Statistical Process Monitoring and Optimization

Statistical Process Monitoring and Optimization
Author: Geoffrey Vining
Publisher: CRC Press
Total Pages: 504
Release: 1999-11-24
Genre: Business & Economics
ISBN: 1482276763

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

Statistical Process Monitoring and Optimization

Statistical Process Monitoring and Optimization
Author: Geoffrey Vining
Publisher: CRC Press
Total Pages: 520
Release: 1999-11-24
Genre: Technology & Engineering
ISBN: 9780824760076

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 of statistical methods and emphasizes practical applications of quality control systems in manufacturing, organization and planning.

Bayesian Process Monitoring, Control and Optimization

Bayesian Process Monitoring, Control and Optimization
Author: Bianca M. Colosimo
Publisher: CRC Press
Total Pages: 350
Release: 2006-11-10
Genre: Business & Economics
ISBN: 1420010700

Although there are many Bayesian statistical books that focus on biostatistics and economics, there are few that address the problems faced by engineers. Bayesian Process Monitoring, Control and Optimization resolves this need, showing you how to oversee, adjust, and optimize industrial processes. Bridging the gap between application and dev

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches
Author: Fouzi Harrou
Publisher: Elsevier
Total Pages: 330
Release: 2020-07-03
Genre: Technology & Engineering
ISBN: 0128193662

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

Introduction to Statistical Quality Control

Introduction to Statistical Quality Control
Author: Christina M. Mastrangelo
Publisher: Wiley
Total Pages: 244
Release: 1991
Genre: Business & Economics
ISBN:

Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.

Student Solutions Manual to accompany Introduction to Statistical Quality Control

Student Solutions Manual to accompany Introduction to Statistical Quality Control
Author: Douglas C. Montgomery
Publisher: Wiley
Total Pages: 0
Release: 2008-12-31
Genre: Technology & Engineering
ISBN: 9780470449486

This Student Solutions Manual is meant to accompany the trusted guide to the statistical methods for quality control, Introduction to Statistical Quality Control, Sixth Edition. Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control, Sixth Edition gives you a sound understanding of the principles of statistical quality control (SQC) and how to apply them in a variety of situations for quality control and improvement. With this text, you'll learn how to apply state-of-the-art techniques for statistical process monitoring and control, design experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques.

Multivariate Statistical Process Control with Industrial Applications

Multivariate Statistical Process Control with Industrial Applications
Author: Robert L. Mason
Publisher: SIAM
Total Pages: 271
Release: 2002-01-01
Genre: Technology & Engineering
ISBN: 0898714966

Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

Optimization in Quality Control

Optimization in Quality Control
Author: Khalaf S. Sultan
Publisher: Springer Science & Business Media
Total Pages: 397
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1461561515

Optimization in Quality Control presents a broad survey of the state of the art in optimization in quality, and focuses on industrial and national competitiveness. Each chapter has been carefully developed and refereed anonymously by experts in the area of optimization in quality control. Some of the topics covered in this volume include: fundamentals of optimization techniques contemporary approaches to optimization models in process control economic design of control charts determining optimal target values in multiple criteria economic selection models examining quality improvement schemes by trading off between expected warranty servicing costs and increasing manufacturing costs designing optimal inspection plans. This book will serve as an important reference source for academics, professionals and researchers.

Distribution-Free Methods for Statistical Process Monitoring and Control

Distribution-Free Methods for Statistical Process Monitoring and Control
Author: Markos V. Koutras
Publisher: Springer Nature
Total Pages: 261
Release: 2020-03-19
Genre: Technology & Engineering
ISBN: 3030250814

This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.

Statistical Control

Statistical Control
Author: George E. P. Box
Publisher: Wiley-Interscience
Total Pages: 358
Release: 1997-09-22
Genre: Mathematics
ISBN:

A detailed, practical, accessible guide to efficient statistical control. Efficient control is a key element in the improvement and maintenance of quality and productivity. This book shows the advantages of bringing together the more commonly used methods of statistical quality control with appropriate techniques of feedback adjustment. It uses recent research and practical experience to provide feedback methods of immediate use in the workplace. Statistical Control by Monitoring and Feedback Adjustment introduces a new coordinated approach to quality control. The authors' clear and cogent presentation uses extensive graphical explanation supplemented by numerous examples and computational tables. A helpful selection of problems and solutions further facilitates understanding. Topics covered include: * A fresh look at process monitoring * Using feedback adjustment charts * Minimizing the size of adjustments * Feedback techniques that minimize costs of adjustment and sampling * Detection of special causes with Cuscore Statistics * Efficient monitoring of operating feedback systems * The roles of models, optimization, and robustness * A brief review of time series analysis. Statistical Control by Monitoring and Feedback Adjustment is important reading for quality control engineers and statisticians as well as graduate students in quality control, industrial engineering, and applied statistics.