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Industry 4.0 and the digital transformation of international business / / edited by Gurinder Singh, Richa Goel, and Vikas Garg
| Industry 4.0 and the digital transformation of international business / / edited by Gurinder Singh, Richa Goel, and Vikas Garg |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (320 pages) |
| Disciplina | 354.81150006 |
| Soggetto topico |
Industry 4.0
International business enterprises |
| ISBN | 981-19-7880-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part1: International Business Trends and Practices in the New Digital Age -- Chapter 1: Role and Importance of Information Technology in Global Business today -- Chapter 2: Changing face of International Business in the new Information Age 4.0 -- Chapter 3: International Production and Digital Economy -- Chapter 4: Global connectivity's knowledge complexities during the new information age -- Chapter 5: Expanding International Business via Smart Cities -- Chapter 6: Case Study -- Part 2: Understanding Entrepreneurial Strategies in Industry 4.0 -- Chapter 7: International Business and Block Chain Ventures -- Chapter 8: Rise of Entrepreneurship/Intrapreneurship during digital age -- Chapter 9: Mapping Global competitors during the new information age -- Chapter 10: New Digital Layers of Business Relationship -- Chapter 11: Role of Emerging Technologies like AI/ML/IOT with Reference to Industry 4.0 -- Chapter 12: Business Model: Alibaba vs Amazon etc -- Part 3: Functional Strategies in International Business in New Information Age -- Chapter 13: Internationalization through Digitization: Role of E-Businesses and E-Commerce -- Chapter 14: Changing Structure of Consumer Buying behavior and Expectation in the Digital Era -- Chapter 15: Understanding the Technology in the Developed World of Industry 4.0 -- Chapter 16: Corporate Social Responsibility and Environment responsibility in the Technology Management -- Chapter 17: Intellectual Property Rights around the Globe -- Part 4: Infrastructural Development and Societal Role with respect to Emerging Technology -- Chapter 18: The Future of Productivity and Growth of Infrastructural development -- Chapter 19: Government Implications on Infrastructural development & CSR with respect to Industry 4.0 -- Chapter 20: Societal Role and Responsibilities of the Emerging Technology in the Digital Transformation of International Business -- Chapter 21: Future roles of business in society: The expanding boundaries of International Business. |
| Record Nr. | UNINA-9910678255503321 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Industry 4.0 for the built environment : methodologies, technologies and skills / / Marzia Bolpagni, Rui Gavina, Diogo Ribeiro, editors
| Industry 4.0 for the built environment : methodologies, technologies and skills / / Marzia Bolpagni, Rui Gavina, Diogo Ribeiro, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (677 pages) |
| Disciplina | 338.47624 |
| Collana | Structural Integrity |
| Soggetto topico |
Construction industry
Industry 4.0 Civil engineering |
| ISBN | 3-030-82430-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910768188903321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Industry 4.0 vision for the supply of energy and materials : enabling technologies and emerging applications / / edited by Mahdi Sharifzadeh
| Industry 4.0 vision for the supply of energy and materials : enabling technologies and emerging applications / / edited by Mahdi Sharifzadeh |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (395 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Industry 4.0
Automation Telecommunication |
| ISBN |
1-119-69586-4
1-119-69595-3 1-119-69596-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910830580203321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Industry 4.1 : intelligent manufacturing with zero defects / / edited by Fan-Tien Cheng
| Industry 4.1 : intelligent manufacturing with zero defects / / edited by Fan-Tien Cheng |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (563 pages) |
| Disciplina | 658.4038028563 |
| Collana | IEEE Press Series on Systems Science and Engineering Ser. |
| Soggetto topico |
Industry 4.0
Manufacturing processes - Automation Manufactures - Defects - Prevention |
| ISBN |
1-119-73992-6
1-119-73990-X 1-119-73991-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Editor Biography -- List of Contributors -- Preface -- Acknowledgments -- Foreword -- Chapter 1 Evolution of Automation and Development Strategy of Intelligent Manufacturing with Zero Defects -- 1.1 Introduction -- 1.2 Evolution of Automation -- 1.2.1 e-Manufacturing -- 1.2.2 Industry 4.0 -- 1.2.3 Zero Defects - Vision of Industry 4.1 -- 1.3 Development Strategy of Intelligent Manufacturing with Zero Defects -- 1.3.1 Five-Stage Strategy of Yield Enhancement and Zero-Defects Assurance -- 1.4 Conclusion -- Appendix 1.A - Abbreviation List -- References -- Chapter 2 Data Acquisition and Preprocessing -- 2.1 Introduction -- 2.2 Data Acquisition -- 2.2.1 Process Data Acquisition -- 2.2.2 Metrology Data Acquisition -- 2.3 Data Preprocessing -- 2.3.1 Segmentation -- 2.3.2 Cleaning -- 2.3.3 Feature Extraction -- 2.4 Case Studies -- 2.4.1 Detrending of the Thermal Effect in Strain Gauge Data -- 2.4.2 Automated Segmentation of Signal Data -- 2.4.3 Tool State Diagnosis -- 2.4.4 Tool Diagnosis using Loading Data -- 2.5 Conclusion -- Appendix 2.A - Abbreviation List -- Appendix B - List of Symbols in Equations -- References -- Chapter 3 Communication Standards -- 3.1 Introduction -- 3.2 Communication Standards of the Semiconductor Equipment -- 3.2.1 Manufacturing Portion -- 3.2.2 Engineering Portion (Interface A) -- 3.3 Communication Standards of the Industrial Devices and Systems -- 3.3.1 Historical Roadmaps of Classic Open Platform Communications (OPC) and OPC Unified Architecture (OPC-UA) Protocols -- 3.3.2 Fundamentals of OPC-UA -- 3.3.3 Example of Intelligent Manufacturing Hierarchy Applying OPC-UA Protocol -- 3.4 Conclusion -- Appendix 3.A - Abbreviation List -- References -- Chapter 4 Cloud Computing, Internet of Things (IoT), Edge Computing, and Big Data Infrastructure -- 4.1 Introduction.
4.2 Cloud Computing -- 4.2.1 Essentials of Cloud Computing -- 4.2.2 Cloud Service Models -- 4.2.3 Cloud Deployment Models -- 4.2.4 Cloud Computing Applications in Manufacturing -- 4.2.5 Summary -- 4.3 IoT and Edge Computing -- 4.3.1 Essentials of IoT -- 4.3.2 Essentials of Edge Computing -- 4.3.3 Applications of IoT and Edge Computing in Manufacturing -- 4.3.4 Summary -- 4.4 Big Data Infrastructure -- 4.4.1 Application Demands -- 4.4.2 Core Software Stack Components -- 4.4.3 Bridging the Gap between Core Software Stack Components and Applications -- 4.4.4 Summary -- 4.5 Conclusion -- Appendix 4.A - Abbreviation List -- Appendix 4.B - List of Symbols in Equations -- References -- Chapter 5 Docker and Kubernetes -- 5.1 Introduction -- 5.2 Fundamentals of Docker -- 5.2.1 Docker Architecture -- 5.2.2 Docker Operational Principles -- 5.2.3 Illustrative Applications of Docker -- 5.2.4 Summary -- 5.3 Fundamentals of Kubernetes -- 5.3.1 Kubernetes Architecture -- 5.3.2 Kubernetes Operational Principles -- 5.3.3 Illustrative Applications of Kubernetes -- 5.3.4 Summary -- 5.4 Conclusion -- Appendix 5.A - Abbreviation List -- References -- Chapter 6 Intelligent Factory Automation (iFA) System Platform -- 6.1 Introduction -- 6.2 Architecture Design of the Advanced Manufacturing Cloud of Things (AMCoT) Framework -- 6.3 -- 6.4 Brief Description of the Baseline Predictive Maintenance (BPM) Scheme in the Intelligent Prediction Maintenance (IPM) Server -- 6.5 Brief Description of the Key-variable Search Algorithm (KSA) Scheme in the Intelligent Yield Management (IYM) Server -- 6.6 The iFA System Platform -- 6.6.1 Cloud-based iFA System Platform -- 6.6.2 Server-based iFA System Platform -- 6.7 Conclusion -- Appendix 6.A - Abbreviation List -- Appendix 6.B - List of Symbols -- References -- Chapter 7 Advanced Manufacturing Cloud of Things (AMCoT) Framework. 7.1 Introduction -- 7.2 Key Components of AMCoT Framework -- 7.2.1 Key Components of Cloud Part -- 7.2.2 Key Components of Factory Part -- 7.2.3 An Example Intelligent Manufacturing Platform Based on AMCoT Framework -- 7.2.4 Summary -- 7.3 Framework Design of Cyber-Physical Agent (CPA) -- 7.3.1 Framework of CPA -- 7.3.2 Framework of Containerized CPA (CPAC) -- 7.3.3 Summary -- 7.4 Rapid Construction Scheme of CPAs (RCSCPA) Based on Docker and Kubernetes -- 7.4.1 Background and Motivation -- 7.4.2 System Architecture of RCSCPA -- 7.4.3 Core Functional Mechanisms of RCSCPA -- 7.4.4 Industrial Case Study of RCSCPA -- 7.4.5 Summary -- 7.5 Big Data Analytics Application Platform -- 7.5.1 Architecture of Big Data Analytics Application Platform -- 7.5.2 Performance Evaluation of Processing Big Data -- 7.5.3 Big Data Analytics Application in Manufacturing - Electrical Discharge Machining -- 7.5.4 Summary -- 7.6 Manufacturing Services Automated Construction Scheme (MSACS) -- 7.6.1 Background and Motivation -- 7.6.2 Design of Three-Phase Workflow of MSACS -- 7.6.3 Architecture Design of MSACS -- 7.6.4 Designs of Core Components -- 7.6.5 Industrial Case Studies -- 7.6.6 Summary -- 7.7 Containerized MSACS (MSACSC) -- 7.8 Conclusion -- Appendix 7.A - Abbreviation List -- Appendix 7.B - Patents (AMCoT + CPA) -- USA Patents -- Taiwan, ROC Patents -- Japan Patent -- China Patent -- References -- Chapter 8 Automatic Virtual Metrology (AVM) -- 8.1 Introduction -- 8.1.1 Survey of Virtual Metrology (VM)-Related Literature -- 8.1.2 Necessity of Applying VM -- 8.1.3 Benefits of VM -- 8.2 Evolution of VM and Invention of AVM -- 8.2.1 Invention of AVM -- 8.3 Integrating AVM Functions into the Manufacturing Execution System (MES) -- 8.3.1 Operating Scenarios among AVM, MES Components, and Run-to-Run (R2R) Controllers. 8.4 Applying AVM for Workpiece-to-Workpiece (W2W) Control -- 8.4.1 Background Materials -- 8.4.2 Fundamentals of Applying AVM for W2W Control -- 8.4.3 R2R Control Utilizing VM with Reliance Index (RI) and Global Similarity Index (GSI) -- 8.4.4 Illustrative Examples -- 8.4.5 Summary -- 8.5 AVM System Deployment -- 8.5.1 Automation Levels of VM Systems -- 8.5.2 Deployment of the AVM System -- 8.6 Conclusion -- Appendix 8.A - Abbreviation List -- Appendix 8.B - List of Symbols in Equations -- Appendix 8.C - Patents (AVM) -- References -- Chapter 9 Intelligent Predictive Maintenance (IPM) -- 9.1 Introduction -- 9.1.1 Necessity of Baseline Predictive Maintenance (BPM) -- 9.1.2 Prediction Algorithms of Remaining Useful Life (RUL) -- 9.1.3 Introducing the Factory-wide IPM System -- 9.2 BPM -- 9.2.1 Important Samples Needed for Creating Target-Device Baseline Model -- 9.2.2 Samples Needed for Creating Baseline Individual Similarity Index (ISIB) Model -- 9.2.3 Device-Health-Index (DHI) Module -- 9.2.4 Baseline-Error-Index (BEI) Module -- 9.2.5 Illustration of Fault-Detection-and-Classification (FDC) Logic -- 9.2.6 Flow Chart of Baseline FDC Execution Procedure -- 9.2.7 Exponential-Curve-Fitting (ECF) RUL Prediction Module -- 9.3 Time-Series-Prediction (TSP) Algorithm for Calculating RUL -- 9.3.1 ABPM Scheme -- 9.3.2 Problems Encountered with the ECF Model -- 9.3.3 Details of the TSP Algorithm -- 9.4 Factory-Wide IPM Management Framework -- 9.4.1 Management View and Equipment View of a Factory -- 9.4.2 Health Index Hierarchy (HIH) -- 9.4.3 Factory-wide IPM System Architecture -- 9.5 IPM System Implementation Architecture -- 9.5.1 Implementation Architecture of IPMC based on Docker and Kubernetes -- 9.5.2 Construction and Implementation of the IPMC -- 9.6 IPM System Deployment -- Step 1: TD Selection and Operation Analysis -- Step 2: IPM System Setup. Step 3: Data Collection -- Step 4: IPM Modeling -- Step 5: IPM Function and Integration Tests -- Step 6: System Release -- 9.7 Conclusion -- Appendix 9.A - Abbreviation List -- Appendix 9.B - List of Symbols in Equations -- Appendix 9.C - Patents (IPM) -- USA Patents -- Taiwan, ROC Patents -- Japan Patent -- European Patent -- China Patents -- Korea Patent -- References -- Chapter 10 Intelligent Yield Management (IYM) -- 10.1 Introduction -- 10.1.1 Traditional Root-Cause Search Procedure of a Yield Loss -- 10.1.2 IYM System -- 10.1.3 Procedure for Finding the Root Causes of a Yield Loss by Applying the Key-variable Search Algorithm (KSA) Scheme -- 10.2 KSA Scheme -- 10.2.1 Data Preprocessing Module -- 10.2.2 KSA Module -- 10.2.3 Blind-stage Search Algorithm (BSA) Module -- 10.2.4 Interaction-Effect Search Algorithm (IESA) Module -- 10.3 IYM System Deployment -- 10.4 Conclusion -- Appendix 10.A - Abbreviation List -- Appendix 10.B - List of Symbols in Equations -- Appendix 10.C - Patents (IYM) -- USA Patents -- Taiwan, ROC Patents -- China Patents -- Korea Patent -- References -- Chapter 11 Application Cases of Intelligent Manufacturing -- 11.1 Introduction -- 11.2 Application Case I: Thin Film Transistor Liquid Crystal Display (TFT-LCD) Industry -- 11.2.1 Automatic Virtual Metrology (AVM) Deployment Examples in the TFT-LCD Industry -- 11.2.2 Intelligent Yield Management (IYM) Deployment Examples in the TFT-LCD Industry -- 11.3 Application Case II: Solar Cell Industry -- 11.3.1 Introducing the Solar Cell Manufacturing Process and Requirement Analysis of Intelligent Manufacturing -- 11.3.2 T2T Control with AVM Deployment Examples -- 11.3.3 Factory-Wide Intelligent Predictive Maintenance (IPM) Deployment Examples -- 11.3.4 Summary -- 11.4 Application Case III: Semiconductor Industry -- 11.4.1 AVM Deployment Example in the Semiconductor Industry. 11.4.2 IPM Deployment Examples in the Semiconductor Industry. |
| Record Nr. | UNINA-9910555085903321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Industry 4.1 : intelligent manufacturing with zero defects / / edited by Fan-Tien Cheng
| Industry 4.1 : intelligent manufacturing with zero defects / / edited by Fan-Tien Cheng |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (563 pages) |
| Disciplina | 658.4038028563 |
| Collana | IEEE Press Series on Systems Science and Engineering |
| Soggetto topico |
Industry 4.0
Manufacturing processes - Automation Manufactures - Defects - Prevention |
| ISBN |
1-119-73992-6
1-119-73990-X 1-119-73991-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Editor Biography -- List of Contributors -- Preface -- Acknowledgments -- Foreword -- Chapter 1 Evolution of Automation and Development Strategy of Intelligent Manufacturing with Zero Defects -- 1.1 Introduction -- 1.2 Evolution of Automation -- 1.2.1 e-Manufacturing -- 1.2.2 Industry 4.0 -- 1.2.3 Zero Defects - Vision of Industry 4.1 -- 1.3 Development Strategy of Intelligent Manufacturing with Zero Defects -- 1.3.1 Five-Stage Strategy of Yield Enhancement and Zero-Defects Assurance -- 1.4 Conclusion -- Appendix 1.A - Abbreviation List -- References -- Chapter 2 Data Acquisition and Preprocessing -- 2.1 Introduction -- 2.2 Data Acquisition -- 2.2.1 Process Data Acquisition -- 2.2.2 Metrology Data Acquisition -- 2.3 Data Preprocessing -- 2.3.1 Segmentation -- 2.3.2 Cleaning -- 2.3.3 Feature Extraction -- 2.4 Case Studies -- 2.4.1 Detrending of the Thermal Effect in Strain Gauge Data -- 2.4.2 Automated Segmentation of Signal Data -- 2.4.3 Tool State Diagnosis -- 2.4.4 Tool Diagnosis using Loading Data -- 2.5 Conclusion -- Appendix 2.A - Abbreviation List -- Appendix B - List of Symbols in Equations -- References -- Chapter 3 Communication Standards -- 3.1 Introduction -- 3.2 Communication Standards of the Semiconductor Equipment -- 3.2.1 Manufacturing Portion -- 3.2.2 Engineering Portion (Interface A) -- 3.3 Communication Standards of the Industrial Devices and Systems -- 3.3.1 Historical Roadmaps of Classic Open Platform Communications (OPC) and OPC Unified Architecture (OPC-UA) Protocols -- 3.3.2 Fundamentals of OPC-UA -- 3.3.3 Example of Intelligent Manufacturing Hierarchy Applying OPC-UA Protocol -- 3.4 Conclusion -- Appendix 3.A - Abbreviation List -- References -- Chapter 4 Cloud Computing, Internet of Things (IoT), Edge Computing, and Big Data Infrastructure -- 4.1 Introduction.
4.2 Cloud Computing -- 4.2.1 Essentials of Cloud Computing -- 4.2.2 Cloud Service Models -- 4.2.3 Cloud Deployment Models -- 4.2.4 Cloud Computing Applications in Manufacturing -- 4.2.5 Summary -- 4.3 IoT and Edge Computing -- 4.3.1 Essentials of IoT -- 4.3.2 Essentials of Edge Computing -- 4.3.3 Applications of IoT and Edge Computing in Manufacturing -- 4.3.4 Summary -- 4.4 Big Data Infrastructure -- 4.4.1 Application Demands -- 4.4.2 Core Software Stack Components -- 4.4.3 Bridging the Gap between Core Software Stack Components and Applications -- 4.4.4 Summary -- 4.5 Conclusion -- Appendix 4.A - Abbreviation List -- Appendix 4.B - List of Symbols in Equations -- References -- Chapter 5 Docker and Kubernetes -- 5.1 Introduction -- 5.2 Fundamentals of Docker -- 5.2.1 Docker Architecture -- 5.2.2 Docker Operational Principles -- 5.2.3 Illustrative Applications of Docker -- 5.2.4 Summary -- 5.3 Fundamentals of Kubernetes -- 5.3.1 Kubernetes Architecture -- 5.3.2 Kubernetes Operational Principles -- 5.3.3 Illustrative Applications of Kubernetes -- 5.3.4 Summary -- 5.4 Conclusion -- Appendix 5.A - Abbreviation List -- References -- Chapter 6 Intelligent Factory Automation (iFA) System Platform -- 6.1 Introduction -- 6.2 Architecture Design of the Advanced Manufacturing Cloud of Things (AMCoT) Framework -- 6.3 -- 6.4 Brief Description of the Baseline Predictive Maintenance (BPM) Scheme in the Intelligent Prediction Maintenance (IPM) Server -- 6.5 Brief Description of the Key-variable Search Algorithm (KSA) Scheme in the Intelligent Yield Management (IYM) Server -- 6.6 The iFA System Platform -- 6.6.1 Cloud-based iFA System Platform -- 6.6.2 Server-based iFA System Platform -- 6.7 Conclusion -- Appendix 6.A - Abbreviation List -- Appendix 6.B - List of Symbols -- References -- Chapter 7 Advanced Manufacturing Cloud of Things (AMCoT) Framework. 7.1 Introduction -- 7.2 Key Components of AMCoT Framework -- 7.2.1 Key Components of Cloud Part -- 7.2.2 Key Components of Factory Part -- 7.2.3 An Example Intelligent Manufacturing Platform Based on AMCoT Framework -- 7.2.4 Summary -- 7.3 Framework Design of Cyber-Physical Agent (CPA) -- 7.3.1 Framework of CPA -- 7.3.2 Framework of Containerized CPA (CPAC) -- 7.3.3 Summary -- 7.4 Rapid Construction Scheme of CPAs (RCSCPA) Based on Docker and Kubernetes -- 7.4.1 Background and Motivation -- 7.4.2 System Architecture of RCSCPA -- 7.4.3 Core Functional Mechanisms of RCSCPA -- 7.4.4 Industrial Case Study of RCSCPA -- 7.4.5 Summary -- 7.5 Big Data Analytics Application Platform -- 7.5.1 Architecture of Big Data Analytics Application Platform -- 7.5.2 Performance Evaluation of Processing Big Data -- 7.5.3 Big Data Analytics Application in Manufacturing - Electrical Discharge Machining -- 7.5.4 Summary -- 7.6 Manufacturing Services Automated Construction Scheme (MSACS) -- 7.6.1 Background and Motivation -- 7.6.2 Design of Three-Phase Workflow of MSACS -- 7.6.3 Architecture Design of MSACS -- 7.6.4 Designs of Core Components -- 7.6.5 Industrial Case Studies -- 7.6.6 Summary -- 7.7 Containerized MSACS (MSACSC) -- 7.8 Conclusion -- Appendix 7.A - Abbreviation List -- Appendix 7.B - Patents (AMCoT + CPA) -- USA Patents -- Taiwan, ROC Patents -- Japan Patent -- China Patent -- References -- Chapter 8 Automatic Virtual Metrology (AVM) -- 8.1 Introduction -- 8.1.1 Survey of Virtual Metrology (VM)-Related Literature -- 8.1.2 Necessity of Applying VM -- 8.1.3 Benefits of VM -- 8.2 Evolution of VM and Invention of AVM -- 8.2.1 Invention of AVM -- 8.3 Integrating AVM Functions into the Manufacturing Execution System (MES) -- 8.3.1 Operating Scenarios among AVM, MES Components, and Run-to-Run (R2R) Controllers. 8.4 Applying AVM for Workpiece-to-Workpiece (W2W) Control -- 8.4.1 Background Materials -- 8.4.2 Fundamentals of Applying AVM for W2W Control -- 8.4.3 R2R Control Utilizing VM with Reliance Index (RI) and Global Similarity Index (GSI) -- 8.4.4 Illustrative Examples -- 8.4.5 Summary -- 8.5 AVM System Deployment -- 8.5.1 Automation Levels of VM Systems -- 8.5.2 Deployment of the AVM System -- 8.6 Conclusion -- Appendix 8.A - Abbreviation List -- Appendix 8.B - List of Symbols in Equations -- Appendix 8.C - Patents (AVM) -- References -- Chapter 9 Intelligent Predictive Maintenance (IPM) -- 9.1 Introduction -- 9.1.1 Necessity of Baseline Predictive Maintenance (BPM) -- 9.1.2 Prediction Algorithms of Remaining Useful Life (RUL) -- 9.1.3 Introducing the Factory-wide IPM System -- 9.2 BPM -- 9.2.1 Important Samples Needed for Creating Target-Device Baseline Model -- 9.2.2 Samples Needed for Creating Baseline Individual Similarity Index (ISIB) Model -- 9.2.3 Device-Health-Index (DHI) Module -- 9.2.4 Baseline-Error-Index (BEI) Module -- 9.2.5 Illustration of Fault-Detection-and-Classification (FDC) Logic -- 9.2.6 Flow Chart of Baseline FDC Execution Procedure -- 9.2.7 Exponential-Curve-Fitting (ECF) RUL Prediction Module -- 9.3 Time-Series-Prediction (TSP) Algorithm for Calculating RUL -- 9.3.1 ABPM Scheme -- 9.3.2 Problems Encountered with the ECF Model -- 9.3.3 Details of the TSP Algorithm -- 9.4 Factory-Wide IPM Management Framework -- 9.4.1 Management View and Equipment View of a Factory -- 9.4.2 Health Index Hierarchy (HIH) -- 9.4.3 Factory-wide IPM System Architecture -- 9.5 IPM System Implementation Architecture -- 9.5.1 Implementation Architecture of IPMC based on Docker and Kubernetes -- 9.5.2 Construction and Implementation of the IPMC -- 9.6 IPM System Deployment -- Step 1: TD Selection and Operation Analysis -- Step 2: IPM System Setup. Step 3: Data Collection -- Step 4: IPM Modeling -- Step 5: IPM Function and Integration Tests -- Step 6: System Release -- 9.7 Conclusion -- Appendix 9.A - Abbreviation List -- Appendix 9.B - List of Symbols in Equations -- Appendix 9.C - Patents (IPM) -- USA Patents -- Taiwan, ROC Patents -- Japan Patent -- European Patent -- China Patents -- Korea Patent -- References -- Chapter 10 Intelligent Yield Management (IYM) -- 10.1 Introduction -- 10.1.1 Traditional Root-Cause Search Procedure of a Yield Loss -- 10.1.2 IYM System -- 10.1.3 Procedure for Finding the Root Causes of a Yield Loss by Applying the Key-variable Search Algorithm (KSA) Scheme -- 10.2 KSA Scheme -- 10.2.1 Data Preprocessing Module -- 10.2.2 KSA Module -- 10.2.3 Blind-stage Search Algorithm (BSA) Module -- 10.2.4 Interaction-Effect Search Algorithm (IESA) Module -- 10.3 IYM System Deployment -- 10.4 Conclusion -- Appendix 10.A - Abbreviation List -- Appendix 10.B - List of Symbols in Equations -- Appendix 10.C - Patents (IYM) -- USA Patents -- Taiwan, ROC Patents -- China Patents -- Korea Patent -- References -- Chapter 11 Application Cases of Intelligent Manufacturing -- 11.1 Introduction -- 11.2 Application Case I: Thin Film Transistor Liquid Crystal Display (TFT-LCD) Industry -- 11.2.1 Automatic Virtual Metrology (AVM) Deployment Examples in the TFT-LCD Industry -- 11.2.2 Intelligent Yield Management (IYM) Deployment Examples in the TFT-LCD Industry -- 11.3 Application Case II: Solar Cell Industry -- 11.3.1 Introducing the Solar Cell Manufacturing Process and Requirement Analysis of Intelligent Manufacturing -- 11.3.2 T2T Control with AVM Deployment Examples -- 11.3.3 Factory-Wide Intelligent Predictive Maintenance (IPM) Deployment Examples -- 11.3.4 Summary -- 11.4 Application Case III: Semiconductor Industry -- 11.4.1 AVM Deployment Example in the Semiconductor Industry. 11.4.2 IPM Deployment Examples in the Semiconductor Industry. |
| Record Nr. | UNINA-9910830143003321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent and fuzzy techniques in aviation 4.0 : theory and applications / / Cengiz Kahraman, Serhat Aydın, editors
| Intelligent and fuzzy techniques in aviation 4.0 : theory and applications / / Cengiz Kahraman, Serhat Aydın, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (547 pages) |
| Disciplina | 658.4038028563 |
| Collana | Studies in systems, decision and control |
| Soggetto topico | Industry 4.0 |
| ISBN | 3-030-75067-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Contributors -- Introduction to Intelligent and Fuzzy Techniques in Aviation 4.0: Theory and Applications -- Aviation 4.0 Revolution -- 1 Introduction -- 2 Aviation 4.0 Technologies -- 2.1 Ground Services Application in Aviation 4.0 -- 2.2 Maintenance and Production in Aviation 4.0 -- 2.3 Unmanned Aerial Vehicle Technology in Aviation 4.0 -- 3 Aviation 4.0 in the Literature -- 4 The Future of the Aviation Revolution -- 5 Conclusion -- References -- Intelligent Systems in Aviation 4.0 Industry -- 1 Introduction -- 2 Intelligent Systems -- 3 Intelligence in Aviation 4.0 -- 4 Fuzzy Systems in Aviation 4.0 -- 5 Fuzzy MCDM Methods in Aviation 4.0 -- 6 Conclusions -- References -- Intelligent and Fuzzy Applications in Aviation 4.0 Ground Services -- Fuzzy Logic Controller for Aviation Parking with 5G Communication Technology -- 1 Introduction -- 2 Preliminaries -- 3 Material and Method -- 4 Proposed Model -- 4.1 Case Study -- 4.2 Proposed Model -- 4.3 Parameters -- 4.4 Assumptions -- 4.5 Assigning of Neutrosophic Numbers and De-Neutrosophication -- 4.6 De-Neutrosophication -- 4.7 FLC Approach for the Calculation of Time -- 4.8 Defuzzification -- 4.9 Membership Function Editor -- 4.10 The Rule Editor -- 4.11 Defuzzified Results -- 4.12 Mobile Usability -- 4.13 How It Will Work? and the Role of 5G? -- 5 Result Discussion and Conclusion -- References -- An Integrated Fuzzy Decision Making and Integer Programming Model for Robot Selection for a Baggage Robot System -- 1 Introduction -- 2 Literature Review -- 3 Conventional Baggage Handling Systems -- 4 Baggage Robot Systems -- 5 Proposed Model -- 6 Application of the Proposed Model -- 7 Conclusion -- References -- Complex Spherical Fuzzy Sets and an Application to Catering Services in Aviation 4.0 -- 1 Introduction -- 2 Methodology -- 2.1 Complex Spherical Fuzzy Sets.
2.2 The EDAS Model with Complex Spherical Fuzzy Information -- 3 Application of CSFSs for MCDM Problems -- 4 Discussion -- 5 Conclusions -- References -- Digitalization on Aviation 4.0: Designing a Scikit-Fuzzy Control System for In-Flight Catering Customer Satisfaction -- 1 Introduction -- 2 Proposed Methodology -- 3 Application -- 4 Conclusion and Discussion -- References -- Analysis of Intelligent Software Implementations in Air Cargo Using Fermatean Fuzzy CODAS Method -- 1 Introduction -- 2 Literature Review -- 3 Air Cargo System -- 4 CODAS Method -- 4.1 Crisp CODAS Method -- 4.2 Fuzzy Extensions of the CODAS Method -- 5 Fermatean Fuzzy CODAS Method -- 5.1 Algebraic Operations of FFNs -- 5.2 Ranking of Fermatean Fuzzy Sets -- 5.3 Proposed Methodology -- 6 Application -- 7 Conclusion -- References -- Intelligent and Fuzzy Applications in Aircraft Handling Services with Aviation 4.0 -- 1 Introduction -- 2 Aircraft Ground Handling Operations -- 3 Ground Handling Fleets Automation -- 3.1 Previous Ground Handling Automation Studies -- 3.2 ACDM and Ground Handling Decision Making -- 3.3 Ground Handling Management Structures -- 4 Mathematical Formulation of GSE Decision Problems -- 4.1 Resources and Demand for Ground Handling Services -- 4.2 Formulation of the GSE Assignment Problem for Type I Operations -- 4.3 Formulation of the GSE Assignment Problem Type II -- 4.4 Formulation of the GSE Assignment Problem Type III -- 4.5 Formulation of the GSE Assignment Problem Type IV -- 5 Conclusions -- References -- Novel Spherical Fuzzy Eco-holonic Concept in Sustainable Supply Chain of Aviation Fuel -- 1 Introduction -- 2 Literature Review -- 2.1 Holarchy and Holonic Structures -- 2.2 Decision Making -- 2.3 Aviation Industry and Aviation Fuel Supply Chain -- 2.4 Sustainable Supply Chain (SSC) for Fuel of Airlines -- 3 Preliminaries. 3.1 Eco-holarchy and Eco-holonic Structure -- 3.2 Spherical Fuzzy Sets -- 4 Methodology -- 4.1 Spherical Fuzzy Eco-holarchy (SF Eco-holarchy) -- 4.2 SF Eco-holarchy Application in a MAGDM Problem -- 5 Application -- 6 Conclusion -- References -- On-Board Cost Index Computation Through Fuzzy Logic -- 1 Introduction -- 2 Needs for Enhanced Automation of Flight Management -- 3 On-Board Flight Plan Generation -- 3.1 Main Functions of Flight Management Systems -- 4 Cost Index -- 4.1 The Flight Costs -- 4.2 Definition of the Cost Index -- 4.3 Current Usage of Cost Index -- 4.4 Vertical Profile Optimization -- 5 Tactical Cost Index Fuzzy Computation -- 5.1 The Operational Framework -- 5.2 Fuzzy Monitoring of the Cost Index -- 5.3 Tactical Cost Index Calculation -- 5.4 A Rule-Based Specialist Decision Maker in Aviation 4.0 -- 5.5 Case Study -- 6 Conclusions -- References -- Intelligent and Fuzzy Applications in Aviation 4.0 Aircraft Maintenance/Production Management -- Toward Joint Application of Fuzzy Systems and Augmented Reality in Aircraft Disassembly -- 1 Introduction -- 2 Aircraft Disassembly -- 3 Fuzzy Approaches to Disassembly Planning -- 4 Application of Augmented Reality in Disassembly -- 5 Fuzzy Approach and Augmented Reality in Disassembly -- 6 Application Perspective -- 7 Conclusion -- References -- Some Novel Preference Relations for Picture Fuzzy Sets and Selection of 3-D Printers in Aviation 4.0 -- 1 Introduction -- 2 Literature Review: Aviation 4.0 -- 3 Preliminaries -- 4 Picture Fuzzy Preference Relations and Incomplete Picture Fuzzy preference Relations -- 4.1 Picture Fuzzy Preference Relations -- 4.2 Incomplete Picture Fuzzy Preference Relations -- 5 Some Alternative Ranking Algorithms -- 5.1 PFPR Based Algorithm for Rank the Alternatives -- 5.2 Case Study -- 5.3 Incomplete PFPR Based Algorithm for Rank the Alternatives. 5.4 Numerical Example -- 6 Conclusion -- References -- A Conceptual Framework for Estimating the Remaining Operational Lifetime of the Recovered Components from End of Life Aircraft Using Fuzzy Simulation and Digital Twin -- 1 Introduction -- 2 Application of Industry 4.0 in Aircraft Maintenance -- 3 Fuzzy Models in Aircraft Maintenance -- 4 Estimating RUL of the Complex Products -- 5 Digital Models and the Advantages in Maintenance and Complex Products Health Monitoring -- 6 A Conceptual Framework Using the Digital Model and Fuzzy Simulation for Estimating RUL -- 7 Conclusion -- References -- Designing a System Architecture for the Management of the Recovered Parts from End-of-Life Aircraft Using Fuzzy Decision Making and Blockchain -- 1 Introduction -- 2 Literature Review -- 3 Aircraft at the End of Life and Parts Management -- 4 Proposed System Architecture Using Fuzzy Logic and Blockchain -- 5 Application Perspectives -- 6 Conclusion -- References -- Intelligent and Fuzzy Applications in Aviation 4.0 Transportation and Cargo Management -- A Hybrid Model Based on FAHP and WASPAS for Evaluation of Explosive and Narcotics Trace Detection Devices -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 FAHP -- 3.2 WASPAS -- 4 Case Study -- 4.1 Scenario Analysis -- 5 Conclusion -- References -- Selection of the Best Face Recognition System for Check in and Boarding Services -- 1 Introduction -- 2 Face Recognition-State of Art, Developments and Challenges in the Context of Aviation 4.0 -- 3 Literature Review -- 4 Methodology -- 4.1 Fuzzy Z-Numbers -- 4.2 Fuzzy Z-AHP -- 4.3 Fuzzy Z-Grey Relational Analysis -- 5 Application -- 6 Conclusion -- References -- Intelligent and Fuzzy Approaches in Aviation 4.0 Transportation and Cargo Applications -- 1 Introduction -- 2 Literature Review -- 3 Axiomatic Design -- 3.1 Independence Axiom. 3.2 Information Axiom -- 3.3 Fuzzy Independence Axiom -- 3.4 Fuzzy Information Axiom -- 4 Design Principles of Smart Containers -- 5 Conclusion -- References -- Intelligent and Fuzzy Applications in Aviation 4.0 Unmanned Aerial Vehicle Technologies -- Blockchain Applications in UAV-Towards Aviation 4.0 -- 1 Introduction -- 1.1 Role of BCT in Aviation -- 2 Literature Review -- 2.1 Blockchain Technology and Its Implementation Architecture -- 2.2 BCT Classification -- 2.3 BCT and Aviation System Applications -- 3 Methodology -- 4 Applications of BCT-Based Aviation System -- 5 Conclusion and Discussion -- References -- Intelligent and Fuzzy UAV Transportation Applications in Aviation 4.0 -- 1 Introduction -- 2 Literature Review -- 2.1 Vehicle Routing Problem -- 2.2 Path Planning Problem -- 2.3 Facility Location Problem -- 2.4 Other Related UAV Problems -- 3 Methodology -- 3.1 Fuzzy Mathematical Model -- 3.2 The Crisp Equivalent of the Fuzzy Model -- 4 Solution Method and Results -- 5 Conclusion -- References -- Spherical Fuzzy Inference Systems (S-FIS) to Control UAVs' Communication Technologies -- 1 Introduction -- 2 Literature Review -- 2.1 Fuzzy Logic and Fuzzy Inference Systems (FIS) -- 2.2 Fuzzy Sets Evolution and Spherical Fuzzy Sets (SFSs) -- 2.3 Unmanned Aerial Vehicles (UAVs) -- 3 Methodology -- 3.1 Preliminaries -- 3.2 Proposed Methodology -- 4 An Application of S-FIS: To Control and Select UAVs' Communication Technologies -- 5 Conclusion -- References -- Technology Analysis for Logistics 4.0 Applications: Criteria Affecting UAV Performances -- 1 Introduction -- 2 Unmanned Aerial Vehicle and Aviation 4.0 Concepts -- 3 Methods -- 3.1 Pythagorean Fuzzy AHP -- 3.2 Hesitant Fuzzy Linguistic Term Set -- 4 Application -- 5 Results and Discussion -- References. A Novel Mathematical Model to Design UAV Trajectory for Search and Rescue Operations in Disaster. |
| Record Nr. | UNINA-9910523747303321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
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| Lo trovi qui: Univ. Federico II | ||
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Intelligent engineering and management for industry 4. 0 / / edited by Yong-Hong Kuo
| Intelligent engineering and management for industry 4. 0 / / edited by Yong-Hong Kuo |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (186 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Industry 4.0
Industrial engineering |
| ISBN | 3-030-94683-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- A Batch Scheduling Model for a Three-Stage Flowshop with Batch Processor and Heterogeneous Job Processor to Minimize Total Actual Flowtime -- 1 Introduction -- 2 Problem Statement -- 3 Actual Flowtime -- 4 Model Development and Proposed Algorithm -- 4.1 Model Development -- 4.2 Proposed Algorithm -- 4.2.1 TSF Algorithm -- 4.2.2 HMS Algorithm -- 5 Illustrative Example -- 6 Concluding Remark -- References -- Batch Scheduling of Unique and Common Components for a Three-Stage Hybrid Flow Shop Processing Different Product Types with Multiple Due Dates to Minimize Total Actual Flow Time -- 1 Introduction -- 2 Problem Description -- 3 Formulation -- 4 Algorithm -- 5 Illustrative Example -- 6 Conclusion -- References -- Interactive Scheduling for a Dual Resource Constrained Job Shop with Manual and Automated Work Units -- 1 Introduction -- 2 Production Environment -- 2.1 Two Types of Work Units -- 2.2 Dual Resource Constrained Scheduling -- 2.3 Scheduled Maintenance -- 3 Interactive Scheduling Support System -- 3.1 Completion Time Calculation -- 3.2 Developed System -- 3.3 Remaining Issues -- 4 Conclusion -- References -- Big Data-Based Similarity Network Model for Cloud Manufacturing Services -- 1 Introduction -- 2 Preliminary -- 3 Invocation History-Based Service Similarity Evaluation -- 4 Service Similarity Network Model -- 4.1 Modeling of Service Similarity Network -- 4.2 Service Importance Evaluation -- 5 Case Study -- 6 Conclusion -- A.1 Electronic Supplementary Material -- References -- Evaluation Methods for the Reliability of a Linear Connected-(1,2)-or-(2,1)-Out-of-(m,n):F Lattice System -- 1 Introduction -- 2 Efficiency Comparison of the Recursive Equation Approach and the FMCIA -- 2.1 Notation -- 2.2 Recursive Equation Approach Yamamoto2008 -- 2.3 FMCIA Nakamura2017a -- 2.4 Efficiency Comparison.
3 Bounds for the Reliability of a Lin/(1,2)-or-(2,1)/(m,n):F System -- 3.1 Derivation of Upper and Lower Bounds -- 3.2 Numerical Experiment -- 4 Conclusions -- References -- Exact Solution Method for Balancing of a Self-Balancing Production Line with Worker- and Station-Dependent Speed -- 1 Introduction -- 2 The Production Line -- 2.1 Assumptions -- 2.2 Self-Balancing and Convergence -- 2.3 Problem Description -- 3 Exact Solution Method for Balancing a Line with Worker- and Station-Dependent Speed -- 4 Numerical Calculations -- 4.1 Two Workers -- 4.2 Three Workers -- 5 Conclusion and Remarks -- References -- A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload -- 1 Introduction -- 2 Problem Formulation -- 3 The Metaheuristics -- 3.1 The Proposed Encoding and Decoding Schemes -- 3.2 General Setting for NSGA-II and BNSGA-II -- 3.3 Comparison Metrics -- 4 Numerical Examples and Results -- 4.1 Parameter Setting for the Metaheuristics -- 4.2 Computational Results and Discussion -- 5 Conclusions -- References -- A Study on Optimal Limit Order Strategy Using Multi-Period Stochastic Programming Considering Nonexecution Risk -- 1 Introduction -- 2 Market Impact -- 2.1 Estimation Model -- 2.2 Data -- 2.3 Result of Estimation -- 3 Estimation Model for Fill Rate -- 4 Optimal Execution Model -- 5 Numerical Analysis -- 5.1 Basic Analysis -- 5.2 Examining Nonexecution Risk -- 5.3 MI of Limit Order -- 5.4 Reorder Strategy -- 5.5 Market Order Strategy -- 6 Conclusion -- References -- Banking the Unbanked: The Fintech Revolution -- 1 Introduction -- 2 Literature Review -- 3 Industry 4.0: India's Next Frontier of Digitally Enabled Financial Inclusion -- 4 Research Methodology -- 4.1 Data -- 4.2 Method -- 5 Analysis -- 6 Discussion -- 7 Conclusion -- Appendix: List of Abbreviations Used. Adaptive Intelligent Redeployment Strategy for Service Parts Inventory Management: A Case Study of a High-Tech Company -- Introduction -- Literature Review -- Multistage Service Parts Inventory Management System -- Representation of Service Parts Inventory Management System -- Control of Excess Inventory Redeployment -- Integrated Solution to Handle Excess Inventory -- An Illustrative Example in a Case Study -- Result of Redeployment Strategy -- Effect of Shipment Cost and Part Cost -- Discussion -- Conclusion and Future Research -- Rehabilitation Staff Scheduling Problem Considering Mental Workloadin Elderly Daytime Care Facility -- Introduction -- Methodology -- Notation and Assumptions -- Formulation -- Facility Survey -- Overview of the Surveyed Service Facility -- Survey Method of Mental Workload of Staff -- Results of the Mental Workload Survey -- Analysis of Current Schedule -- Numerical Experiment -- Assumptions of a Numerical Experiment -- Balanced Schedule for Mental Workloads -- Current Schedule in the Facility -- Balanced Schedule for Physical Workloads -- Discussion -- Conclusions -- Knowledge Management and Open Innovation for Improving SocialPerformance of Small and Medium Industry: A Pilot Study -- Introduction -- Literature Review -- Knowledge Management and Open Innovation -- Open Innovation and Social Performance -- Knowledge Management, Open Innovation, and Social Performance -- Methodology -- Conceptual Model and Hypotheses -- Knowledge Management -- Open Innovation -- Social Performance -- Hypotheses -- Results and Discussion -- Conclusion -- A Design Method of the Joint Venture Formation in EPC Projects -- Introduction -- Related Work -- Design of Joint Venture Formation -- Design Method -- Mathematical Model -- Simulation Model for Evaluating Joint Venture Formation -- Effectiveness of Joint Venture Formation. Problem Setting -- Results of Calculation -- Conclusions -- The Importance of Information Sharing in Blanket Order: Case Studiesof System Dynamics Simulation -- Introduction -- Literature Survey -- System Dynamics -- System Dynamic Simulation -- Stock and Flow Diagram -- System Dynamics Simulation of Supply Chain -- Methods -- Results and Discussion -- Case Study of Sister Company -- Current System of Sister Company -- Alternative Improvement Model -- Performance Comparison of Case Study 1 -- Case Study of Brokerage -- Current System of Brokerage -- Alternative Improvement -- Performance Comparison of Case Study 2 -- Managerial Implications -- Conclusions -- Multi-objective Robust Optimization for the Design of Biomass Co-firingNetworks -- Introduction -- Literature Review -- Model Formulation -- Computational Experiments -- Conclusions and Recommendations -- Appendix 1: Biomass Data -- Appendix 2: Co-firing Scheme Parameters -- Appendix 3: Power Plant Data -- Appendix 4: Biochar Sink Data -- Appendix 5: Other Relevant Parameters -- Co-evolution Theory-Based Collaborative Conceptual-EmbodimentCAD System -- Introduction -- Literature Research -- Collaborative CAD System -- Conceptual CAD System -- Creative and Cognitive CAD System -- Co-Evolution Design Theory -- Collaborative Conceptual-Embodiment Design CAD System -- Components of the CAD System -- Discussion -- Index. |
| Record Nr. | UNINA-9910578692403321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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International Virtual Conference on Industry 4. 0 : Select Proceedings of IVCI4. 0 2021 / / R. Jagadeesh Kannan [and three others], editors
| International Virtual Conference on Industry 4. 0 : Select Proceedings of IVCI4. 0 2021 / / R. Jagadeesh Kannan [and three others], editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (VIII, 241 p. 122 illus., 89 illus. in color.) |
| Disciplina | 658.4038028563 |
| Collana | Lecture Notes in Electrical Engineering Series |
| Soggetto topico | Industry 4.0 |
| ISBN | 981-19-9989-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910686780203321 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
International Virtual Conference on Industry 4.0 : select proceedings of IVCI4.0 2020 / / R. Jagadeesh Kannan [and three others], editors
| International Virtual Conference on Industry 4.0 : select proceedings of IVCI4.0 2020 / / R. Jagadeesh Kannan [and three others], editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIV, 473 p. 200 illus., 164 illus. in color.) |
| Disciplina | 658.4038028563 |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico | Industry 4.0 |
| ISBN | 981-16-1244-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pre-diagnosis, Prediction and Report Generation of a Disease -- An Audio Aided Face and Text Recognition System for Visually Impaired -- Improving Prediction Accuracy using Machine Learning Classification Techniques for Alzheimer’s Disease in Healthcare Services -- Evolutionary Computing based Feature Selection for Cardiovascular Disease: A Review -- Readiness and Maturity Assessment Model to Measure the Industry 4.0 Ecosystem -- An Insight on Context-aware Mobile Application Execution in Mobile Cloud IoT (MCIoT) -- Breast Cancer Detection in Histology Images using Convolutional Neural Network -- A Novel Approach on Auto Scaling for Resource Scheduling using AWS -- A Blockchain-based COVID19 Protection Framework -- A State-Of-Art of Machine Learning Algorithms Applied Over Language Identification and Speech Recognition Models. |
| Record Nr. | UNINA-9910494560803321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Interpretability for Industry 4.0 : statistical and machine learning approaches / / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi, editors
| Interpretability for Industry 4.0 : statistical and machine learning approaches / / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (130 pages) : illustrations |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Industry 4.0
Machine learning - Industrial applications Industry 4.0 - Statistical methods Aprenentatge automàtic Aplicacions industrials |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-12402-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- 1 Different Views of Interpretability -- 1.1 Introduction -- 1.2 Interpretability: In Praise of Transparent Models -- 1.2.1 What Happened? -- 1.2.2 What Will Happen? -- 1.2.3 What Shall be Done to Make It Happen? -- 1.2.4 Patterns and Models -- 1.3 Generalizability and Interpretability with Industry 4.0 Implications -- 1.3.1 Introduction to Interpretable AI -- 1.3.2 A Wide Angle Perspective of Generalizability -- 1.3.3 Statistical Generalizability -- 1.4 Connections Between Interpretability in Machine Learning and Sensitivity Analysis of Model Outputs -- 1.4.1 Machine Learning and Uncertainty Quantification -- 1.4.2 Basics on Sensitivity Analysis and Its Main Settings -- 1.4.3 A Brief Taxonomy of Interpretability in Machine Learning -- 1.4.4 A Review of Sensitivity Analysis Powered Interpretability Methods -- References -- 2 Model Interpretability, Explainability and Trust for Manufacturing 4.0 -- 2.1 Manufacturing 4.0: Driving Trends for Data Mining -- 2.1.1 Process Monitoring in Manufacturing 4.0 -- 2.1.2 Design of Experiments in Manufacturing 4.0 -- 2.1.3 Increasing Trust in AI Models for Manufacturing 4.0: Interpretability, Explainability and Robustness -- 2.2 Additive Manufacturing as a Paradigmatic Example of Manufacturing 4.0 -- 2.3 Increase Trust in Additive Manufacturing: Robust Functional Analysis of Variance in Video-Image Analysis -- 2.3.1 The RoFANOVA Approach -- 2.3.2 An Additive Manufacturing Application -- References -- 3 Interpretability via Random Forests -- 3.1 Introduction -- 3.2 Interpretable Rule-Based Models -- 3.2.1 Literature Review -- 3.2.1.1 Definitions and Origins of Rule Models -- 3.2.1.2 Decision Trees -- 3.2.1.3 Tree-Based Rule Learning -- 3.2.1.4 Modern Rule Learning -- 3.2.2 SIRUS: Stable and Interpretable RUle Set -- 3.2.2.1 SIRUS Algorithm -- 3.2.2.2 Theoretical Analysis.
3.2.2.3 Experiments -- 3.2.3 Discussion -- 3.3 Post-Processing of Black-Box Algorithms via Variable Importance -- 3.3.1 Literature Review -- 3.3.1.1 Model-Specific Variable Importance -- 3.3.1.2 Global Sensitivity Analysis -- 3.3.1.3 Local Interpretability -- 3.3.2 Sobol-MDA -- 3.3.2.1 Sobol-MDA Algorithm -- 3.3.2.2 Sobol-MDA Properties -- 3.3.2.3 Experiments -- 3.3.3 SHAFF: SHApley eFfects Estimates via Random Forests -- 3.3.3.1 SHAFF Algorithm -- 3.3.3.2 SHAFF Consistency -- 3.3.3.3 Experiments -- 3.3.4 Discussion -- References -- 4 Interpretability in Generalized Additive Models -- 4.1 GAMs: A Basic Framework for Flexible Interpretable Regression -- 4.1.1 Flexibility Can Be Important -- 4.1.2 Making the Model Computable -- 4.1.3 Estimation and Inference -- 4.1.4 Checking, Effective Degrees of Freedom and Model Selection -- 4.1.5 GAM Computation with mgcv in R -- 4.1.6 Smooths of Several Predictors -- 4.1.7 Further Interpretable Structure -- 4.2 From GAM to GAMLSS: Interpretability for Model Building -- 4.2.1 GAMLSS Modelling of UK Aggregate Electricity Demand -- 4.2.1.1 Data Overview and Pre-processing -- 4.2.1.2 Interactive GAMLSS Model Building -- 4.3 From GAMs to Aggregations of Experts, Are We Still Interpretable? -- 4.3.1 Online Forecasting with Online Aggregation of Experts -- 4.3.2 Visualizing the Black Boxes -- References. |
| Record Nr. | UNINA-9910619274503321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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