Monitoring Multimode Continuous Processes
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Monitoring Multimode Continuous Processes
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Author : Marcos Quiñones-Grueiro
language : en
Publisher: Springer Nature
Release Date : 2020-08-04
Monitoring Multimode Continuous Processes written by Marcos Quiñones-Grueiro and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with Technology & Engineering categories.
This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.
Process Monitoring And Fault Diagnosis Based On Multivariable Statistical Analysis
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Author : Xiangyu Kong
language : en
Publisher: Springer Nature
Release Date :
Process Monitoring And Fault Diagnosis Based On Multivariable Statistical Analysis written by Xiangyu Kong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Innovative Techniques And Applications Of Modelling Identification And Control
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Author : Quanmin Zhu
language : en
Publisher: Springer
Release Date : 2018-04-20
Innovative Techniques And Applications Of Modelling Identification And Control written by Quanmin Zhu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-20 with Technology & Engineering categories.
This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems. The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.
Secure And Trusted Cyber Physical Systems
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Author : Shantanu Pal
language : en
Publisher: Springer Nature
Release Date : 2022-09-02
Secure And Trusted Cyber Physical Systems written by Shantanu Pal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-02 with Technology & Engineering categories.
This book highlights the latest design and development of security issues and various defences to construct safe, secure and trusted Cyber-Physical Systems (CPS). In addition, the book presents a detailed analysis of the recent approaches to security solutions and future research directions for large-scale CPS, including its various challenges and significant security requirements. Furthermore, the book provides practical guidance on delivering robust, privacy, and trust-aware CPS at scale. Finally, the book presents a holistic insight into IoT technologies, particularly its latest development in strategic applications in mission-critical systems, including large-scale Industrial IoT, Industry 4.0, and Industrial Control Systems. As such, the book offers an essential reference guide about the latest design and development in CPS for students, engineers, designers, and professional developers.
Artifact Driven Business Process Monitoring
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Author : Giovanni Meroni
language : en
Publisher: Springer Nature
Release Date : 2019-10-23
Artifact Driven Business Process Monitoring written by Giovanni Meroni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-23 with Computers categories.
This book proposes a novel technique, named artifact-driven process monitoring, by which multi-party processes, involving non-automated activities, can be continuously and autonomously monitored. This technique exploits the Internet of Things (IoT) paradigm to make the physical objects, participating in a process, smart. Being equipped with sensors, a computing device, and a communication interface, such smart objects can then become self-aware of their own conditions and of the process they participate in, and exchange this information with the other smart objects and the involved organizations. To allow organizations to reuse preexisting process models, a method to instruct smart objects given Business Process Model and Notation (BPMN) collaboration diagrams is also presented. The work constitutes a revised version of the PhD dissertation written by the author at the PhD School of Information Engineering of Politecnico di Milano, Italy. In 2019, the PhD dissertation won the “CAiSE PhD award”, granted to outstanding PhD theses in the field of Information Systems Engineering.
Process Monitoring And Improvement Handbook Second Edition
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Author : Manuel E. Peña-Rodríguez
language : en
Publisher: Quality Press
Release Date : 2018-08-27
Process Monitoring And Improvement Handbook Second Edition written by Manuel E. Peña-Rodríguez and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-27 with Technology & Engineering categories.
The concept of process monitoring and improvement applies to any type of industry: automotive, textiles, food, pharmaceuticals, biologics, medical devices, electronics, aerospace, banking, educational institutions, service providers, and so on. The focus of this book is to identify and apply different process monitoring and improvement tools in any organization. This book is aimed at engineers, scientists, analysts, technicians, managers, supervisors, and all other professionals responsible to measure and improve the quality of their processes. Many times, these professionals do not have a formal education on the use of these tools but learn about them throughout the different improvement projects in which they are involved in their work environment. This book is intended to fill the gap between the lack of formal education in the tools and the need to implement those tools in an improvement project. The book can also be used as a refresher course for those professionals who did learn about these tools as part of their educational background.
Multivariate Statistical Process Control
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Author : Zhiqiang Ge
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-28
Multivariate Statistical Process Control written by Zhiqiang Ge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Technology & Engineering categories.
Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas. Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Machine Learning In Python For Process And Equipment Condition Monitoring And Predictive Maintenance
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Author : Ankur Kumar
language : en
Publisher: MLforPSE
Release Date : 2024-01-12
Machine Learning In Python For Process And Equipment Condition Monitoring And Predictive Maintenance written by Ankur Kumar and has been published by MLforPSE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-12 with Computers categories.
This book is designed to help readers quickly gain a working knowledge of machine learning-based techniques that are widely employed for building equipment condition monitoring, plantwide monitoring , and predictive maintenance solutions in process industry . The book covers a broad spectrum of techniques ranging from univariate control charts to deep learning-based prediction of remaining useful life. Consequently, the readers can leverage the concepts learned to build advanced solutions for fault detection, fault diagnosis, and fault prognosis. The application focused approach of the book is reader friendly and easily digestible to the practicing and aspiring process engineers and data scientists. Upon completion, readers will be able to confidently navigate the Prognostics and Health Management literature and make judicious selection of modeling approaches suitable for their problems. This book has been divided into seven parts. Part 1 lays down the basic foundations of ML-assisted process and equipment condition monitoring, and predictive maintenance. Part 2 provides in-detail presentation of classical ML techniques for univariate signal monitoring. Different types of control charts and time-series pattern matching methodologies are discussed. Part 3 is focused on the widely popular multivariate statistical process monitoring (MSPM) techniques. Emphasis is paid to both the fault detection and fault isolation/diagnosis aspects. Part 4 covers the process monitoring applications of classical machine learning techniques such as k-NN, isolation forests, support vector machines, etc. These techniques come in handy for processes that cannot be satisfactorily handled via MSPM techniques. Part 5 navigates the world of artificial neural networks (ANN) and studies the different ANN structures that are commonly employed for fault detection and diagnosis in process industry. Part 6 focusses on vibration-based monitoring of rotating machinery and Part 7 deals with prognostic techniques for predictive maintenance applications. Broadly, the book covers the following: Exploratory analysis of process data Best practices for process monitoring and predictive maintenance solutions Univariate monitoring via control charts and time series data mining Multivariate statistical process monitoring techniques (PCA, PLS, FDA, etc.) Machine learning and deep learning techniques to handle dynamic, nonlinear, and multimodal processes Fault detection and diagnosis of rotating machinery using vibration data Remaining useful life predictions for predictive maintenance
Statistical Process Monitoring And Optimization
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Author : Geoffrey Vining
language : en
Publisher: CRC Press
Release Date : 1999-11-24
Statistical Process Monitoring And Optimization written by Geoffrey Vining and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-11-24 with Business & Economics categories.
Demonstrates ways to track industrial processes and performance, integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. The book covers a range o
Neural Information Processing
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Author : Derong Liu
language : en
Publisher: Springer
Release Date : 2017-11-07
Neural Information Processing written by Derong Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-07 with Computers categories.
The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.