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.

Industry 4.0 (i4.0) can unleash new business models or develop essential insights for a better decision-making process. It includes technologies like the Internet of Things (IoT), AI, cloud computing, machine learning, robotics, 5G, and Big Data Analytics (BDA). The imperative of i4.0 can enhance value creation and value capture at the same time with unmatched efficiency. This book explores how entrepreneurs can balance entrepreneurial exploration and exploitation in i4.0. The analytics world is moving beyond the descriptive to predictive, and in the future, it will be more prescriptive enabled by AI, machine learning, expert systems, and 5G. Thus, the future of entrepreneurial exploration and exploitation depends on how information is used to develop insights and to make intelligent, smart, and fact-based decisions to take actions that may have real-time correction mechanisms. As such, i4.0 has implications for students, managers, researchers, policymakers, and politicians alike. This book is a must-read for all.

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.

The Fourth Industrial Revolution, also known as Industry 4.0, refers to the industrial paradigm bringing together the digital and physical worlds through the cyber-physical Systems, enhanced by the Internet of Things aimed to increase the effectiveness of human-machine cooperation (HMC). This book deals with issues related to the challenges of Industry 4.0 that are faced by enterprises and universities. Contrary to most publications on the subject, it covers both technological and business aspects of these challenges and shows how strong they are intertwined, bringing new value to readers. The book also presents new findings that will guide enterprises through Industry 4.0. This book offers readers an in-depth discussion of important areas of enterprises’ activities in the context of Industry 4.0. The first area concerns human resources management; in particular, what new employee competencies will be needed on the labor market, how to use modern concepts (e.g. design thinking), and how to manage multi-national teams of employees. The second area is related to marketing and covers issues regarding customized products. The third area is devoted to technical aspects such as autonomous vehicles, Internet of Things (IoT), radio-frequency identification (RFID) systems, and Bluetooth Low Energy (BLE) technology. The fourth area concerns IT systems, including systems that support work and business management, strategic information systems, and cyber-physical systems. Aimed at researchers, academics, practitioners, and students, it will be of value to those in the fields of human resource management, marketing, organizational studies, and management of technology and innovation.

Enables readers to use real-world data from connected devices to improve product performance, detect design vulnerabilities, and design better solutions Quality in the Era of Industry 4.0 provides an insightful guide in harnessing user performance and behavior data through AI and other Industry 4.0 technologies. This transformative approach enables companies not only to optimize products and services in real-time, but also to anticipate and mitigate likely failures proactively. In a succinct and lucid style, the book presents a pioneering framework for a new paradigm of quality management in the Industry 4.0 landscape. It introduces groundbreaking techniques such as utilizing real-world data to tailor products for superior fit and performance, leveraging connectivity to adapt products to evolving needs and use-cases, and employing cutting-edge manufacturing methods to create bespoke, cost-effective solutions with greater efficiency. Case examples featuring applications from the automotive, mobile device, home appliance, and healthcare industries are used to illustrate how these new quality approaches can be used to benchmark the product’s performance and durability, maintain smart manufacturing, and detect design vulnerabilities. Written by a seasoned expert with experience teaching quality management in both corporate and academic settings, Quality in the Era of Industry 4.0 covers sample topics such as: Evolution of quality through industrial revolutions, from ancient times to the first and second industrial revolutions Quality by customer value creation, explaining differences in producers, stakeholders, and customers in the new digital age, along with new realities brought by Industry 4.0 Data quality dimensions and strategy, data governance, and new talents and skill sets for quality professionals in Industry 4.0 Automated product lifecycle management, predictive quality control, and defect prevention using technologies like smart factories, IoT, and sensors Quality in the Era of Industry 4.0 is a highly valuable resource for product engineers, quality managers, quality engineers and quality consultants, industrial engineers, and systems engineers who wish to make a participatory approach towards data-driven design, economical mass-customization, and late differentiation.

Utilizing Industry 4.0 technologies is essential to meet consumer expectations of personalized products and services but not without obstacles and challenges. This book provides comprehensive knowledge on the operating conditions and challenges of small- and medium-sized enterprises operating in the era of Industry 4.0 and proposes a Business Model 4.0 concept. The authors provide insights on the general conditions for the development of Economy 4.0 and Society 5.0, the expectations of modern consumers in product personalization, customization, servitization and the SME sector's requirements. In addition, the book offers a business model of cooperation between enterprises and the concept of rapid network prototyping methodology for the implementation of personalized products. It proposes the creation of e-business platforms that will allow for better integration of the customer with the manufacturer and the possibility of greater involvement in product configurations. The empirical research offered in this book will provide valuable insights for scholars and upper-level students across business disciplines, including strategic management, entrepreneurship, technology and innovation management.

The growth of digital technologies and Artificial Intelligence (AI) has the potential to increase global wealth and tackle some of the world's most serious problems, including economic marginalization. In contrast, these innovations may contribute to widening economic gaps and potentially threaten the stability of democratic governments. Changes in economic growth and distribution are occurring in both developed and developing countries due to the impact that new technologies are having on businesses and the workplace. This book provides answers to the question of whether the technologies of the Fourth Industrial Revolution, such as Artificial Intelligence, will lead to greater economic uncertainty, environmental collapse, and social unrest or whether they will help achieve shared prosperity and sustainable development, and successively the Sustainable Development Goals (SDGs). The book focuses on Human-centered Artificial Intelligence (AI) and the responsible deployment of diverse technologies for achieving sustainable development. It examines why the human-centred approach is so crucial to long-term success. It underlines the definition of human-centred AI and its importance in creating sustainability and resilience. It starts with a comprehensive history of the Fourth Industrial Revolution, details how to produce artificial intelligence that is centred on humans in order to accomplish sustainable development in the era of the Fourth Industrial Revolution, and then goes on to discuss the need for proper management and governance of emerging technologies. The book ends by presenting a framework that will assist stakeholders in employing AI in a human-centred manner to achieve the sustainable development goals set for 2030. The book will appeal to scholars, academics and researchers interested in information linked to the SDGs, AI and industry 4.0.

This book presents innovative breakthroughs in operational excellence that can solve the operational issues of smart factories. It illustrates various tools and techniques of Lean Six Sigma 4.0 and details their suitability for manufacturing and service systems. Lean Six Sigma 4.0 for Operational Excellence Under the Industry 4.0 Transformation provides technological advancement in operational excellence and offers a framework to integrate Lean Six Sigma and Industry 4.0. The book is a guide to dealing with new operational challenges and explains how to use Industrial IoT, Sensors, and AI to collect real-time data on the shop floor. While focusing on developing a toolset for Lean Six Sigma 4.0, this book also presents the enabling factors to adopt Lean Six Sigma 4.0 in the manufacturing and service sectors. The book will help industrial managers, practitioners, and researchers on the path of process improvement in modern-day industries.

Comprehensive reference exploring the benefits and implementation of digital twins in industrial production and manufacturing Digital Twins in Industrial Production and Smart Manufacturing provides an overview of digital twin theoretical concepts, techniques, and recent trends used to meet the requirements and challenges of industrial production and smart manufacturing. The text describes how to achieve industrial excellence through virtual factory simulation and digital modeling innovations for next-generation manufacturing system design. The contributing authors address the many possible technical advantages of major Industry 5.0 technological advancements, using illustrations to aid readers in practical implementation of concepts, along with existing scenarios, potential research gaps, adoption difficulties, case studies, and future research objectives. The text also presents many applications and use cases of Industry 5.0 and digital twins in a variety of industries, including the aerospace industry, pharmaceutical manufacturing and biotech, augmented reality, virtual reality, edge computing and blockchain-based Internet of Things (IoT), cobots, intelligent logistics and supply chain management, and more. Edited by a group of highly qualified academics with significant experience in the field, Digital Twins in Industrial Production and Smart Manufacturing covers additional topics such as: Hyper-automation technology, including specialized workflow procedures and particular sectors of solicitations linked to hyper-automation Digital twins in the context of smart cities, with attempts to draw comparisons with the use of digital twins in industrial IoT Virtual factories based on digital twins and corresponding architecture to facilitate modeling, simulation, and assessment of manufacturing systems Cognitive, interactive, and standardization aspects of digital twins, and the proper implementation of digital twin technology for safety critical systems Digital Twins in Industrial Production and Smart Manufacturing is a must-have reference for researchers, scholars, and professionals in fields related to digital twins in industrial production and manufacturing. It is also suitable as a hands-on resource for students interested in the fields of digital twins and smart manufacturing.