. He received his doctorate in Electrical Engineering from the Ohio State University in 1989. His research foci are on topics related to intelligent manufacturing and Industry 4.0.

Inhaltsangabe

Editor Biography xv

List of Contributors xvii

Preface xix

Acknowledgments xxi

Foreword xxiii

1 Evolution of Automation and Development Strategy of Intelligent Manufacturing with Zero Defects 1
Fan-Tien Cheng

1.1 Introduction 1

1.2 Evolution of Automation 1

1.2.1 e-Manufacturing 1

1.2.1.1 Manufacturing Execution System (MES) 3

1.2.1.2 Supply Chain (SC) 6

1.2.1.3 Equipment Engineering System (EES) 7

1.2.1.4 Engineering Chain (EC) 9

1.2.2 Industry 4.0 10

1.2.2.1 Definition and Core Technologies of Industry 4.0 10

1.2.2.2 Migration from e-Manufacturing to Industry 4.0 12

1.2.2.3 Mass Customization 12

1.2.3 Zero Defects - Vision of Industry 4.1 13

1.2.3.1 Two Stages of Achieving Zero Defects 14

1.3 Development Strategy of Intelligent Manufacturing with Zero Defects 14

1.3.1 Five-Stage Strategy of Yield Enhancement and Zero-Defects Assurance 15

1.4 Conclusion 18

Appendix 1.A - Abbreviation List 18

References 20

2 Data Acquisition and Preprocessing 25
Hao Tieng, Haw-Ching Yang, and Yu-Yong Li

2.1 Introduction 25

2.2 Data Acquisition 26

2.2.1 Process Data Acquisition 26

2.2.1.1 Sensing Signals Acquisition 26

2.2.1.2 Manufacturing Parameters Acquisition 35

2.2.2 Metrology Data Acquisition 36

2.3 Data Preprocessing 37

2.3.1 Segmentation 37

2.3.2 Cleaning 38

2.3.2.1 Trend Removal 39

2.3.2.2 Wavelet Thresholding 41

2.3.3 Feature Extraction 43

2.3.3.1 Time Domain 43

2.3.3.2 Frequency Domain 47

2.3.3.3 Time-Frequency Domain 49

2.3.3.4 Autoencoder 52

2.4 Case Studies 53

2.4.1 Detrending of the Thermal Effect in Strain Gauge Data 53

2.4.2 Automated Segmentation of Signal Data 55

2.4.3 Tool State Diagnosis 57

2.4.4 Tool Diagnosis using Loading Data 61

2.5 Conclusion 64

Appendix 2.A - Abbreviation List 64

Appendix 2.B - List of Symbols in Equations 65

References 67

3 Communication Standards 69
Fan-Tien Cheng, Hao Tieng, and Yu-Chen Chiu

3.1 Introduction 69

3.2 Communication Standards of the Semiconductor Equipment 69

3.2.1 Manufacturing Portion 69

3.2.1.1 SEMI Equipment Communication Standard I (SECS-I) (SEMI E4) 70

3.2.1.2 SEMI Equipment Communication Standard II (SECS-II) (SEMI E5) 75

3.2.1.3 Generic Model for Communications and Control of Manufacturing Equipment (GEM) (SEMI E30) 81

3.2.1.4 High-Speed SECS Message Services (HSMS) (SEMI E37) 84

3.2.2 Engineering Portion (Interface A) 91

3.2.2.1 Authentication & Authorization (A&A) (SEMI E132) 93

3.2.2.2 Common Equipment Model (CEM) (SEMI E120) 95

3.2.2.3 Equipment Self-Description (EqSD) (SEMI E125) 95

3.2.2.4 Equipment Data Acquisition (EDA) Common Metadata (ECM) (SEMI E164) 98

3.2.2.5 Data Collection Management (DCM) (SEMI E134) 102

3.3 Communication Standards of the Industrial Devices and Systems 107

3.3.1 Historical Roadmaps of Classic Open Platform Communications (OPC) and OPC Unified Architecture (OPC-UA) Protocols 108

3.3.1.1 Classic OPC 108

3.3.1.2 OPC-UA 109

3.3.2 Fundamentals of OPC-UA 110

3.3.2.1 Requirements 110

3.3.2.2 Foundations 111

3.3.2.3 Specifications 112

3.3.2.4 System Architecture 112

3.3.3 Example of Intelligent Manufacturing Hierar