Optimizing Supply Chain in Industry 4.O – Utilizing AI and Big Data Analytics


Book Description

Optimizing Supply Chain in Industry 4.0: Utilizing AI and Big Data Analytics the transformative impact of advanced technologies on supply chain management. How AI and big data analytics revolutionize operations, enabling predictive decision-making, enhanced efficiency, and real-time adaptability. Covering key concepts, applications, and strategies, it actionable insights for leveraging these technologies to build resilient, sustainable, and agile supply chains in the era of Industry 4.0. Designed for professionals, researchers, and students, it bridges theory with practical implementation for optimizing supply chain processes in a rapidly evolving digital landscape.




Supply Chain 4.0


Book Description

Supply Chain 4.0 has introduced automation into logistics and supply chain processes, exploiting predictive analytics to better match supply with demand, optimizing operations and using the latest technologies for the last mile delivery such as drones and autonomous robots. Supply Chain 4.0 presents new methods, techniques, and information systems that support the coordination and optimization of logistics processes, reduction of operational costs as well as the emergence of entirely new services and business processes. This edited collection includes contributions from leading international researchers from academia and industry. It considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, Internet of Things, and decision support systems for transportation and logistics. It also highlights market requirements and includes case studies of cutting-edge applications from innovators in the logistics industry.




Logistics 4.0


Book Description

Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.




Topics in Artificial Intelligence Applied to Industry 4.0


Book Description

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.




Convergence of Industry 4.0 and Supply Chain Sustainability


Book Description

In the ever-increasing landscape of industry and technology, companies worldwide face an unprecedented challenge. The relentless march of progress, epitomized by the revolution of Industry 4.0, demands adaptation for survival and competitiveness. The integration of technologies such as the Internet of Things (IoT), blockchain, artificial intelligence, additive manufacturing, and robotics has irrevocably altered manufacturing and supply chain operations. What was initially a quest for augmented quality and production has now become an inexorable pursuit of sustainability. The United Nations Sustainable Development Goals (UNSDG) 2030 have left no room for exemptions, making sustainability an imperative at the heart of every business strategy. The answer to this pressing challenge lies within the pages of the book, Convergence of Industry 4.0 and Supply Chain Sustainability. It serves a meticulously curated collection of research that illuminates the intricacies of implementing Industry 4.0 and the ramifications for sustainable supply chains. Our work focuses on the associated challenges and opportunities encountered by the adoption of Industry 4.0 in supply chain management (SCM).




Handbook of Smart Manufacturing


Book Description

This handbook covers smart manufacturing development, processing, modifications, and applications. It provides a complete understanding of the recent advancements in smart manufacturing through its various enabling manufacturing technologies, and how industries and organizations can find the needed information on how to implement smart manufacturing towards sustainability of manufacturing practices. Handbook of Smart Manufacturing: Forecasting the Future of Industry 4.0 covers all related advances in manufacturing such as the integration of reverse engineering with smart manufacturing, industrial internet of things (IIoT), and artificial intelligence approaches, including Artificial Neural Network, Markov Decision Process, and Heuristics Methodology. It offers smart manufacturing methods like 4D printing, micro-manufacturing, and processing of smart materials to assist the biomedical industries in the fabrication of human prostheses and implants. The handbook goes on to discuss how to accurately predict the requirements, identify errors, and make innovation for the manufacturing process more manageable by implementing various advanced technologies and solutions into the traditional manufacturing process. Strategies and algorithms used to incorporate smart manufacturing into different sectors are also highlighted within the handbook. This handbook is an invaluable resource for stakeholders, industries, professionals, technocrats, academics, research scholars, senior graduate students, and human healthcare professionals.




Agri-Food 4.0


Book Description

Agri-Food 4.0: Innovations, Challenges and Strategies addresses new research on digital technologies in the Agri-Food industry, including smart packaging, smart warehousing, effective inventory control, blockchain technology, artificial intelligence, and other Industry 4.0 concepts.




Artificial Intelligence for Fashion Industry in the Big Data Era


Book Description

This book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application




Big Data Analytics in Supply Chain Management


Book Description

In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.




Industrial Ecology


Book Description