Integration Of Ai Based Manufacturing And Industrial Engineering Systems With The Internet Of Things

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments. The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency. A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

INDUSTRIAL INTERNET OF THINGS (IIOT) This book discusses how the industrial internet will be augmented through increased network agility, integrated artificial intelligence (AI) and the capacity to deploy, automate, orchestrate, and secure diverse user cases at hyperscale. Since the internet of things (IoT) dominates all sectors of technology, from home to industry, automation through IoT devices is changing the processes of our daily lives. For example, more and more businesses are adopting and accepting industrial automation on a large scale, with the market for industrial robots expected to reach $73.5 billion in 2023. The primary reason for adopting IoT industrial automation in businesses is the benefits it provides, including enhanced efficiency, high accuracy, cost-effectiveness, quick process completion, low power consumption, fewer errors, and ease of control. The 15 chapters in the book showcase industrial automation through the IoT by including case studies in the areas of the IIoT, robotic and intelligent systems, and web-based applications which will be of interest to working professionals and those in education and research involved in a broad cross-section of technical disciplines. The volume will help industry leaders by Advancing hands-on experience working with industrial architecture Demonstrating the potential of cloud-based Industrial IoT platforms, analytics, and protocols Putting forward business models revitalizing the workforce with Industry 4.0. Audience Researchers and scholars in industrial engineering and manufacturing, artificial intelligence, cyber-physical systems, robotics, safety engineering, safety-critical systems, and application domain communities such as aerospace, agriculture, automotive, critical infrastructures, healthcare, manufacturing, retail, smart transports, smart cities, and smart healthcare.

INTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment. The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration. In addition, the reader will find: Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems; Highlights of the current and highly relevant topics in manufacturing management; Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more; Intelligent techniques for sustainable practices in industrial waste management. Audience The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities.

This book presents the trends, challenges, and advances in Internet of Things (IoT) in the areas of industrial management and industrial engineering. The authors look at how smart environments (smart city, smart university, smart regions, smart transportation, etc.) affect the way industrial management and industrial engineering are envisioned, planned, and applied and how engineers must incorporate new ideas and methods now and in the future. Some topics include the impact of ICT on the emergency response vehicle driving time, car accident detecting systems based on machine learning algorithms, smart city platforms based on citizen reporting services, and IoT-based household energy consumption prediction using machine learning. The book brings together contributions from academics and practitioners from around the world to discuss the intersection of IoT, industry and management.

INTEGRATION OF MECHANICAL AND MANUFACTURING ENGINEERING WITH IOT The book provides researchers, professionals, and students with a resource on the basic principles of IoT and its applications, as well as a guide to practicing engineers who want to understand how the Internet of Things can be implemented for different fields of mechanical and manufacturing engineering. This book broadly explores the latest developments of IoT and its integration into mechanical and manufacturing engineering. It details the fundamental concepts and recent developments in IoT & Industry 4.0 with special emphasis on the mechanical engineering platform for such issues as product development and manufacturing, environmental monitoring, automotive applications, energy management, and renewable energy sectors. Topics and related concepts are portrayed comprehensively so that readers can develop expertise and knowledge in the field of IoT. It is packed with reference tables and schematic diagrams for the most commonly used processes and techniques, thereby providing a resource on the basic principles and application of IoT in manufacturing sectors. Audience The book will be read by academic researchers, industry engineers, and R&D personnel in materials, information and technology, artificial intelligence, and manufacturing. The book will greatly assist graduate students.

This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools. This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.

This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments. AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances. This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.

Industrial systems integration is a very diverse topic. It includes the primary technologies of industrial processes, industrial automation systems, industrial networks, industrial systems integration software applications, safety systems, energy systems, and manufacturing management software applications. Therefore, it is difficult to find literature that covers all the areas of industrial systems integration in a coherent manner. In addition, the new manufacturing paradigm of Industry 4.0 has increased the need for experts in industrial systems integration, because it is based on Industrial Internet of Things which is a product of industrial systems integration. This book is a result of lecture notes that the author has developed and refined over many years to cover the theory and practice of industrial systems integration in a coherent manner for those aspiring to become experts in industrial systems integration in particular and Industry 4.0 in general. Principally, the book is written for senior undergraduate and graduate students studying mechanical engineering, manufacturing engineering, electrical engineering, software engineering, automation and smart systems engineering, and computer science. The text is also useful to those in industry who are interested in the implementation of the Industry 4.0 manufacturing paradigm