Industry 4 0 The Power Of Data

This book is a compilation of some of the best papers presented at the 15th International Conference on Industrial Engineering and Industrial Management in 2021. The Conference was promoted by ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización), organized by the University of Burgos, and it took place online on July 8 and 9, 2021. The book highlights some of the latest research advances and cutting-edge analyses of real-world case studies on industrial engineering and industrial management from a wide range of international contexts. It also identifies business applications and the latest findings and innovations in operations management and decision sciences. Industry 4.0: The Power of Data will help academic researchers and practitioners in industrial engineering and industrial management to keep abreast of state-of-the-art developments in these subjects.

World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolu­tion, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wear­able sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manu­facturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individu­als. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frame­works that advance progress.

Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making

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.

This book constitutes the refereed proceedings of the 15th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2019, held in Ustroń, Poland, in May 2019. It consists of 26 carefully reviewed papers selected from 69 submissions. The papers are organized in topical sections, namely big data and cloud computing; architectures, structures and algorithms for efficient data processing and analysis; artificial intelligence, data mining and knowledge discovery; image analysis and multimedia mining; bioinformatics and biomedical data analysis; industrial applications; networks and security.

This book introduces fundamental, advanced, and future-oriented scientific quality management methods for the engineering and manufacturing industries. It presents new knowledge and experiences in the manufacturing industry with real world case studies. It introduces Quality 4.0 with Industry 4.0, including quality engineering tools for software quality and offers lean quality management methods for lean manufacturing. It also bridges the gap between quality management and quality engineering, and offers a scientific methodology for problem solving and prevention. The methods, techniques, templates, and processes introduced in this book can be utilized in various areas in industry, from product engineering to manufacturing and shop floor management. This book will be of interest to manufacturing industry leaders and managers, who do not require in-depth engineering knowledge. It will also be helpful to engineers in design and suppliers in management and manufacturing, all who have daily concerns with project and quality management. Students in business and engineering programs may also find this book useful as they prepare for careers in the engineering and manufacturing industries. Presents new knowledge and experiences in the manufacturing industry with real world case studies Introduces quality engineering methods for software development Introduces Quality 4.0 with Industry 4.0 Offers lean quality management methods for lean manufacturing Bridges the gap between quality management methods and quality engineering Provides scientific methodology for product planning, problem solving and prevention management Includes forms, templates, and tools that can be used conveniently in the field

This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap. Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry.