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Global supply chains are entering an exciting era driven by technological innovation. Buzzwords like Big Data Analytics, IoT, Smart Manufacturing, Smart Logistics and Industries 4.0 are generating both interest and confusion in the business community. This book's comprehensive, one-of-a-kind coverage, journeys from the birth of digital data during Industries 3.0, to the latest practices, trends, and emerging developments in Industries 4.0. The balanced approach of the book follows the natural flow of supply chain processes and provides a deeper insight into the role data analytics plays in streamlining today's business models. Well-organized chapters demonstrate the practical applications of data analytics in today's supply chain workplace, and provide a wealth of real-world business examples. The book provides a step-by-step approach to building your own data analytics strategy.
Book Synopsis Industry 4.0 Data Analytics by : Rajesh Agnihotri
Download or read book Industry 4.0 Data Analytics written by Rajesh Agnihotri and published by Createspace Independent Publishing Platform. This book was released on 2016-07-31 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global supply chains are entering an exciting era driven by technological innovation. Buzzwords like Big Data Analytics, IoT, Smart Manufacturing, Smart Logistics and Industries 4.0 are generating both interest and confusion in the business community. This book's comprehensive, one-of-a-kind coverage, journeys from the birth of digital data during Industries 3.0, to the latest practices, trends, and emerging developments in Industries 4.0. The balanced approach of the book follows the natural flow of supply chain processes and provides a deeper insight into the role data analytics plays in streamlining today's business models. Well-organized chapters demonstrate the practical applications of data analytics in today's supply chain workplace, and provide a wealth of real-world business examples. The book provides a step-by-step approach to building your own data analytics strategy.
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
Book Synopsis Big Data Applications in Industry 4.0 by : P. Kaliraj
Download or read book Big Data Applications in Industry 4.0 written by P. Kaliraj and published by CRC Press. This book was released on 2022-02-10 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.
Book Synopsis Industry 4.0, AI, and Data Science by : Vikram Bali
Download or read book Industry 4.0, AI, and Data Science written by Vikram Bali and published by . This book was released on 2021 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.
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
Book Synopsis Artificial Intelligence and Industry 4.0 by : Aboul Ella Hassanien
Download or read book Artificial Intelligence and Industry 4.0 written by Aboul Ella Hassanien and published by Academic Press. This book was released on 2022-08-14 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Book Synopsis Data Mining and Predictive Analytics by : Daniel T. Larose
Download or read book Data Mining and Predictive Analytics written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2015-02-19 with total page 827 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Industry 4.0 is a revolutionary concept that aims to enhance productivity and profitability in various industries through the implementation of smart manufacturing techniques. This book discusses the profound impact of Industry 4.0, which involves the seamless integration of digital technologies into manufacturing processes within the realm of industrial engineering. Industry 4.0, Smart Manufacturing, and Industrial Engineering: Challenges and Opportunities thoroughly examines the intricate facets of Industry 4.0 and Smart Manufacturing, offering a comprehensive overview of the challenges and opportunities that this paradigm shift presents to industrial engineers. It provides practical insights and strategies to help professionals navigate the complexities of this evolving landscape. Fundamental components of Industry 4.0 and Smart Manufacturing, ranging from the incorporation of sensors and data analytics to the deployment of cyber-physical systems and the promotion of sustainable practices are covered in detail. The book addresses the obstacles and prospects brought about by Industry 4.0 in the digital age and offers solutions to issues such as data security, interoperability, and workforce preparedness. The book sheds light on how Industry 4.0 combines various disciplines, including engineering technology, data science, and management. It serves as a valuable resource for researchers, undergraduate and postgraduate students, as well as professionals operating in the field of industrial engineering and related domains.
Book Synopsis Industry 4.0, Smart Manufacturing, and Industrial Engineering by : Amit Kumar Tyagi
Download or read book Industry 4.0, Smart Manufacturing, and Industrial Engineering written by Amit Kumar Tyagi and published by CRC Press. This book was released on 2024-09-16 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industry 4.0 is a revolutionary concept that aims to enhance productivity and profitability in various industries through the implementation of smart manufacturing techniques. This book discusses the profound impact of Industry 4.0, which involves the seamless integration of digital technologies into manufacturing processes within the realm of industrial engineering. Industry 4.0, Smart Manufacturing, and Industrial Engineering: Challenges and Opportunities thoroughly examines the intricate facets of Industry 4.0 and Smart Manufacturing, offering a comprehensive overview of the challenges and opportunities that this paradigm shift presents to industrial engineers. It provides practical insights and strategies to help professionals navigate the complexities of this evolving landscape. Fundamental components of Industry 4.0 and Smart Manufacturing, ranging from the incorporation of sensors and data analytics to the deployment of cyber-physical systems and the promotion of sustainable practices are covered in detail. The book addresses the obstacles and prospects brought about by Industry 4.0 in the digital age and offers solutions to issues such as data security, interoperability, and workforce preparedness. The book sheds light on how Industry 4.0 combines various disciplines, including engineering technology, data science, and management. It serves as a valuable resource for researchers, undergraduate and postgraduate students, as well as professionals operating in the field of industrial engineering and related domains.
This book presents essentially a collection of proceedings that deliberate on the key challenges and recent trends on robotics, automation and data analytics which are the pillars of Industry 4.0. Solutions that are employed in the multitude spectra of innovative robotics & automation and data analytics are discussed. The readers are expected to gain an insightful view on the current trends, issues, mitigating factors as well as solutions from the book. This book consists of selected papers presented at the 2nd International Conference on Innovative Technology, Engineering and Sciences 2020 (iCITES) hosted virtually by Universiti Malaysia Pahang on 22nd December 2020. iCITES is a biennial conference, aimed at building a platform that allows relevant stakeholders to share and discuss their latest researches, ideas and survey reports from theoretical to a practical standpoint especially in the Innovative Robotics & Automation and Data Analytics tracks which was published in this book.
Book Synopsis Advances in Robotics, Automation and Data Analytics by : Jessnor Arif Mat Jizat
Download or read book Advances in Robotics, Automation and Data Analytics written by Jessnor Arif Mat Jizat and published by Springer Nature. This book was released on 2021-03-10 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents essentially a collection of proceedings that deliberate on the key challenges and recent trends on robotics, automation and data analytics which are the pillars of Industry 4.0. Solutions that are employed in the multitude spectra of innovative robotics & automation and data analytics are discussed. The readers are expected to gain an insightful view on the current trends, issues, mitigating factors as well as solutions from the book. This book consists of selected papers presented at the 2nd International Conference on Innovative Technology, Engineering and Sciences 2020 (iCITES) hosted virtually by Universiti Malaysia Pahang on 22nd December 2020. iCITES is a biennial conference, aimed at building a platform that allows relevant stakeholders to share and discuss their latest researches, ideas and survey reports from theoretical to a practical standpoint especially in the Innovative Robotics & Automation and Data Analytics tracks which was published in this book.
Business innovation and industrial intelligence are paving the way for a future in which smart factories, intelligent machines, networked processes and Big Data are combined to foster industrial growth. The maturity and growth of instrumentation, monitoring and automation as key technology drivers support Industry 4.0 as a viable, competent and actionable business model. This book offers a primer, helping readers understand this paradigm shift from industry 1.0 to industry 4.0. The focus is on grasping the necessary pre-conditions, development & technological aspects that conceptually describe this transformation, along with the practices, models and real-time experience needed to achieve sustainable smart manufacturing technologies. The primary goal is to address significant questions of what, how and why in this context, such as:What is Industry 4.0?What is the current status of its implementation?What are the pillars of Industry 4.0?How can Industry 4.0 be effectively implemented?How are firms exploiting the Internet of Things (IoT), Big Data and other emerging technologies to improve their production and services?How can the implementation of Industry 4.0 be accelerated?How is Industry 4.0 changing the workplace landscape?Why is this melding of the virtual and physical world needed for smart production engineering environments?Why is smart production a game-changing new form of product design and manufacturing?
Book Synopsis A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development by : Anand Nayyar
Download or read book A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development written by Anand Nayyar and published by Springer Nature. This book was released on 2019-11-27 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business innovation and industrial intelligence are paving the way for a future in which smart factories, intelligent machines, networked processes and Big Data are combined to foster industrial growth. The maturity and growth of instrumentation, monitoring and automation as key technology drivers support Industry 4.0 as a viable, competent and actionable business model. This book offers a primer, helping readers understand this paradigm shift from industry 1.0 to industry 4.0. The focus is on grasping the necessary pre-conditions, development & technological aspects that conceptually describe this transformation, along with the practices, models and real-time experience needed to achieve sustainable smart manufacturing technologies. The primary goal is to address significant questions of what, how and why in this context, such as:What is Industry 4.0?What is the current status of its implementation?What are the pillars of Industry 4.0?How can Industry 4.0 be effectively implemented?How are firms exploiting the Internet of Things (IoT), Big Data and other emerging technologies to improve their production and services?How can the implementation of Industry 4.0 be accelerated?How is Industry 4.0 changing the workplace landscape?Why is this melding of the virtual and physical world needed for smart production engineering environments?Why is smart production a game-changing new form of product design and manufacturing?
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Book Synopsis Guide to Industrial Analytics by : Richard Hill
Download or read book Guide to Industrial Analytics written by Richard Hill and published by Springer Nature. This book was released on 2021-09-27 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
The book addresses the needs of researchers on the fundamentals as well as more advanced knowledge on microgrids and their evolution. This book covers newly emerging trends in fields such as Computer Science, Energy, Electrical Engineering, and Electronics and brings the reader up-to-date on the new emerging fields that play an important role in the power infrastructure. This book provides knowledge on decision making for newly evolving trends in microgrid design. It discusses techniques on how to improve the existing power quality and reduce load shedding and power imbalances. The book presents the emerging fields that now play an important role in microgrid design such as Data Science, Machine Learning, AI, and IT. The readership includes researchers, academia, practicing engineers, consumers, power companies and policy makers located across the globe.
Book Synopsis Microgrids by : Ghous Bakhsh Narejo
Download or read book Microgrids written by Ghous Bakhsh Narejo and published by CRC Press. This book was released on 2021-10-12 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book addresses the needs of researchers on the fundamentals as well as more advanced knowledge on microgrids and their evolution. This book covers newly emerging trends in fields such as Computer Science, Energy, Electrical Engineering, and Electronics and brings the reader up-to-date on the new emerging fields that play an important role in the power infrastructure. This book provides knowledge on decision making for newly evolving trends in microgrid design. It discusses techniques on how to improve the existing power quality and reduce load shedding and power imbalances. The book presents the emerging fields that now play an important role in microgrid design such as Data Science, Machine Learning, AI, and IT. The readership includes researchers, academia, practicing engineers, consumers, power companies and policy makers located across the globe.
