Challenges And Opportunities For Deep Learning Applications In Industry 4 0
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Challenges And Opportunities For Deep Learning Applications In Industry 4 0
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Author : Vaishali Mehta
language : en
Publisher: Bentham Science Publishers
Release Date : 2022-10-05
Challenges And Opportunities For Deep Learning Applications In Industry 4 0 written by Vaishali Mehta and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-05 with Computers categories.
The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods. The book takes the reader on a technological voyage of the industry 4.0 space. Chapters highlight recent applications of deep learning and the associated challenges and opportunities it presents for automating industrial processes and smart applications. Chapters introduce the reader to a broad range of topics in deep learning and machine learning. Several deep learning techniques used by industrial professionals are covered, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical project methodology. Readers will find information on the value of deep learning in applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. The book also discusses prospective research directions that focus on the theory and practical applications of deep learning in industrial automation. Therefore, the book aims to serve as a comprehensive reference guide for industrial consultants interested in industry 4.0, and as a handbook for beginners in data science and advanced computer science courses.
Industrial Applications Of Machine Learning
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Author : Pedro Larrañaga
language : en
Publisher: CRC Press
Release Date : 2018-12-12
Industrial Applications Of Machine Learning written by Pedro Larrañaga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Business & Economics categories.
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka
Artificial Intelligence And Machine Learning For Industry 4 0
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Author : M. Thirunavukkarasan
language : en
Publisher: John Wiley & Sons
Release Date : 2025-06-10
Artificial Intelligence And Machine Learning For Industry 4 0 written by M. Thirunavukkarasan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Computers categories.
This book is essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. This book emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial Intelligence and Machine Learning for Industry 4.0offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications.
The Future Impact Of Chatgpt On Several Business Sectors
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Author : Dimple Patil
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-28
The Future Impact Of Chatgpt On Several Business Sectors written by Dimple Patil and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-28 with Computers categories.
ChatGPT and other generative AI models are leading the technological revolution. The Future impact of ChatGPT on several business sectors documents the profound impact ChatGPT and artificial intelligence are having and will continue to have on business. A thorough analysis reveals how these tools change interactions, strategies, and efficiencies across industries.vIn the first chapter, we discuss how ChatGPT and generative AI are changing operations, decision-making, and communication across industries. The second chapter examines how ChatGPT redefines customer engagement, personalization, and satisfaction, reshaping customer loyalty. Chapter Three addresses ChatGPT and AI implementation challenges, as every innovation does. We examine the challenges businesses face, from data security to workforce adaptation. Chapter 4 discusses resilience and how ChatGPT helps organizations adapt, mitigate risks, and maintain continuity in unpredictable environments. Chapter Five analyzes ChatGPT adoption across industries, highlighting the challenge of AI integration acceptance. Chapter Six examines new opportunities and applications where ChatGPT's transformative potential grows. Finally, Chapter Seven forecasts ChatGPT's business sector futures and discusses AI's changing role in industry. This book guides businesses, researchers, and anyone interested in ChatGPT's future impact on business.
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0
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Author : Jayesh Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-14
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0 written by Jayesh Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.
Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary to provide perspective on the implications as one continuous stream of technology. It then discusses scalable and adaptive deep learning algorithms, which work in modern machine learning systems where there is a deluge of data. These algorithms sufficiently prepare AI technologies to face the challenges of increasing data as well as expansion of computational capabilities. Chapter three is Federated learning for Edge AI further makes privacy / personalization and security stronger. The amalgamation of blockchain emphasizes the robust and distributed nature of edge intelligence in modern IoT ecosystems. One of the most pressing issues in today's ethical landscape is that of Explainable Artificial Intelligence (XAI), and so the fourth chapter deals with some recent advances in explaining black-box models, providing a way to better understand -and thus potentially trust- AI-driven decision-making processes. This study explores the application of Automated Machine Learning (AutoML) in the contexts of Industry 4.0 and Society 5.0 giving insights on how automation can bring efficiency and innovation in different sectors. It also presents information on the challenges and opportunities that AutoML faces. In conclusion, the book discusses Artificial General Intelligence (AGI), which is a new topic that presents an ambitious view of what AI may be capable of in the future and some points to digest over how the concept might relate to our understanding on what industry may look like in the next stage of human evolution. Individually, these chapters offer a slice of the overall picture of where AI technologies are headed to keep pace with an advancing world.
Machine Learning For Sustainable Manufacturing In Industry 4 0
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Author : Raman Kumar
language : en
Publisher: CRC Press
Release Date : 2023-11-03
Machine Learning For Sustainable Manufacturing In Industry 4 0 written by Raman Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-03 with Technology & Engineering categories.
The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods. Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions. Highlights the importance of the explainable machine learning model in the manufacturing processes. Presents the integration of machine learning and big data analytics from an industry 4.0 perspective. Discusses advanced computational techniques for sustainable manufacturing. Examines environmental impacts of operations and supply chain from an industry 4.0 perspective. This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.
Sustainable Logistics And Production In Industry 4 0
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Author : Katarzyna Grzybowska
language : en
Publisher: Springer Nature
Release Date : 2019-11-30
Sustainable Logistics And Production In Industry 4 0 written by Katarzyna Grzybowska and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-30 with Technology & Engineering categories.
This book proposes essential methods, models, and case studies for Sustainable Logistics and Production in Industry 4.0. In addition to identifying and discussing various challenges and future prospects, it also features numerous case studies and quantitative research from different sectors. The authors (which include academics and managers) present insightful tips on the technical, organizational and social aspects of implementing Sustainable Logistics and Production in Industry 4.0. In today’s world, changes are coming faster and more unpredictably. Production is becoming more automated, computerized and complex. In short, Industry 4.0 is creating many new opportunities, but at the same time several new challenges. This book offers a valuable resource for all academics and practitioners who want to deepen their knowledge of Sustainable Logistics and Production in Industry 4.0.
Intelligent Analytics For Industry 4 0 Applications
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Author : Avinash Chandra Pandey
language : en
Publisher: CRC Press
Release Date : 2023-06-06
Intelligent Analytics For Industry 4 0 Applications written by Avinash Chandra Pandey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Business & Economics categories.
The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.
Artificial Intelligence For Smart Manufacturing And Industry X 0
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Author : M. M. Manjurul Islam
language : en
Publisher: Springer Nature
Release Date : 2025-03-05
Artificial Intelligence For Smart Manufacturing And Industry X 0 written by M. M. Manjurul Islam and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-05 with Technology & Engineering categories.
This book offers a foundational understanding of smart manufacturing (SM) and introduces effective AI methods tailored for smart manufacturing, including supervised, unsupervised, and reinforcement learning techniques. It also features real-world industrial case studies that demonstrate the practical applications of smart manufacturing. Drawing from the invaluable experiences gleaned from the aviation, healthcare, and semiconductors industries, this book provides an in-depth understanding of how AI is driving transformative changes in the manufacturing landscape. In the era of rapid technological advancements, the integration of AI into manufacturing processes has emerged as a game-changer. This book serves as an indispensable guide for navigating this transformation, presenting readers with a multidimensional perspective on the diverse applications, challenges, and opportunities that AI brings to the manufacturing sector. The book explores the emergence of Large Language Models (LLMs) as a valuable tool in manufacturing. It presents how LLMs, especially the GPT series, can process and generate textual data, offering potential applications in areas like smart manufacturing and big-data analysis. It contains detailed case studies, illustrating the practical implementation of smart manufacturing in different industries. The aviation, healthcare, automotive, and semiconductors sectors are examined, highlighting tangible benefits, challenges faced, and lessons learned from each domain. The book addresses the future prospects of Industry 4.0 and beyond—the interconnected, data-driven evolution of manufacturing. It examines the potential impact of emerging technologies such as the Industrial Internet of Things (IIoT), 5G, and advanced robotics on the manufacturing landscape. Challenges and future possibilities pertaining to research and advancement in smart manufacturing within the domains of Aviation, Semiconductors, and Healthcare sectors are also discussed. The chapters are written in a tutorial style to allow early-career researchers and industry practitioners an in-depth understanding of the various topics. The book serves as a reference for researchers, engineers, and students seeking to understand the synergy between AI, Industry 4.0, LLMs, and real-world applications.
Artificial Intelligence And Industry 4 0
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Author : Aboul Ella Hassanien
language : en
Publisher: Academic Press
Release Date : 2022-08-14
Artificial Intelligence And Industry 4 0 written by Aboul Ella Hassanien and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-14 with Technology & Engineering categories.
Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT. - Explores artificial intelligence applications within the industrial manufacturing and communications sectors - Presents a wide range of machine learning, computer vision, and digital twin applications across the IoT sector - Explores how deep learning and cognitive computing tools enable processing vast data sets, precise and comprehensive forecast of risks, and delivering recommended actions