This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications. Industry 4.0, the Fourth Industrial Revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in the industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance. Features Presents a comprehensive guide on how to use machine vision for Industry 4.0 applications, such as analysis of images for automated inspections, object detection, object tracking, and more Includes case studies of Robotics Internet of Things with its current and future applications in healthcare, agriculture, and transportation Highlights the inclusion of impaired people in the industry, for example, an intelligent assistant that helps deaf-mute individuals to transmit instructions and warnings in a manufacturing process Examines the significant technological advancements in machine vision for Industrial Internet of Things and explores the commercial benefits using real-world applications from healthcare to transportation Discusses a conceptual framework of machine vision for various industrial applications The book addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone interested in the trends, development, and opportunities for machine vision for Industry 4.0 applications.

The research and exploitation of optoelectronic properties in the industrial branch of electronics is becoming more popular each day due to the important role they play in the development of a large variety of sensors, devices, and systems for identifying, measuring, and constructing. While optoelectronics study the applications of electronic devices that source, detect, and transform light, machine vision generates and detects light in order to provide imaging-based automatic inspections and analysis for such applications as automatic object and environmental inspection, process control, and robot/mobile machine guidance in industry. Machine vision is less efficient without optoelectronics, and thus, it is important to investigate the theoretical approaches to different optoelectronic devices available for machine vision as well as current scanning technologies. Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications. The book covers topics such as the design, fabrication, and implementation of sensors and devices as well as the development viewpoint of optoelectronic systems and artificial vision techniques using optoelectronic devices. The interaction and informational communication between all these mentioned devices in the complex solution of the same task is the subject of modern challenges in Industry 4.0. Thus, this book supports engineers, technology developers, academicians, researchers, and students who seek machine vision techniques for detection, measurement, and 3D reconstruction.

Industry 4.0 Vision for the Supply of Energy and Materials Explore the impact of Industry 4.0 technologies on the supply chain with this authoritative text written by a leader in his field In Industry 4.0 Vision for the Supply of Energy and Materials, distinguished researcher and editor, Dr. Mahdi Sharifzadeh, delivers thematic, analytic, and applied discussions of the Industry 4.0 vision for supply chain design and operation. The book compiles all current aspects and emerging notions of Industry 4.0 into clusters of “enablers” and “analytics” of Supply Chain 4.0. Their multifaceted and highly interconnected nature is discussed at length, as are their diverse range of applications. You will discover uses of these new technologies ranging from the supply of conventional energy networks to renewables, pharmaceuticals, and additive manufacturing. You will also learn about their implications for economic prosperity and environmental sustainability. For each sector, this book scrutinizes current industrial practice and discusses developing concepts. Finally, the book concludes with potential future research directions of interest to industry practitioners and academics alike. Readers will also benefit from the inclusion of: A thorough introduction to connectivity through wireless communications and remote sensors An exploration of blockchains and smart contracts, as well as robotics and automation and cloud computing Practical discussions of supply chain analytics, including big data, machine-learning, and artificial intelligence, as well as supply chain modeling, optimization, and control A concise treatment of Industry 4.0 applications in supply chain design and operation, including the circular economy and the power industry An analysis of the oil, gas, and petrochemical industry, the pharmaceutical industry, and additive manufacturing Perfect for PhD-level and Postdoctoral researchers and industrial researchers, Industry 4.0 Vision for the Supply of Energy and Materials will also earn a place in the libraries of working professionals with an interest in the quantitative analysis of Supply Chain 4.0 concepts and techniques.

This book gathers the proceedings of the 12th International Conference on Measurement and Quality Control – Cyber Physical Issues (IMEKO TC 14 2019), held in Belgrade, Serbia, on 4–7 June 2019. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of measurement of geometrical quantities. The book addresses a wide range of topics, including: 3D measurement of GPS characteristics, measurement of gears and threads, measurement of roughness, micro- and nano-metrology, laser metrology for precision measurements, cyber physical metrology, optical measurement techniques, industrial computed tomography, multisensor techniques, intelligent measurement systems, evaluating measurement uncertainty, dimensional management in industry, product quality assurance methods, and big data analytics. By providing updates on key issues and highlighting recent advances in measurement and quality control, the book supports the transfer of vital knowledge to the next generation of academics and practitioners.

This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications. Industry 4.0, the Fourth Industrial Revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in the industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance. Features Presents a comprehensive guide on how to use machine vision for Industry 4.0 applications, such as analysis of images for automated inspections, object detection, object tracking, and more Includes case studies of Robotics Internet of Things with its current and future applications in healthcare, agriculture, and transportation Highlights the inclusion of impaired people in the industry, for example, an intelligent assistant that helps deaf-mute individuals to transmit instructions and warnings in a manufacturing process Examines the significant technological advancements in machine vision for Industrial Internet of Things and explores the commercial benefits using real-world applications from healthcare to transportation Discusses a conceptual framework of machine vision for various industrial applications The book addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone interested in the trends, development, and opportunities for machine vision for Industry 4.0 applications.

The book consists of high-quality papers presented at the International Conference on Computational Science and Applications (ICCSA 2019), held at Maharashtra Institute of Technology World Peace University, Pune, India, from 7 to 9 August 2019. It covers the latest innovations and developments in information and communication technology, discussing topics such as soft computing and intelligent systems, web of sensor networks, drone operating systems, web of sensor networks, wearable smart sensors, automated guided vehicles and many more.

Get up to speed with how the latest knowledge management and industry 4.0 technologyhelp make enterprises secure, controlled, and optimized for a better future. This book focuses on how the practices of Industrial Revolution 4.0 and knowledge management interact to create value. In recent years, value chain relationships and related activities have utilized new technologies so that existing conceptual frameworks require a roadmap for innovation strategies and effective implementation. The chapters in this book include case studies contributed by researchers and industry practitioners that showcase the impact of practices and challenges presented by technological changes, upgrading of old systems, and internal and external factors. Knowledge Management and Industrial Revolution 4.0 describes how knowledge management impacts the automation of the industry in secure, controlled, and optimized ways. For instance, the use of the latest technologies and sensors can lead to significant time and cost savings, and operators can utilize their machines and equipment from remote locations. The Industrial Revolution 4.0 incorporates the latest technologies for automation and, in many cases, the result is similar to working from home, even in manufacturing. The use of deep learning should offer many quality control benefits. Furthermore, blockchain technology can help the industry with automation in secure and transparent ways. Apart from industry automation, other departments like human resources can also use effective knowledge management for better outcomes. The use of HR knowledge management allows employees to find and access the information they require without the assistance of the HR department. The book focuses on every aspect of the industry to help all the stakeholders of an organization. The benefits include a reduction in time required for accessing information, easier training, decreased operational expenses, improved stakeholders’ satisfaction, faster problem-solving, increased pace of innovation, simpler employee review and progress reports. Audience The book will have a wide audience within academia, education, businesses, and industrial organizations, especially those who are undergoing industry 4.0 changes to optimize for a better future.

Topics in Artificial Intelligence Applied to Industry 4.0 Forward thinking resource discussing emerging AI and IoT technologies and how they are applied to Industry 4.0 Topics in Artificial Intelligence Applied to Industry 4.0 discusses the design principles, technologies, and applications of emerging AI and IoT solutions on Industry 4.0, explaining how to make improvements in infrastructure through emerging technologies. Providing a clear connection with different technologies such as IoT, Big Data, AR and VR, and Blockchain, this book presents security, privacy, trust, and other issues whilst delving into real-world problems and case studies. The text takes a highly practical approach, with a clear insight on how readers can increase productivity by drastically shortening the time period between the development of a new product and its delivery to customers in the market by 50%. This book also discusses how to save energy across systems to ensure competitiveness in a global market, and become more responsive in how they produce products and services for their consumers, such as by investing in flexible production lines. Written by highly qualified authors, Topics in Artificial Intelligence Applied to Industry 4.0 explores sample topics such as: Quantum machine learning, neural network implementation, and cloud and data analytics for effective analysis of industrial data Computer vision, emerging networking technologies, industrial data spaces, and an industry vision for 2030 in both developing and developed nations Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart environment Future professions in agriculture, medicine, education, fitness, R&D, and transport and communication as a result of new technologies Aimed at researchers and students in the interdisciplinary fields of Smart Manufacturing and Smart Applications, Topics in Artificial Intelligence Applied to Industry 4.0 provides the perfect overview of technology from the perspective of modern society and operational environment.

Known models for assessing the readiness and level of Industry 4.0 implementation are helpful in revealing key technological and non-technological aspects relevant in the frame of Industry 4.0 implementation in organizations. At the forefront are technological aspects of Industry 4.0 implementation in organizations, while non-technological aspects play a marginal role. Building upon ample evidence about the role of non-technological aspects of Industry 4.0 implementation in organizations, this book addresses these ever-important non-technological aspects. The authors address the role of management solutions in the framework of Industry 4.0 implementation through the utilization of various management tools, which support organizations working in all organizational areas. The importance of humans for Industry 4.0 is currently severely neglected, despite the many changes in the workplace. Thus, new challenges for human resource management (HRM) have emerged, such as technostress, human–robot interaction (HRI), and new tasks for employees. Non-technological aspects of Industry 4.0 are broadly influencing entire organizations, as the management tools support the working of organizations in all areas. Focusing on non-technological aspects of Industry 4.0 implementation, this book considers the utilization of traditional management tools as a key vehicle for supporting implementation in organizations. In terms of the importance of humans for implementation, at the forefront are changes in the workplace due to Industry 4.0, HRIs, and changing HRM practices. This book will be of value to researchers, academics, and advanced students in the fields of organizational studies, HRM, and change management.