| Description |
1 online resource |
| Contents |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part I: Smart Technologies in Manufacturing -- Chapter 1 Smart Manufacturing Systems for Industry 4.0 -- Abbreviations -- 1.1 Introduction -- 1.2 Research Methodology -- 1.3 Pillars of Smart Manufacturing -- 1.3.1 Manufacturing Technology and Processes -- 1.3.2 Materials -- 1.3.3 Data -- 1.3.4 Sustainability -- 1.3.5 Resource Sharing and Networking -- 1.3.6 Predictive Engineering -- 1.3.7 Stakeholders -- 1.3.8 Standardization -- 1.4 Enablers and Their Applications -- 1.4.1 Smart Design -- 1.4.2 Smart Machining |
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1.4.3 Smart Monitoring -- 1.4.4 Smart Control -- 1.4.5 Smart Scheduling -- 1.5 Assessment of Smart Manufacturing Systems -- 1.6 Challenges in Implementation of Smart Manufacturing Systems -- 1.6.1 Technological Issue -- 1.6.2 Methodological Issue -- 1.7 Implications of the Study for Academicians and Practitioners -- 1.8 Conclusion -- References -- Chapter 2 Smart Manufacturing Technologies in Industry 4.0: Challenges and Opportunities -- Abbreviations -- 2.1 Introduction to Smart Manufacturing -- 2.1.1 Background of SM -- 2.1.2 Traditional Manufacturing versus Smart Manufacturing |
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2.1.3 Concept and Evolution of Industry 4.0 -- 2.1.4 Motivations for Research in Smart Manufacturing -- 2.1.5 Objectives and Need of Industry 4.0 -- 2.1.6 Research Methodology -- 2.1.7 Principles of I4.0 -- 2.1.8 Benefits/Advantages of Industry 4.0 -- 2.2 Technology Pillars of Industry 4.0 -- 2.2.1 Automation in Industry 4.0 -- 2.2.1.1 Need of Automation -- 2.2.1.2 Components of Automation -- 2.2.1.3 Applications of Automation -- 2.2.2 Robots in Industry 4.0 -- 2.2.2.1 Need of Robots -- 2.2.2.2 Advantages of Robots -- 2.2.2.3 Applications of Robots -- 2.2.2.4 Advances Robotics |
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2.2.3 Additive Manufacturing (AM) -- 2.2.3.1 Additive Manufacturing's Potential Applications -- 2.2.4 Big Data Analytics -- 2.2.5 Cloud Computing -- 2.2.6 Cyber Security -- 2.2.6.1 Cyber-Security Challenges in Industry 4.0 -- 2.2.7 Augmented Reality and Virtual Reality -- 2.2.8 Simulation -- 2.2.8.1 Need of Simulation in Smart Manufacturing -- 2.2.8.2 Advantages of Simulation -- 2.2.8.3 Simulation and Digital Twin -- 2.2.9 Digital Twins -- 2.2.9.1 Integration of Horizontal and Vertical Systems -- 2.2.10 IoT and IIoT in Industry 4.0 -- 2.2.11 Artificial Intelligence in Industry 4.0 |
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2.2.12 Implications of the Study for Academicians and Practitioners -- 2.3 Summary and Conclusions -- 2.3.1 Benefits of Industry 4.0 -- 2.3.2 Challenges in Industry 4.0 -- 2.3.3 Future Directions -- Acknowledgement -- References -- Chapter 3 IoT-Based Intelligent Manufacturing System: A Review -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Research Procedure -- 3.3.1 The Beginning and Advancement of SM/IM -- 3.3.2 Beginning of SM/IM -- 3.3.3 Defining SM/IM -- 3.3.4 Potential of SM/IM -- 3.3.5 Statistical Analysis of SM/IM -- 3.3.6 Future Endeavour of SM/IM |
| Summary |
INTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment. The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration. In addition, the reader will find: Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems; Highlights of the current and highly relevant topics in manufacturing management; Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more; Intelligent techniques for sustainable practices in industrial waste management. Audience The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities. |
| Subject |
Production control.
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Production -- Contrôle. |
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Production control |
| Added Author |
Muduli, Kamalakanta.
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Kommula, V. P.
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Yadav, Devendra K.
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Selvan, M. Chithirai Pon.
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Kandasamy, Jayakrishna.
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| Other Form: |
Print version: 1119836247 9781119836247 (OCoLC)1286946435 |
| ISBN |
9781119836780 electronic book |
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1119836786 electronic book |
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9781119836773 electronic book |
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1119836778 electronic book |
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9781119836766 (electronic bk.) |
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111983676X (electronic bk.) |
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hardcover |
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hardcover |
| Standard No. |
10.1002/9781119836780 doi |
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