{"product_id":"industry-4-1-9781119739890","title":"Industry 4.1","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eIndustry 4.1 Intelligent Manufacturing with Zero Defects\u003c\/b\u003e \u003cp\u003e\u003cb\u003eDiscover the future of manufacturing with this comprehensive introduction to Industry 4.0 technologies from a celebrated expert in the field\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eIndustry 4.1: Intelligent Manufacturing with Zero Defects\u003c\/i\u003e 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.  \u003c\/p\u003e\u003cp\u003eYou'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. \u003c\/p\u003e\u003cp\u003eIn add\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eEditor Biography xv\u003c\/p\u003e \u003cp\u003eList of Contributors xvii\u003c\/p\u003e \u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003eAcknowledgments xxi\u003c\/p\u003e \u003cp\u003eForeword xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Evolution of Automation and Development Strategy of Intelligent Manufacturing with Zero Defects \u003c\/b\u003e\u003cb\u003e1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFan-Tien Cheng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Evolution of Automation 1\u003c\/p\u003e \u003cp\u003e1.2.1 e-Manufacturing 1\u003c\/p\u003e \u003cp\u003e1.2.1.1 Manufacturing Execution System (MES) 3\u003c\/p\u003e \u003cp\u003e1.2.1.2 Supply Chain (SC) 6\u003c\/p\u003e \u003cp\u003e1.2.1.3 Equipment Engineering System (EES) 7\u003c\/p\u003e \u003cp\u003e1.2.1.4 Engineering Chain (EC) 9\u003c\/p\u003e \u003cp\u003e1.2.2 Industry 4.0 10\u003c\/p\u003e \u003cp\u003e1.2.2.1 Definition and Core Technologies of Industry 4.0 10\u003c\/p\u003e \u003cp\u003e1.2.2.2 Migration from e-Manufacturing to Industry 4.0 12\u003c\/p\u003e \u003cp\u003e1.2.2.3 Mass Customization 12\u003c\/p\u003e \u003cp\u003e1.2.3 Zero Defects – Vision of Industry 4.1 13\u003c\/p\u003e \u003cp\u003e1.2.3.1 Two Stages of Achieving Zero Defects 14\u003c\/p\u003e \u003cp\u003e1.3 Development Strategy of Intelligent Manufacturing with Zero Defects 14\u003c\/p\u003e \u003cp\u003e1.3.1 Five-Stage Strategy of Yield Enhancement and Zero-Defects Assurance 15\u003c\/p\u003e \u003cp\u003e1.4 Conclusion 18\u003c\/p\u003e \u003cp\u003eAppendix 1.A – Abbreviation List 18\u003c\/p\u003e \u003cp\u003eReferences 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Data Acquisition and Preprocessing \u003c\/b\u003e\u003cb\u003e25\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHao Tieng, Haw\u003c\/i\u003e-\u003ci\u003eChing Yang, and Yu-Yong Li\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 25\u003c\/p\u003e \u003cp\u003e2.2 Data Acquisition 26\u003c\/p\u003e \u003cp\u003e2.2.1 Process Data Acquisition 26\u003c\/p\u003e \u003cp\u003e2.2.1.1 Sensing Signals Acquisition 26\u003c\/p\u003e \u003cp\u003e2.2.1.2 Manufacturing Parameters Acquisition 35\u003c\/p\u003e \u003cp\u003e2.2.2 Metrology Data Acquisition 36\u003c\/p\u003e \u003cp\u003e2.3 Data Preprocessing 37\u003c\/p\u003e \u003cp\u003e2.3.1 Segmentation 37\u003c\/p\u003e \u003cp\u003e2.3.2 Cleaning 38\u003c\/p\u003e \u003cp\u003e2.3.2.1 Trend Removal 39\u003c\/p\u003e \u003cp\u003e2.3.2.2 Wavelet Thresholding 41\u003c\/p\u003e \u003cp\u003e2.3.3 Feature Extraction 43\u003c\/p\u003e \u003cp\u003e2.3.3.1 Time Domain 43\u003c\/p\u003e \u003cp\u003e2.3.3.2 Frequency Domain 47\u003c\/p\u003e \u003cp\u003e2.3.3.3 Time–Frequency Domain 49\u003c\/p\u003e \u003cp\u003e2.3.3.4 Autoencoder 52\u003c\/p\u003e \u003cp\u003e2.4 Case Studies 53\u003c\/p\u003e \u003cp\u003e2.4.1 Detrending of the Thermal Effect in Strain Gauge Data 53\u003c\/p\u003e \u003cp\u003e2.4.2 Automated Segmentation of Signal Data 55\u003c\/p\u003e \u003cp\u003e2.4.3 Tool State Diagnosis 57\u003c\/p\u003e \u003cp\u003e2.4.4 Tool Diagnosis using Loading Data 61\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 64\u003c\/p\u003e \u003cp\u003eAppendix 2.A – Abbreviation List 64\u003c\/p\u003e \u003cp\u003eAppendix 2.B – List of Symbols in Equations 65\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Communication Standards \u003c\/b\u003e\u003cb\u003e69\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFan-Tien Cheng, Hao Tieng, and Yu-Chen Chiu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 69\u003c\/p\u003e \u003cp\u003e3.2 Communication Standards of the Semiconductor Equipment 69\u003c\/p\u003e \u003cp\u003e3.2.1 Manufacturing Portion 69\u003c\/p\u003e \u003cp\u003e3.2.1.1 SEMI Equipment Communication Standard I (SECS-I) (SEMI E4) 70\u003c\/p\u003e \u003cp\u003e3.2.1.2 SEMI Equipment Communication Standard II (SECS-II) (SEMI E5) 75\u003c\/p\u003e \u003cp\u003e3.2.1.3 Generic Model for Communications and Control of Manufacturing Equipment (GEM) (SEMI E30) 81\u003c\/p\u003e \u003cp\u003e3.2.1.4 High-Speed SECS Message Services (HSMS) (SEMI E37) 84\u003c\/p\u003e \u003cp\u003e3.2.2 Engineering Portion (Interface A) 91\u003c\/p\u003e \u003cp\u003e3.2.2.1 Authentication \u0026amp; Authorization (A\u0026amp;A) (SEMI E132) 93\u003c\/p\u003e \u003cp\u003e3.2.2.2 Common Equipment Model (CEM) (SEMI E120) 95\u003c\/p\u003e \u003cp\u003e3.2.2.3 Equipment Self-Description (EqSD) (SEMI E125) 95\u003c\/p\u003e \u003cp\u003e3.2.2.4 Equipment Data Acquisition (EDA) Common Metadata (ECM) (SEMI E164) 98\u003c\/p\u003e \u003cp\u003e3.2.2.5 Data Collection Management (DCM) (SEMI E134) 102\u003c\/p\u003e \u003cp\u003e3.3 Communication Standards of the Industrial Devices and Systems 107\u003c\/p\u003e \u003cp\u003e3.3.1 Historical Roadmaps of Classic Open Platform Communications (OPC) and OPC Unified Architecture (OPC-UA) Protocols 108\u003c\/p\u003e \u003cp\u003e3.3.1.1 Classic OPC 108\u003c\/p\u003e \u003cp\u003e3.3.1.2 OPC-UA 109\u003c\/p\u003e \u003cp\u003e3.3.2 Fundamentals of OPC-UA 110\u003c\/p\u003e \u003cp\u003e3.3.2.1 Requirements 110\u003c\/p\u003e \u003cp\u003e3.3.2.2 Foundations 111\u003c\/p\u003e \u003cp\u003e3.3.2.3 Specifications 112\u003c\/p\u003e \u003cp\u003e3.3.2.4 System Architecture 112\u003c\/p\u003e \u003cp\u003e3.3.3 Example of Intelligent Manufacturing Hierarchy Applying OPC-UA Protocol 119\u003c\/p\u003e \u003cp\u003e3.3.3.1 Equipment Application Program (EAP) Server 121\u003c\/p\u003e \u003cp\u003e3.3.3.2 Use Cases of Data Manipulation 122\u003c\/p\u003e \u003cp\u003e3.3.3.3 Sequence Diagrams of Data Manipulation 123\u003c\/p\u003e \u003cp\u003e3.4 Conclusion 125\u003c\/p\u003e \u003cp\u003eAppendix 3.A – Abbreviation List 125\u003c\/p\u003e \u003cp\u003eReferences 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Cloud Computing, Internet of Things (IoT), Edge Computing, and Big Data Infrastructure \u003c\/b\u003e\u003cb\u003e129\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHung-Chang Hsiao, Min-Hsiung Hung, Chao-Chun Chen, and Yu-Chuan Lin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 129\u003c\/p\u003e \u003cp\u003e4.2 Cloud Computing 131\u003c\/p\u003e \u003cp\u003e4.2.1 Essentials of Cloud Computing 131\u003c\/p\u003e \u003cp\u003e4.2.2 Cloud Service Models 132\u003c\/p\u003e \u003cp\u003e4.2.3 Cloud Deployment Models 134\u003c\/p\u003e \u003cp\u003e4.2.4 Cloud Computing Applications in Manufacturing 137\u003c\/p\u003e \u003cp\u003e4.2.5 Summary 142\u003c\/p\u003e \u003cp\u003e4.3 IoT and Edge Computing 142\u003c\/p\u003e \u003cp\u003e4.3.1 Essentials of IoT 142\u003c\/p\u003e \u003cp\u003e4.3.2 Essentials of Edge Computing 146\u003c\/p\u003e \u003cp\u003e4.3.3 Applications of IoT and Edge Computing in Manufacturing 148\u003c\/p\u003e \u003cp\u003e4.3.4 Summary 150\u003c\/p\u003e \u003cp\u003e4.4 Big Data Infrastructure 150\u003c\/p\u003e \u003cp\u003e4.4.1 Application Demands 150\u003c\/p\u003e \u003cp\u003e4.4.2 Core Software Stack Components 152\u003c\/p\u003e \u003cp\u003e4.4.3 Bridging the Gap between Core Software Stack Components and Applications 153\u003c\/p\u003e \u003cp\u003e4.4.3.1 Hadoop Data Service (HDS) 153\u003c\/p\u003e \u003cp\u003e4.4.3.2 Distributed R Language Computing Service (DRS) 156\u003c\/p\u003e \u003cp\u003e4.4.4 Summary 159\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 159\u003c\/p\u003e \u003cp\u003eAppendix 4.A – Abbreviation List 160\u003c\/p\u003e \u003cp\u003eAppendix 4.B – List of Symbols in Equations 162\u003c\/p\u003e \u003cp\u003eReferences 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Docker and Kubernetes \u003c\/b\u003e\u003cb\u003e169\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eChao-Chun Chen, Min-Hsiung Hung, Kuan-Chou Lai, and Yu-Chuan Lin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 169\u003c\/p\u003e \u003cp\u003e5.2 Fundamentals of Docker 173\u003c\/p\u003e \u003cp\u003e5.2.1 Docker Architecture 173\u003c\/p\u003e \u003cp\u003e5.2.1.1 Docker Engine 174\u003c\/p\u003e \u003cp\u003e5.2.1.2 High-Level Docker Architecture 174\u003c\/p\u003e \u003cp\u003e5.2.1.3 Architecture of Linux Docker Host 176\u003c\/p\u003e \u003cp\u003e5.2.1.4 Architecture of Windows Docker Host 177\u003c\/p\u003e \u003cp\u003e5.2.1.5 Architecture of Windows Server Containers 177\u003c\/p\u003e \u003cp\u003e5.2.1.6 Architecture of Hyper-V Containers 178\u003c\/p\u003e \u003cp\u003e5.2.2 Docker Operational Principles 178\u003c\/p\u003e \u003cp\u003e5.2.2.1 Docker Image 178\u003c\/p\u003e \u003cp\u003e5.2.2.2 Dockerfile 179\u003c\/p\u003e \u003cp\u003e5.2.2.3 Docker Container 183\u003c\/p\u003e \u003cp\u003e5.2.2.4 Container Network Model 184\u003c\/p\u003e \u003cp\u003e5.2.2.5 Docker Networking 185\u003c\/p\u003e \u003cp\u003e5.2.3 Illustrative Applications of Docker 187\u003c\/p\u003e \u003cp\u003e5.2.3.1 Workflow of Building, Shipping, and Deploying a Containerized Application 188\u003c\/p\u003e \u003cp\u003e5.2.3.2 Deployment of a Docker Container Running a Linux Application 189\u003c\/p\u003e \u003cp\u003e5.2.3.3 Deployment of a Docker Container Running a Windows Application 191\u003c\/p\u003e \u003cp\u003e5.2.4 Summary 194\u003c\/p\u003e \u003cp\u003e5.3 Fundamentals of Kubernetes 195\u003c\/p\u003e \u003cp\u003e5.3.1 Kubernetes Architecture 195\u003c\/p\u003e \u003cp\u003e5.3.1.1 Kubernetes Control Plane Node 195\u003c\/p\u003e \u003cp\u003e5.3.1.2 Kubernetes Worker Nodes 197\u003c\/p\u003e \u003cp\u003e5.3.1.3 Kubernetes Objects 199\u003c\/p\u003e \u003cp\u003e5.3.2 Kubernetes Operational Principles 200\u003c\/p\u003e \u003cp\u003e5.3.2.1 Deployment 200\u003c\/p\u003e \u003cp\u003e5.3.2.2 High Availability and Self-Healing 200\u003c\/p\u003e \u003cp\u003e5.3.2.3 Ingress 202\u003c\/p\u003e \u003cp\u003e5.3.2.4 Replication 204\u003c\/p\u003e \u003cp\u003e5.3.2.5 Scheduler 204\u003c\/p\u003e \u003cp\u003e5.3.2.6 Autoscaling 205\u003c\/p\u003e \u003cp\u003e5.3.3 Illustrative Applications of Kubernetes 205\u003c\/p\u003e \u003cp\u003e5.3.4 Summary 209\u003c\/p\u003e \u003cp\u003e5.4 Conclusion 209\u003c\/p\u003e \u003cp\u003eAppendix 5.A – Abbreviation List 210\u003c\/p\u003e \u003cp\u003eReferences 211\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Intelligent Factory Automation (iFA) System Platform \u003c\/b\u003e\u003cb\u003e215\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFan-Tien Cheng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 215\u003c\/p\u003e \u003cp\u003e6.2 Architecture Design of the Advanced Manufacturing Cloud of Things (AMCoT) Framework 215\u003c\/p\u003e \u003cp\u003e6.3 Brief Description of the Automatic Virtual Metrology (AVM) Server 218\u003c\/p\u003e \u003cp\u003e6.4 Brief Description of the Baseline Predictive Maintenance (BPM) Scheme in the Intelligent Prediction Maintenance (IPM) Server 218\u003c\/p\u003e \u003cp\u003e6.5 Brief Description of the Key-variable Search Algorithm (KSA) Scheme in the Intelligent Yield Management (IYM) Server 219\u003c\/p\u003e \u003cp\u003e6.6 The iFA System Platform 220\u003c\/p\u003e \u003cp\u003e6.6.1 Cloud-based iFA System Platform 220\u003c\/p\u003e \u003cp\u003e6.6.2 Server-based iFA System Platform 221\u003c\/p\u003e \u003cp\u003e6.7 Conclusion 222\u003c\/p\u003e \u003cp\u003eAppendix 6.A – Abbreviation List 222\u003c\/p\u003e \u003cp\u003eAppendix 6.B – List of Symbols 224\u003c\/p\u003e \u003cp\u003eReferences 224\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Advanced Manufacturing Cloud of Things (AMCoT) Framework \u003c\/b\u003e\u003cb\u003e225\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMin-Hsiung Hung, Chao-Chun Chen, and Yu-Chuan Lin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 225\u003c\/p\u003e \u003cp\u003e7.2 Key Components of AMCoT Framework 227\u003c\/p\u003e \u003cp\u003e7.2.1 Key Components of Cloud Part 227\u003c\/p\u003e \u003cp\u003e7.2.2 Key Components of Factory Part 229\u003c\/p\u003e \u003cp\u003e7.2.3 An Example Intelligent Manufacturing Platform Based on AMCoT Framework 229\u003c\/p\u003e \u003cp\u003e7.2.4 Summary 231\u003c\/p\u003e \u003cp\u003e7.3 Framework Design of Cyber-Physical Agent (CPA) 231\u003c\/p\u003e \u003cp\u003e7.3.1 Framework of CPA 231\u003c\/p\u003e \u003cp\u003e7.3.2 Framework of Containerized CPA (CPAC) 232\u003c\/p\u003e \u003cp\u003e7.3.3 Summary 233\u003c\/p\u003e \u003cp\u003e7.4 Rapid Construction Scheme of CPAs (RCSCPA) Based on Docker and Kubernetes 234\u003c\/p\u003e \u003cp\u003e7.4.1 Background and Motivation 234\u003c\/p\u003e \u003cp\u003e7.4.2 System Architecture of RCSCPA 235\u003c\/p\u003e \u003cp\u003e7.4.3 Core Functional Mechanisms of RCSCPA 236\u003c\/p\u003e \u003cp\u003e7.4.3.1 Horizontal Auto-Scaling Mechanism 237\u003c\/p\u003e \u003cp\u003e7.4.3.2 Load Balance Mechanism 238\u003c\/p\u003e \u003cp\u003e7.4.3.3 Failover Mechanism 238\u003c\/p\u003e \u003cp\u003e7.4.4 Industrial Case Study of RCSCPA 239\u003c\/p\u003e \u003cp\u003e7.4.4.1 Experimental Setup 239\u003c\/p\u003e \u003cp\u003e7.4.4.2 Testing Results 239\u003c\/p\u003e \u003cp\u003e7.4.5 Summary 242\u003c\/p\u003e \u003cp\u003e7.5 Big Data Analytics Application Platform 242\u003c\/p\u003e \u003cp\u003e7.5.1 Architecture of Big Data Analytics Application Platform 242\u003c\/p\u003e \u003cp\u003e7.5.2 Performance Evaluation of Processing Big Data 243\u003c\/p\u003e \u003cp\u003e7.5.3 Big Data Analytics Application in Manufacturing – Electrical Discharge Machining 245\u003c\/p\u003e \u003cp\u003e7.5.4 Summary 247\u003c\/p\u003e \u003cp\u003e7.6 Manufacturing Services Automated Construction Scheme (MSACS) 248\u003c\/p\u003e \u003cp\u003e7.6.1 Background and Motivation 248\u003c\/p\u003e \u003cp\u003e7.6.2 Design of Three-Phase Workflow of MSACS 249\u003c\/p\u003e \u003cp\u003e7.6.3 Architecture Design of MSACS 251\u003c\/p\u003e \u003cp\u003e7.6.4 Designs of Core Components 252\u003c\/p\u003e \u003cp\u003e7.6.4.1 Design of Key Information (KI) Extractor 252\u003c\/p\u003e \u003cp\u003e7.6.4.2 Design of Library Information (Lib. Info.) Template 255\u003c\/p\u003e \u003cp\u003e7.6.4.3 Design of Service Interface Information (SI Info.) Template 256\u003c\/p\u003e \u003cp\u003e7.6.4.4 Design of Web Service Package (WSP) Generator 256\u003c\/p\u003e \u003cp\u003e7.6.4.5 Design of Service Constructor 261\u003c\/p\u003e \u003cp\u003e7.6.5 Industrial Case Studies 262\u003c\/p\u003e \u003cp\u003e7.6.5.1 Web Graphical User Interface (GUI) of MSACS 262\u003c\/p\u003e \u003cp\u003e7.6.5.2 Case Study 1: Automated Construction of the AVM Cloud-based Manufacturing (CMfg) Service for Validating the Efficacy of MSACS 262\u003c\/p\u003e \u003cp\u003e7.6.5.3 Case Study 2: Performance Evaluation of MSACS 264\u003c\/p\u003e \u003cp\u003e7.6.6 Summary 265\u003c\/p\u003e \u003cp\u003e7.7 Containerized MSACS (MSACSC) 266\u003c\/p\u003e \u003cp\u003e7.8 Conclusion 268\u003c\/p\u003e \u003cp\u003eAppendix 7.A – Abbreviation List 269\u003c\/p\u003e \u003cp\u003eAppendix 7.B – Patents (AMCoT + CPA) 270\u003c\/p\u003e \u003cp\u003eReferences 271\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Automatic Virtual Metrology (AVM) \u003c\/b\u003e\u003cb\u003e275\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFan-Tien Cheng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 275\u003c\/p\u003e \u003cp\u003e8.1.1 Survey of Virtual Metrology (VM)-Related Literature 276\u003c\/p\u003e \u003cp\u003e8.1.2 Necessity of Applying VM 277\u003c\/p\u003e \u003cp\u003e8.1.3 Benefits of VM 278\u003c\/p\u003e \u003cp\u003e8.2 Evolution of VM and Invention of AVM 282\u003c\/p\u003e \u003cp\u003e8.2.1 Invention of AVM 283\u003c\/p\u003e \u003cp\u003e8.3 Integrating AVM Functions into the Manufacturing Execution System (MES) 287\u003c\/p\u003e \u003cp\u003e8.3.1 Operating Scenarios among AVM, MES Components, and Run-to-Run (R2R) Controllers 289\u003c\/p\u003e \u003cp\u003e8.4 Applying AVM for Workpiece-to-Workpiece (W2W) Control 292\u003c\/p\u003e \u003cp\u003e8.4.1 Background Materials 293\u003c\/p\u003e \u003cp\u003e8.4.2 Fundamentals of Applying AVM for W2W Control 295\u003c\/p\u003e \u003cp\u003e8.4.3 R2R Control Utilizing VM with Reliance Index (RI) and Global Similarity Index (GSI) 299\u003c\/p\u003e \u003cp\u003e8.4.4 Illustrative Examples 300\u003c\/p\u003e \u003cp\u003e8.4.5 Summary 313\u003c\/p\u003e \u003cp\u003e8.5 AVM System Deployment 313\u003c\/p\u003e \u003cp\u003e8.5.1 Automation Levels of VM Systems 313\u003c\/p\u003e \u003cp\u003e8.5.2 Deployment of the AVM System 315\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 318\u003c\/p\u003e \u003cp\u003eAppendix 8.A – Abbreviation List 319\u003c\/p\u003e \u003cp\u003eAppendix 8.B – List of Symbols in Equations 321\u003c\/p\u003e \u003cp\u003eAppendix 8.C – Patents (AVM) 323\u003c\/p\u003e \u003cp\u003eReferences 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Intelligent Predictive Maintenance (IPM) \u003c\/b\u003e\u003cb\u003e331\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eYu-Chen Chiu, Yu-Ming Hsieh, Chin-Yi Lin, and Fan-Tien Cheng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 331\u003c\/p\u003e \u003cp\u003e9.1.1 Necessity of Baseline Predictive Maintenance (BPM) 332\u003c\/p\u003e \u003cp\u003e9.1.2 Prediction Algorithms of Remaining Useful Life (RUL) 333\u003c\/p\u003e \u003cp\u003e9.1.3 Introducing the Factory-wide IPM System 334\u003c\/p\u003e \u003cp\u003e9.2 BPM 334\u003c\/p\u003e \u003cp\u003e9.2.1 Important Samples Needed for Creating Target-Device Baseline Model 337\u003c\/p\u003e \u003cp\u003e9.2.2 Samples Needed for Creating Baseline Individual Similarity Index (ISIB) Model 338\u003c\/p\u003e \u003cp\u003e9.2.3 Device-Health-Index (DHI) Module 338\u003c\/p\u003e \u003cp\u003e9.2.4 Baseline-Error-Index (BEI) Module 339\u003c\/p\u003e \u003cp\u003e9.2.5 Illustration of Fault-Detection-and-Classification (FDC) Logic 340\u003c\/p\u003e \u003cp\u003e9.2.6 Flow Chart of Baseline FDC Execution Procedure 340\u003c\/p\u003e \u003cp\u003e9.2.7 Exponential-Curve-Fitting (ECF) RUL Prediction Module 340\u003c\/p\u003e \u003cp\u003e9.3 Time-Series-Prediction (TSP) Algorithm for Calculating RUL 344\u003c\/p\u003e \u003cp\u003e9.3.1 ABPM Scheme 345\u003c\/p\u003e \u003cp\u003e9.3.2 Problems Encountered with the ECF Model 346\u003c\/p\u003e \u003cp\u003e9.3.3 Details of the TSP Algorithm 346\u003c\/p\u003e \u003cp\u003e9.3.3.1 AR Model 348\u003c\/p\u003e \u003cp\u003e9.3.3.2 MA Model 349\u003c\/p\u003e \u003cp\u003e9.3.3.3 ARMA and ARIMA Models 349\u003c\/p\u003e \u003cp\u003e9.3.3.4 TSP Algorithm 349\u003c\/p\u003e \u003cp\u003e9.3.3.5 Pre-Alarm Module 352\u003c\/p\u003e \u003cp\u003e9.3.3.6 Death Correlation Index 353\u003c\/p\u003e \u003cp\u003e9.4 Factory-Wide IPM Management Framework 354\u003c\/p\u003e \u003cp\u003e9.4.1 Management View and Equipment View of a Factory 354\u003c\/p\u003e \u003cp\u003e9.4.2 Health Index Hierarchy (HIH) 355\u003c\/p\u003e \u003cp\u003e9.4.3 Factory-wide IPM System Architecture 356\u003c\/p\u003e \u003cp\u003e9.5 IPM System Implementation Architecture 359\u003c\/p\u003e \u003cp\u003e9.5.1 Implementation Architecture of IPMC based on Docker and Kubernetes 359\u003c\/p\u003e \u003cp\u003e9.5.2 Construction and Implementation of the IPMC 361\u003c\/p\u003e \u003cp\u003e9.6 IPM System Deployment 364\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 367\u003c\/p\u003e \u003cp\u003eAppendix 9.A – Abbreviation List 367\u003c\/p\u003e \u003cp\u003eAppendix 9.B – List of Symbols in Equations 370\u003c\/p\u003e \u003cp\u003eAppendix 9.C – Patents (IPM) 371\u003c\/p\u003e \u003cp\u003eReferences 372\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Intelligent Yield Management (IYM) \u003c\/b\u003e\u003cb\u003e377\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eYu-Ming Hsieh, Chin-Yi Lin, and Fan-Tien Cheng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 377\u003c\/p\u003e \u003cp\u003e10.1.1 Traditional Root-Cause Search Procedure of a Yield Loss 379\u003c\/p\u003e \u003cp\u003e10.1.2 IYM System 380\u003c\/p\u003e \u003cp\u003e10.1.3 Procedure for Finding the Root Causes of a Yield Loss by Applying the Key-variable Search Algorithm (KSA) Scheme 380\u003c\/p\u003e \u003cp\u003e10.2 KSA Scheme 381\u003c\/p\u003e \u003cp\u003e10.2.1 Data Preprocessing Module 382\u003c\/p\u003e \u003cp\u003e10.2.2 KSA Module 382\u003c\/p\u003e \u003cp\u003e10.2.2.1 Triple Phase Orthogonal Greedy Algorithm (TPOGA) 382\u003c\/p\u003e \u003cp\u003e10.2.2.2 Automated Least Absolute Shrinkage and Selection Operator (ALASSO) 384\u003c\/p\u003e \u003cp\u003e10.2.2.3 Reliance Index of KSA (RIK) Module 385\u003c\/p\u003e \u003cp\u003e10.2.3 Blind-stage Search Algorithm (BSA) Module 386\u003c\/p\u003e \u003cp\u003e10.2.3.1 Blind Cases 387\u003c\/p\u003e \u003cp\u003e10.2.3.2 Blind-stage Search Algorithm 390\u003c\/p\u003e \u003cp\u003e10.2.4 Interaction-Effect Search Algorithm (IESA) Module 393\u003c\/p\u003e \u003cp\u003e10.2.4.1 Interaction-Effect 393\u003c\/p\u003e \u003cp\u003e10.2.4.2 Interaction-Effect Search Algorithm 396\u003c\/p\u003e \u003cp\u003e10.3 IYM System Deployment 401\u003c\/p\u003e \u003cp\u003e10.4 Conclusion 402\u003c\/p\u003e \u003cp\u003eAppendix 10.A – Abbreviation List 402\u003c\/p\u003e \u003cp\u003eAppendix 10.B – List of Symbols in Equations 403\u003c\/p\u003e \u003cp\u003eAppendix 10.C – Patents (IYM) 405\u003c\/p\u003e \u003cp\u003eReferences 406\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Application Cases of Intelligent Manufacturing \u003c\/b\u003e\u003cb\u003e409\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFan-Tien Cheng, Yu-Chen Chiu, Yu-Ming Hsieh, Hao Tieng, Chin-Yi Lin, and Hsien-Cheng Huang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 409\u003c\/p\u003e \u003cp\u003e11.2 Application Case I: Thin Film Transistor Liquid Crystal Display (TFT-LCD) Industry 409\u003c\/p\u003e \u003cp\u003e11.2.1 Automatic Virtual Metrology (AVM) Deployment Examples in the TFT-LCD Industry 409\u003c\/p\u003e \u003cp\u003e11.2.1.1 Introducing the TFT-LCD Production Tools and Manufacturing Processes for AVM Deployment 410\u003c\/p\u003e \u003cp\u003e11.2.1.2 AVM Deployment Types for TFT-LCD Manufacturing 413\u003c\/p\u003e \u003cp\u003e11.2.1.3 Illustrative Examples 418\u003c\/p\u003e \u003cp\u003e11.2.1.4 Summary 425\u003c\/p\u003e \u003cp\u003e11.2.2 Intelligent Yield Management (IYM) Deployment Examples in the TFT-LCD Industry 425\u003c\/p\u003e \u003cp\u003e11.2.2.1 Introducing the TFT-LCD Production Tools and Manufacturing Processes for IYM Deployment 425\u003c\/p\u003e \u003cp\u003e11.2.2.2 KSA Deployment Example 426\u003c\/p\u003e \u003cp\u003e11.2.2.3 Summary 432\u003c\/p\u003e \u003cp\u003e11.3 Application Case II: Solar Cell Industry 432\u003c\/p\u003e \u003cp\u003e11.3.1 Introducing the Solar Cell Manufacturing Process and Requirement Analysis of Intelligent Manufacturing 433\u003c\/p\u003e \u003cp\u003e11.3.2 T2T Control with AVM Deployment Examples 434\u003c\/p\u003e \u003cp\u003e11.3.2.1 T2T+VM Control Scheme with RI\u0026amp;GSI 435\u003c\/p\u003e \u003cp\u003e11.3.2.2 Illustrative Examples of T2T Control with AVM 437\u003c\/p\u003e \u003cp\u003e11.3.3 Factory-Wide Intelligent Predictive Maintenance (IPM) Deployment Examples 444\u003c\/p\u003e \u003cp\u003e11.3.3.1 Illustrative Examples of BPM and RUL Prediction 444\u003c\/p\u003e \u003cp\u003e11.3.3.2 Illustrative Example of Factory-Wide IPM System 451\u003c\/p\u003e \u003cp\u003e11.3.4 Summary 453\u003c\/p\u003e \u003cp\u003e11.4 Application Case III: Semiconductor Industry 453\u003c\/p\u003e \u003cp\u003e11.4.1 AVM Deployment Example in the Semiconductor Industry 453\u003c\/p\u003e \u003cp\u003e11.4.1.1 AVM Deployment Example of the Etching Process 454\u003c\/p\u003e \u003cp\u003e11.4.1.2 Summary 456\u003c\/p\u003e \u003cp\u003e11.4.2 IPM Deployment Examples in the Semiconductor Industry 456\u003c\/p\u003e \u003cp\u003e11.4.2.1 Introducing the Bumping Production Tools for IPM Deployment 456\u003c\/p\u003e \u003cp\u003e11.4.2.2 Illustrative Example 456\u003c\/p\u003e \u003cp\u003e11.4.2.3 Summary 460\u003c\/p\u003e \u003cp\u003e11.4.3 IYM Deployment Examples in the Semiconductor Industry 460\u003c\/p\u003e \u003cp\u003e11.4.3.1 Introducing the Bumping Process of Semiconductor Manufacturing for IYM Deployment 460\u003c\/p\u003e \u003cp\u003e11.4.3.2 Illustrative Example 460\u003c\/p\u003e \u003cp\u003e11.4.3.3 Summary 464\u003c\/p\u003e \u003cp\u003e11.5 Application Case IV: Automotive Industry 464\u003c\/p\u003e \u003cp\u003e11.5.1 AMCoT and AVM Deployment Examples in Wheel Machining Automation (WMA) 464\u003c\/p\u003e \u003cp\u003e11.5.1.1 Integrating GED-plus-AVM (GAVM) into WMA for Total Inspection 464\u003c\/p\u003e \u003cp\u003e11.5.1.2 Applying AMCoT to WMA 466\u003c\/p\u003e \u003cp\u003e11.5.1.3 Applying AVM in AMCoT to WMA 469\u003c\/p\u003e \u003cp\u003e11.5.1.4 Summary 472\u003c\/p\u003e \u003cp\u003e11.5.2 Mass Customization (MC) Example for WMA 472\u003c\/p\u003e \u003cp\u003e11.5.2.1 Requirements of MC Production for WMA 472\u003c\/p\u003e \u003cp\u003e11.5.2.2 Considerations for Applying AVM in MC-Production of WMA 473\u003c\/p\u003e \u003cp\u003e11.5.2.3 The AVM-plus-Target-Value-Adjustment (TVA) Scheme for MC 473\u003c\/p\u003e \u003cp\u003e11.5.2.4 AVM-plus-TVA Deployment Example for WMA 477\u003c\/p\u003e \u003cp\u003e11.5.2.5 Summary 478\u003c\/p\u003e \u003cp\u003e11.6 Application Case V: Aerospace Industry 478\u003c\/p\u003e \u003cp\u003e11.6.1 Introducing the Engine-Case (EC) Manufacturing Process 479\u003c\/p\u003e \u003cp\u003e11.6.1.1 Manufacturing Processes of an EC 479\u003c\/p\u003e \u003cp\u003e11.6.1.2 Inspection Processes of the Flange Holes 479\u003c\/p\u003e \u003cp\u003e11.6.1.3 Literature Reviews 480\u003c\/p\u003e \u003cp\u003e11.6.2 Integrating GAVM into EC Manufacturing for Total Inspection 481\u003c\/p\u003e \u003cp\u003e11.6.2.1 Considerations of Applying AVM in EC Manufacturing 481\u003c\/p\u003e \u003cp\u003e11.6.3 The DF Scheme for Estimating the Flange Deformation of an EC 482\u003c\/p\u003e \u003cp\u003e11.6.3.1 Probing Scenario 482\u003c\/p\u003e \u003cp\u003e11.6.3.2 Ellipse-like Deformation of an EC 483\u003c\/p\u003e \u003cp\u003e11.6.3.3 Position Error 486\u003c\/p\u003e \u003cp\u003e11.6.3.4 Integrating the On-Line Probing, the DF Scheme, and the AVM Prediction 488\u003c\/p\u003e \u003cp\u003e11.6.4 Illustrative Examples 488\u003c\/p\u003e \u003cp\u003e11.6.4.1 Diameter Prediction 490\u003c\/p\u003e \u003cp\u003e11.6.4.2 Position Prediction 490\u003c\/p\u003e \u003cp\u003e11.6.5 Summary 492\u003c\/p\u003e \u003cp\u003e11.7 Application Case VI: Chemical Industry 492\u003c\/p\u003e \u003cp\u003e11.7.1 Introducing the Carbon-Fiber Manufacturing Process 492\u003c\/p\u003e \u003cp\u003e11.7.2 Three Preconditions of Applying AVM 493\u003c\/p\u003e \u003cp\u003e11.7.3 Challenges of Applying AVM to Carbon-Fiber Manufacturing 494\u003c\/p\u003e \u003cp\u003e11.7.3.1 CPA+AVM (CPAVM) Scheme for Carbon-Fiber Manufacturing 494\u003c\/p\u003e \u003cp\u003e11.7.3.2 AMCoT for Carbon-Fiber Manufacturing 498\u003c\/p\u003e \u003cp\u003e11.7.4 Illustrative Example 498\u003c\/p\u003e \u003cp\u003e11.7.4.1 Production Data Traceback (PDT) Mechanism for Work-in-Process (WIP) Tracking 499\u003c\/p\u003e \u003cp\u003e11.7.4.2 AVM for Carbon-Fiber Manufacturing 500\u003c\/p\u003e \u003cp\u003e11.7.5 Summary 501\u003c\/p\u003e \u003cp\u003e11.8 Application Case VII: Bottle Industry 502\u003c\/p\u003e \u003cp\u003e11.8.1 Bottle Industry and Its Intelligent Manufacturing Requirements 502\u003c\/p\u003e \u003cp\u003e11.8.1.1 Introducing the Blow-Molding Manufacturing Process 502\u003c\/p\u003e \u003cp\u003e11.8.2 Applying AVM to Blow Molding Manufacturing Process 502\u003c\/p\u003e \u003cp\u003e11.8.3 AVM-Based Run-to-Run (R2R) Control for Blow Molding Manufacturing Process 503\u003c\/p\u003e \u003cp\u003e11.8.4 Illustrative Example 504\u003c\/p\u003e \u003cp\u003e11.8.5 Summary 507\u003c\/p\u003e \u003cp\u003eAppendix 11.A – Abbreviation List 508\u003c\/p\u003e \u003cp\u003eAppendix 11.B – List of Symbols in Equations 512\u003c\/p\u003e \u003cp\u003eReferences 516\u003c\/p\u003e \u003cp\u003eIndex 521\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407134335319,"sku":"9781119739890","price":101.66,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/industry-4-1-9781119739890","provider":"Book Curl","version":"1.0","type":"link"}