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This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.
Book Synopsis Control Charts and Machine Learning for Anomaly Detection in Manufacturing by : Kim Phuc Tran
Download or read book Control Charts and Machine Learning for Anomaly Detection in Manufacturing written by Kim Phuc Tran and published by Springer Nature. This book was released on 2021-08-29 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.
This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.
Book Synopsis Artificial Intelligence for Smart Manufacturing by : Kim Phuc Tran
Download or read book Artificial Intelligence for Smart Manufacturing written by Kim Phuc Tran and published by Springer Nature. This book was released on 2023-06-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.
FLINS, an acronym originally for Fuzzy Logic and Intelligent Technologies in Nuclear Science, was inaugurated by Prof. Da Ruan of the Belgian Nuclear Research Center (SCK·CEN) in 1994 with the purpose of providing PhD and Postdoc researchers with a platform to present their research ideas in fuzzy logic and artificial intelligence. For more than 28 years, FLINS has been expanded to include research in both theoretical and practical development of computational intelligent systems.With this successful conference series: FLINS1994 and FLINS1996 in Mol, FLINS1998 in Antwerp, FLINS2000 in Bruges, FLINS2002 in Gent, FLINS2004 in Blankenberge, FLINS2006 in Genova, FLINS2008 in Marid, FLINS2010 in Chengdu, FLINS2012 in Istanbul, FLINS2014 in Juan Pesoa, FLINS2016 in Roubaix, FLINS2018 in Belfast and FLINS2020 in Cologne, FLINS2022 was organized by Nankai University, and co-organized by Southwest Jiaotong University, University of Technology Sydney and Ecole Nationale Supérieure des Arts et Industries Textiles of University of Lille. This unique international research collaboration has provided researchers with a platform to share and exchange ideas on state-of-art development in machine learning, multi agent and cyber physical systems.Following the wishes of Prof. Da Ruan, FLINS2022 offered an international platform that brought together mathematicians, computer scientists, and engineers who are actively involved in machine learning, intelligent systems, data analysis, knowledge engineering and their applications, to share their latest innovations and developments, exchange notes on the state-of-the-art research ideas, especially in the areas of industrial microgrids, intelligent wearable systems, sustainable development, logistics, supply chain and production optimization, evaluation systems and performance analysis, as well as risk and security management, that have now become part and parcel of Fuzzy Logic and Intelligent Technologies in Nuclear Science.This FLINS2022 Proceedings has selected 78 conference papers that cover the following seven areas of interests:
Book Synopsis Machine Learning, Multi Agent And Cyber Physical Systems - Proceedings Of The 15th International Flins Conference (Flins 2022) by : Qinglin Sun
Download or read book Machine Learning, Multi Agent And Cyber Physical Systems - Proceedings Of The 15th International Flins Conference (Flins 2022) written by Qinglin Sun and published by World Scientific. This book was released on 2022-12-20 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: FLINS, an acronym originally for Fuzzy Logic and Intelligent Technologies in Nuclear Science, was inaugurated by Prof. Da Ruan of the Belgian Nuclear Research Center (SCK·CEN) in 1994 with the purpose of providing PhD and Postdoc researchers with a platform to present their research ideas in fuzzy logic and artificial intelligence. For more than 28 years, FLINS has been expanded to include research in both theoretical and practical development of computational intelligent systems.With this successful conference series: FLINS1994 and FLINS1996 in Mol, FLINS1998 in Antwerp, FLINS2000 in Bruges, FLINS2002 in Gent, FLINS2004 in Blankenberge, FLINS2006 in Genova, FLINS2008 in Marid, FLINS2010 in Chengdu, FLINS2012 in Istanbul, FLINS2014 in Juan Pesoa, FLINS2016 in Roubaix, FLINS2018 in Belfast and FLINS2020 in Cologne, FLINS2022 was organized by Nankai University, and co-organized by Southwest Jiaotong University, University of Technology Sydney and Ecole Nationale Supérieure des Arts et Industries Textiles of University of Lille. This unique international research collaboration has provided researchers with a platform to share and exchange ideas on state-of-art development in machine learning, multi agent and cyber physical systems.Following the wishes of Prof. Da Ruan, FLINS2022 offered an international platform that brought together mathematicians, computer scientists, and engineers who are actively involved in machine learning, intelligent systems, data analysis, knowledge engineering and their applications, to share their latest innovations and developments, exchange notes on the state-of-the-art research ideas, especially in the areas of industrial microgrids, intelligent wearable systems, sustainable development, logistics, supply chain and production optimization, evaluation systems and performance analysis, as well as risk and security management, that have now become part and parcel of Fuzzy Logic and Intelligent Technologies in Nuclear Science.This FLINS2022 Proceedings has selected 78 conference papers that cover the following seven areas of interests:
This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Book Synopsis Machine Learning and Probabilistic Graphical Models for Decision Support Systems by : Kim Phuc Tran
Download or read book Machine Learning and Probabilistic Graphical Models for Decision Support Systems written by Kim Phuc Tran and published by CRC Press. This book was released on 2022-10-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
This book presents a series of applications of different techniques found in Industry 4.0 with relation to productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different areas of engineering to understand how the use of new technologies is applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. This is accomplished through the analysis of illustrative case studies, descriptive methodologies and structured insights that are provided through the different considered techniques.
Book Synopsis Innovation and Competitiveness in Industry 4.0 Based on Intelligent Systems by : Luis Carlos Méndez-González
Download or read book Innovation and Competitiveness in Industry 4.0 Based on Intelligent Systems written by Luis Carlos Méndez-González and published by Springer Nature. This book was released on 2023-06-16 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a series of applications of different techniques found in Industry 4.0 with relation to productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different areas of engineering to understand how the use of new technologies is applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. This is accomplished through the analysis of illustrative case studies, descriptive methodologies and structured insights that are provided through the different considered techniques.
This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.
Book Synopsis Handbook of Smart Energy Systems by : Michel Fathi
Download or read book Handbook of Smart Energy Systems written by Michel Fathi and published by Springer Nature. This book was released on 2023-08-04 with total page 3382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.
This book describes the potential contributions of emerging technologies in different fields as well as the opportunities and challenges related to the integration of these technologies in the socio-economic sector. In this book, many latest technologies are addressed, particularly in the fields of computer science and engineering. The expected scientific papers covered state-of-the-art technologies, theoretical concepts, standards, product implementation, ongoing research projects, and innovative applications of Sustainable Development. This new technology highlights, the guiding principle of innovation for harnessing frontier technologies and taking full profit from the current technological revolution to reduce gaps that hold back truly inclusive and sustainable development. The fundamental and specific topics are Big Data Analytics, Wireless sensors, IoT, Geospatial technology, Engineering and Mechanization, Modeling Tools, Risk analytics, and preventive systems.
Book Synopsis International Conference on Advanced Intelligent Systems for Sustainable Development by : Janusz Kacprzyk
Download or read book International Conference on Advanced Intelligent Systems for Sustainable Development written by Janusz Kacprzyk and published by Springer Nature. This book was released on 2023-06-09 with total page 995 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the potential contributions of emerging technologies in different fields as well as the opportunities and challenges related to the integration of these technologies in the socio-economic sector. In this book, many latest technologies are addressed, particularly in the fields of computer science and engineering. The expected scientific papers covered state-of-the-art technologies, theoretical concepts, standards, product implementation, ongoing research projects, and innovative applications of Sustainable Development. This new technology highlights, the guiding principle of innovation for harnessing frontier technologies and taking full profit from the current technological revolution to reduce gaps that hold back truly inclusive and sustainable development. The fundamental and specific topics are Big Data Analytics, Wireless sensors, IoT, Geospatial technology, Engineering and Mechanization, Modeling Tools, Risk analytics, and preventive systems.
Book Synopsis Engineering Applications of Neural Networks by : Lazaros Iliadis
Download or read book Engineering Applications of Neural Networks written by Lazaros Iliadis and published by Springer Nature. This book was released on with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods
Book Synopsis Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches by : Fouzi Harrou
Download or read book Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods
The German Academic Association for Production Technology (WGP) annually invites researchers coming from its institutes and from industry to contribute peer reviewed papers in the field of production technology. This congress proceedings provides recent research results and findings on leading-edge manufacturing processes. Main aim of this scientific congress is to push forward existing borders in production and to provide novel solutions of "Production at the Leading Edge of Manufacturing Technology”. Different sessions were held on the topics • Recent Developments in Manufacturing Processes • Advancements in Production Planning • New Approaches in Machine Learning • Aspects of Resilience of Production Processes • Creating Digital Twins for Production
Book Synopsis Production at the Leading Edge of Technology by : Mathias Liewald
Download or read book Production at the Leading Edge of Technology written by Mathias Liewald and published by Springer Nature. This book was released on 2023-02-01 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: The German Academic Association for Production Technology (WGP) annually invites researchers coming from its institutes and from industry to contribute peer reviewed papers in the field of production technology. This congress proceedings provides recent research results and findings on leading-edge manufacturing processes. Main aim of this scientific congress is to push forward existing borders in production and to provide novel solutions of "Production at the Leading Edge of Manufacturing Technology”. Different sessions were held on the topics • Recent Developments in Manufacturing Processes • Advancements in Production Planning • New Approaches in Machine Learning • Aspects of Resilience of Production Processes • Creating Digital Twins for Production
