This book addresses the topic of integrated digitization of plants on an objective basis and in a holistic manner by sharing data, applying analytics tools and integrating workflows via pertinent examples from industry. It begins with an evaluation of current performance management practices and an overview of the need for a "Connected Plant" via digitalization followed by sections on "Connected Assets: Improve Reliability and Utilization," "Connected Processes: Optimize Performance and Economic Margin " and "Connected People: Digitalizing the Workforce and Workflows and Developing Ownership and Digital Culture," then culminating in a final section entitled "Putting All Together Into an Intelligent Digital Twin Platform for Smart Operations and Demonstrated by Application cases."
This book offers the latest research on formation of modern workers in the context of digitalization: from constant improvement of new training technologies to growing requirements for employees in workplace, as well as an assessment of specialists' digital skills and dynamics of changes over the past years. The book proposes to look at the pool of these problems through the prism of acquisition of new digital competencies and requirements for a modern worker. This book is intended for both young and experienced scientists who want to get acquainted with latest trends and data to use them in their research.
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin—an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system’s behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI’s capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.
Plant Intelligent Automation and Digital Transformation: Process and Factory Automation is an expansive four volume collection reviewing every major aspect of the intelligent automation and digital transformation of power, process and manufacturing plants, from the specific control and automation systems pertinent to various power process plants through manufacturing and factory automation systems. This volume introduces the foundations of automation control theory, networking practices and communication for power, process and manufacturing plants considered as integrated digital systems. In addition, it discusses Distributed control System (DCS) for Closed loop controls system (CLCS) and PLC based systems for Open loop control systems (OLCS) and factory automation. This book provides in-depth guidance on functional and design details pertinent to each of the control types referenced above, along with the installation and commissioning of control systems. - Introduces the foundations of control systems, networking and industrial data communications for power, process and manufacturing plant automation - Reviews core functions, design details and optimized configurations of plant digital control systems - Addresses advanced process control for digital control systems (inclusive of software implementations) - Provides guidance for installation commissioning of control systems in working plants
Plant Intelligent Automation and Digital Transformation: Volume II: Control and Monitoring Hardware and Software is an expansive four volume collection that reviews every major aspect of the intelligent automation and digital transformation of power, process and manufacturing plants, including specific control and automation systems pertinent to various power process plants using manufacturing and factory automation systems. The book reviews the key role of management Information systems (MIS), HMI and alarm systems in plant automation in systemic digitalization, covering hardware and software implementations for embedded microcontrollers, FPGA and operator and engineering stations. Chapters address plant lifecycle considerations, inclusive of plant hazards and risk analysis. Finally, the book discusses industry 4.0 factory automation as a component of digitalization strategies as well as digital transformation of power plants, process plants and manufacturing industries. - Reviews supervisory control and data acquisitions (SCADA) systems for real-time plant data analysis - Provides practitioner perspectives on operational implementation, including human machine interface, operator workstation and engineering workstations - Covers alarm and alarm management systems, including lifecycle considerations - Fully covers risk analysis and assessment, including safety lifecycle and relevant safety instrumentation
This book captures the path of digital transformation that the cement enterprises are adopting progressively to elevate themselves to ‘Industry 4.0’ level. Digital innovations-based Internet of Things (IoT) and Artificial Intelligence (AI) are pertinent technologies for the cement enterprises as the manufacturing processes operate at very large scales with multiple inputs, outputs, and variables, resulting in the essentiality of big data management. Featuring contributions from cement industries worldwide, it covers various aspects of cement manufacturing from IoT, machine learning and data analytics perspective. It further discusses implementation of digital solutions in cement process and plants through case studies. Features: Present an up-to-date, consolidated view on modern cement manufacturing technology, applying new systems. Provides narration of complexity and variables in modern cement plants and processes. Discusses evolution of automation and computerization for the manufacturing processes. Covers application of ERP techniques to cement enterprises. Includes data-driven approaches for energy, environment, and quality management. This book aims at researchers and industry professionals involved in cement manufacturing, cement machinery and system suppliers, chemical engineering, process engineering, industrial engineering, and chemistry.
This book gathers the most recent developments in fuzzy & intelligence systems and real complex systems presented at INFUS 2020, held in Istanbul on July 21–23, 2020. The INFUS conferences are a well-established international research forum to advance the foundations and applications of intelligent and fuzzy systems, computational intelligence, and soft computing, highlighting studies on fuzzy & intelligence systems and real complex systems at universities and international research institutions. Covering a range of topics, including the theory and applications of fuzzy set extensions such as intuitionistic fuzzy sets, hesitant fuzzy sets, spherical fuzzy sets, and fuzzy decision-making; machine learning; risk assessment; heuristics; and clustering, the book is a valuable resource for academics, M.Sc. and Ph.D. students, as well as managers and engineers in industry and the service sectors.
The book concentrates on the impact of digitalization and digital transformation technologies on the Industry 4.0 and smart factories, how the factory of tomorrow can be designed, built, and run virtually as a digital twin likeness of its real-world counterpart, before the physical structure is actually erected. It highlights the main digitalization technologies that have stimulated the Industry 4.0, how these technologies work and integrate with each other, and how they are shaping the industry of the future. It examines how multimedia data and digital images in particular are being leveraged to create fully virtualized worlds in the form of digital twin factories and fully virtualized industrial assets. It uses BMW Group’s latest SORDI dataset (Synthetic Object Recognition Dataset for Industry), i.e., the largest industrial images dataset to-date and its applications at BMW Group and Idealworks, as one of the main explanatory scenarios throughout the book. It discusses the need of synthetic data to train advanced deep learning computer vision models, and how such datasets will help create the “robot gym” of the future: training robots on synthetic images to prepare them to function in the real world.
