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Author: Fouzi Harrou
Publisher: Elsevier
ISBN: 0128193662
Category : Technology & Engineering
Languages : en
Pages : 330
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Book Description
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
Author: Fouzi Harrou
Publisher: Elsevier
ISBN: 0128193662
Category : Technology & Engineering
Languages : en
Pages : 330
Get Book Here
Book Description
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
Author: Kim Phuc Tran
Publisher: Springer Nature
ISBN: 3030838196
Category : Technology & Engineering
Languages : en
Pages : 270
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Book Description
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.
Author: Loon Ching Tang
Publisher: John Wiley & Sons
ISBN: 0470061995
Category : Technology & Engineering
Languages : en
Pages : 426
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Book Description
The 2007 winner of the Masing Book Prize sets out important Six Sigma concepts and a selection of up-to-date tools for quality improvement in industry. Six Sigma is a widely used methodology for measuring and improving an organization’s operational performance through a rigorous analysis of its practices and systems. This book presents a series of papers providing a systematic ‘roadmap’ for implementing Six Sigma, following the DMAIC (Define, Measure, Analyse, Improve and Control) phased approach. Motivated by actual problems, the authors offer insightful solutions to some of the most commonly encountered issues in Six Sigma projects, such as validation of normality, experimentation under constraints and statistical control of complex processes. They also include many examples and case studies to help readers learn how to apply the appropriate techniques to real-world problems. Key features: Provides a comprehensive introduction to Six Sigma, with a critical strategic assessment and a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. Presents some prominent design features of Six Sigma, and a newly proposed roadmap for healthcare delivery. Sets out information on graphical tools, including fishbone diagrams, mind-maps, and reality trees. Gives a thorough treatment of process capability analysis for non-normal data. Discusses advanced tools for Six Sigma, such as statistical process control for autocorrelated data. Consolidating valuable methodologies for process optimization and quality improvement, Six Sigma: Advanced Tools for Black Belts and Master Black Belts is a unique reference for practising engineers in the electronics, defence, communications and energy industries. It is also useful for graduate students taking courses in quality assurance.
Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
ISBN: 1119657113
Category : Einführung
Languages : en
Pages : 773
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Book Description
"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--
Author: Hoang Pham
Publisher: Springer Nature
ISBN: 1447175034
Category : Technology & Engineering
Languages : en
Pages : 1136
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Book Description
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
Author: Kaveh Sheibani
Publisher: ORLAB Analytics
ISBN:
Category : Business & Economics
Languages : en
Pages : 564
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Book Description
These proceedings gather contributions presented at the 2nd International Conference on Applied Operational Research (ICAOR 2010) in Turku, Finland, August 25-27, 2010, published in the series Lecture Notes in Management Science (LNMS). The conference covers all aspects of Operational Research and Management Science (OR/MS) with a particular emphasis on applications.
Author: Hans-Joachim Lenz
Publisher: Springer Science & Business Media
ISBN: 3790823805
Category : Mathematics
Languages : en
Pages : 367
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Book Description
The twenty-three papers in this volume are carefully selected, reviewed and revised for this volume, and are divided into two parts: Part 1: "On-line Control" with subchapters 1.1 "Control Charts" and 1.2 "Surveillance Sampling and Sampling Plans" and Part 2:"Off-line Control".
Author: Sio-Iong Ao
Publisher: Springer
ISBN: 981102717X
Category : Technology & Engineering
Languages : en
Pages : 578
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Book Description
This proceedings volume contains selected revised and extended research articles written by researchers who participated in the World Congress on Engineering and Computer Science 2015, held in San Francisco, USA, 21-23 October 2015. Topics covered include engineering mathematics, electrical engineering, circuits, communications systems, computer science, chemical engineering, systems engineering, manufacturing engineering, and industrial applications. The book offers the reader an overview of the state of the art in engineering technologies, computer science, systems engineering and applications, and will serve as an excellent reference work for researchers and graduate students working in these fields.
Author: Christine M. Anderson-Cook
Publisher: Quality Press
ISBN: 087389930X
Category : Business & Economics
Languages : en
Pages : 552
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Book Description
Quality Progress, the flagship journal of ASQ, has been publishing the column Statistics Roundtable since 1999. With over 130 contributions from leading authors in applied statistics, the column has been highly successful and widely read. This book collects 90 of the most interesting and useful articles on some key topics. The editors have constructed this book to be a resource for statisticians and practitioners alike with short, accessible, practical advice in important core areas of statistics from world-renowned experts. This book is intended to be an informative read, with bite-sized columns, as well as a starting point for deeper exploration of key statistical areas. The book contains nine chapters with collections of articles on the following topics: Statistical engineering Data quality and measurement Data collection Key statistical tools Quality control Reliability Multiple response and meta-analysis Applications Communication and training Chapter introductions provide a quick overview of the material contained in the columns of that chapter, as well as complementary articles for that topic that appear elsewhere in the book. Also included at the end of the each chapter introduction is a short list of key references that can provide additional details or examples for material in the topic area.
Author: Marianne Frisen
Publisher: John Wiley & Sons
ISBN: 9780470987162
Category : Mathematics
Languages : en
Pages : 272
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Book Description
This is the first book-length treatment of statistical surveillance methods used in financial analysis. It contains carefully selected chapters written by specialists from both fields and strikes a balance between the financial and statistical worlds, enhancing future collaborations between the two areas, and enabling more successful prediction of financial market trends. The book discusses, in detail, schemes for different control charts and different linear and nonlinear time series models and applies methods to real data from worldwide markets, as well as including simulation studies.
