Industry 4.0 refers to automation and data exchange in manufacturing technologies. From innovative research, challenges, solutions and strategies to real-world case studies, the aim of this edited book is to focus on the nine pillars of technology that are supporting the transition to Industry 4.0 and smart manufacturing. The nine pillars include the internet of things, cloud computing, autonomous and robotics systems, big data analytics, augmented reality, cyber security, simulation, system integration, and additive manufacturing. A key role is played by the industrial IoTs and state-of-the-art technologies such as fog and edge computing, advanced data analytics, innovative data exchange models, artificial intelligence, machine learning, mobile and network technologies, robotics and sensors.
This book is a useful resource for an audience of academic and industry researchers and engineers, as well as advanced students in the fields of information and communication technologies, robotics and automation, big data analytics and data mining, machine learning, artificial intelligence, AR/VR/ER, cybersecurity, cyber physical systems, sensing and robotics with a focus on Industry 4.0, and smart manufacturing.
- Chapter 2: Leading the digital transformation, a Technology Roadmap for Industry 4.0
- Chapter 3: Big Data and Big Data Analytics for Smart Manufacturing
- Chapter 4: Virtual and Augmented Reality in Industry 4.0
- Chapter 5: Cyber-physical systems (CPS) for Industry 4.0
- Chapter 6: The Role of IIoT in Smart Industries 4.0
- Chapter 7: Simulation for Industry 4.0
- Chapter 8: The Role of Artificial Intelligence in Development of Smart Cities
- Chapter 9: Industrial robots: How smart machines will transform everything we know and make sense of it
- Chapter 10: Industrial Automation and Interoperability
- Chapter 11: System integration for Industry 4.0
- Chapter 12: Additive manufacturing for Industry 4.0
- Chapter 13: Cloud Computing in Industrial Revolution 4.0
- Chapter 14: Cybersecurity for Industry 4.0 Context: Background, issues, and future directions
- Chapter 15: Case Studies 1: IoT Based Data Acquisition Monitoring System for Solar Photovoltaic Panel
- Chapter 16: Case Study 2: Internet of Things (IoT) Application for The Development of Building Intelligent Energy Management System
- Chapter 17: Case Study 3: Expert Fault Diagnosis System for Building Air Conditioning Mechanical Ventilation
- Chapter 18: Case Study 4: Lean Integration with Various Tools and Technique towards Industry 4.0
- Chapter 19: Case Study 5: Lean Government in Improving Public Sector Performance towards Industry 4.0
- Chapter 20: Case Study 6: Lean Dominancy in Service Industry 4.0 - Puvanasvaran A Perumal
- Chapter 21: Case Study 21: Security system for solar panel theft based on system integration of GPS tracking and face recognition using deep learning
- Chapter 22: Industry 4.0 and SMEs
- Chapter 23: Project Dragonfly
- Chapter 24: Improving Round-Robin Through Load Adjusted-Load Informed Algorithm in Parallel Database Server Application
- Chapter 25: Virtual Learning System with Enhanced Database Replication
- Chapter 26: 5G Network for Industry 4.0: Reviews and Challenges
Mahsa University, Malaysia.
Professor Wai Yie is the Dean of Engineering and Information Technology of Mahsa University, Malaysia. She specializes in sensing and wireless communications and medical signal processing research including RFID, wireless sensor networks, ultra-wideband and wireless communications, and brain signal processing for signal conditioning and classification in various EEG-based mental tasks. She received the Women Engineer of the Year award in 2018, the IEM Presidential of Excellence Award in 2016 & 2015, and the INTI Outstanding Alumni Award for Academic Excellence in 2016. She holds a PhD in Electrical Engineering (Hons I) from The University of Queensland, Australia.Joon Huang Chuah Senior Lecturer.
University of Malaya, Department of Electrical Engineering, Malaysia.
Dr. Joon Huang Chuah is a Senior Lecturer with the Department of Electrical Engineering, University of Malaya, Malaysia. He is a Chartered Engineer registered under the Engineering Council, UK, and a Professional Engineer with Practising Certificate (PEPC) registered under the Board of Engineers, Malaysia. He serves on several editorial boards, including the Journal of Nanoelectronics and Optoelectronics and the ASEAN Engineering Journal. He has been appointed Scientific Advisor and Technical Consultant for several companies including Genome Solutions, Iconix Consulting, and TrafficSens. He is a Council Member of the Institution of Engineers Malaysia (IEM) and a Committee Member of the Board of Engineers Malaysia (BEM). He received the Ph.D. degree from the University of Cambridge, UK.Tee Boon Tuan Manager.
Universiti Teknikal Malaysia Melaka, Centre for Advanced Research on Energy (CARe), Malaysia.
Professor Tee Boon Tuan is a professor at the Faculty of Mechanical Engineering, Technical University of Malaysia Melaka, Malaysia. His research focuses on energy management system and thermal & environment monitoring. His other professional certifications include Certified Energy Manager under ASEAN Energy Management System (AEMAS) and Certified Professional in Measurement & Verification from Malaysia Greentech. He has been a member of the IET since 2015. He holds a PhD Degree in Engineering from University of Cambridge, UK.