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Industrial Data Analytics For Diagnosis And Prognosis


Industrial Data Analytics For Diagnosis And Prognosis
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Industrial Data Analytics For Diagnosis And Prognosis


Industrial Data Analytics For Diagnosis And Prognosis
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Author : Shiyu Zhou
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-31

Industrial Data Analytics For Diagnosis And Prognosis written by Shiyu Zhou 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 2021-08-31 with Mathematics categories.


Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.



Industrial Data Analytics For Diagnosis And Prognosis


Industrial Data Analytics For Diagnosis And Prognosis
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Author : Shiyu Zhou
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-21

Industrial Data Analytics For Diagnosis And Prognosis written by Shiyu Zhou 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 2021-07-21 with Mathematics categories.


Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.



Big Data Analytics And Artificial Intelligence In The Healthcare Industry


Big Data Analytics And Artificial Intelligence In The Healthcare Industry
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Author : Machado, José
language : en
Publisher: IGI Global
Release Date : 2022-04-29

Big Data Analytics And Artificial Intelligence In The Healthcare Industry written by Machado, José and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Computers categories.


Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.



Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing


Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing
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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2024-10-23

Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Computers categories.


Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.



Big Data Analytics In Smart Manufacturing


Big Data Analytics In Smart Manufacturing
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Author : P Suresh
language : en
Publisher: CRC Press
Release Date : 2022-12-14

Big Data Analytics In Smart Manufacturing written by P Suresh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-14 with Computers categories.


The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners



Iot Based Data Analytics For The Healthcare Industry


Iot Based Data Analytics For The Healthcare Industry
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Author : Sanjay Kumar Singh
language : en
Publisher: Academic Press
Release Date : 2020-11-07

Iot Based Data Analytics For The Healthcare Industry written by Sanjay Kumar Singh and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-07 with Technology & Engineering categories.


IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. - Provides state-of-art methods and current trends in data analytics for the healthcare industry - Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques - Discusses several potential AI techniques developed using IoT for the healthcare industry - Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages



32nd European Symposium On Computer Aided Process Engineering


32nd European Symposium On Computer Aided Process Engineering
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Author : Ludovic Montastruc
language : en
Publisher: Elsevier
Release Date : 2022-06-30

32nd European Symposium On Computer Aided Process Engineering written by Ludovic Montastruc and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Technology & Engineering categories.


32nd European Symposium on Computer Aided Process Engineering: ESCAPE-32 contains the papers presented at the 32nd European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Toulouse, France. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students and consultants for chemical industries who work in process development and design. - Presents findings and discussions from the 32nd European Symposium of Computer Aided Process Engineering (ESCAPE) event



Data Analytics With Artificial Intelligence Transforming Big Data Into Valuable Information


Data Analytics With Artificial Intelligence Transforming Big Data Into Valuable Information
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Author : Mehmet Ali Yilbasi
language : en
Publisher: Mehmet Ali Yılbaşı
Release Date : 2023-06-11

Data Analytics With Artificial Intelligence Transforming Big Data Into Valuable Information written by Mehmet Ali Yilbasi and has been published by Mehmet Ali Yılbaşı this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-11 with Education categories.


This ebook is a guide for anyone who wants to understand the impact of Data Analytics and Artificial Intelligence in business and explore how these technologies can be applied. Businesses should use this association correctly to extract more valuable information from large data sets, optimize their operational processes and gain competitive advantage. Throughout our book, we will try to explain the potential in Data Analytics and Artificial Intelligence with examples, practical tips and real-world applications. We will also provide resources and recommendations for our readers who want to follow developments in these areas.



The Impact Of Artificial Intelligence On Healthcare Industry


The Impact Of Artificial Intelligence On Healthcare Industry
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Author : Mustafa Berktas
language : en
Publisher: CRC Press
Release Date : 2024-12-06

The Impact Of Artificial Intelligence On Healthcare Industry written by Mustafa Berktas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Computers categories.


Healthcare and medical science are inherently dependent on technological advances and innovations for improved care. In recent times we have witnessed a new drive in implementing these advances and innovations through the use of Artificial Intelligence, in both clinical and non-clinical areas. The set of 2 volumes aims to make available the latest research and applications to all, and to present the current state of clinical and non-clinical applications in the health sector and areas open to development, as well as to provide recommendations to policymakers. This volume covers non-clinical applications. The chapters covered in this book have been written by professionals who are experts in the healthcare sector and have academic experience.



Topics In Artificial Intelligence Applied To Industry 4 0


Topics In Artificial Intelligence Applied To Industry 4 0
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Author : Mahmoud Ragab AL-Refaey
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-15

Topics In Artificial Intelligence Applied To Industry 4 0 written by Mahmoud Ragab AL-Refaey 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 2024-07-15 with Computers categories.


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.