Download or read book A Process Control Chart for the Detection of a Change in the Level Parameter of the First and Second Order Autoregressive Processes written by Douglas Harvey Timmer and published by . This book was released on 1994 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dissertation Abstracts International written by and published by . This book was released on 1995 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book American Doctoral Dissertations written by and published by . This book was released on 1994 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the Section on Quality and Productivity written by American Statistical Association. Section on Quality and Productivity and published by . This book was released on 1996 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Technical Report written by University of Wisconsin--Madison. Department of Statistics and published by . This book was released on 1972 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Change Detection in Autocorrelated Processes written by Jiangbin Yang and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of change detection is about quick detection of a change in a dynamic system or process at a low rate of false alarm by sequentially observing the system or process. It has important applications in quality control, signal processing and other areas. This thesis studies the problem in the context of autocorrelated processes. First, we systematically investigate the properties of process residuals (one-step ahead forecast errors) for change detection. We show that process residuals are statistically sufficient for the problem of change detection, and change detection can be done by using process residuals. We show that process residuals are mutually uncorrelated with zero means when there is no change to the process, that is, when the process is in-control. We develop a general procedure for specifically deriving the forms of process residuals. Using the procedure, we derive the forms of residuals of general autoregressive integrated moving average (ARIMA) processes and state space models, and obtain some specific properties of the residuals under several situations. Under the Gaussian assumption, for an ARIMA process or a steady-state state space model subject to a change in process mean level, the residuals are i.i.d. with zero means before the occurrence of change. After the occurrence of change, the residuals are still mutually independent with the same variance as before, but with time-varying and generally nonzero means. For an autocorrelated process subject to a change in process mean level, we find that the properties of residuals are independent of the feedback control applied to the process. We then concentrate on detection of a change in process mean level in an autocorrelated process by using the process residuals. Cumulative sum (CUSUM), exponentially weighted moving average (EWMA) and Shewhart control chart procedures are applied to the residuals. For computation of the average run lengths (ARLs) of the control chart procedures applied to the residuals whose means are time-varying after change, we derive an explicit formula for Shewhart, establish integral equations for CUSUM and EWMA, and develop efficient numerical procedures for solving the integral equations. Under the ARL criterion, we numerically study the performance of the control chart procedures applied to the residuals of autocorrelated processes under several situations. We study the likelihood ratio (LR) testing procedure applied to the process residuals. We extend the classical LR testing procedure by replacing its constant threshold value with a time-varying threshold sequence. We propose a combined CUSUM and Shewhart control chart procedure to approximate the extended LR testing procedure. We develop numerical procedures based on integral equations for computation of the ARLs of these change detection procedures, and numerically study their performance. We study the problem of optimal sequential testing on process mean levels. The problem is a special situation of change detection, an extension of the Wald's sequential probability ratio testing (SPRT) problem, and has wide application in signal processing and other areas. We formulate the problem as an optimal stopping problem, derive the optimal stopping rule, obtain some important properties of the optimal stopping boundaries, develop a numerical procedure for computation of the optimal stopping boundaries, and present a numerical example.
Download or read book Journal of Engineering for Industry written by and published by . This book was released on 1990 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Control of Shewhart Control Charts written by Rob Goedhart and published by . This book was released on 2018 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data availability has increased immensely in the past years, and so has the need for data analysis techniques. A key point of interest is often to use process data to detect changes in the underlying process. This applies to numerous environments, ranging from standard manufacturing processes to intelligence agencies using complex network data to detect possible terrorist cells, or even our own body. Even though many processes may appear constant at first glance, the corresponding process data will vary over time. Certain variations are inherent to the process under consideration, and pinpointing the exact cause of these differences is often very difficult, if not impossible. However, special events or disturbances can change the underlying process, bringing a different source of variation. If no corrective actions are taken, this may lead to undesirable and potentially harmful consequences, depending on the circumstances. The field of statistical process monitoring (SPM) provides tools to detect process changes by monitoring data streams. This dissertation revolves around the design of one of such tools, namely the Shewhart control chart. When constructing a control chart, process parameters have to be estimated. Because different practitioners obtain different samples, their estimates will differ as well. This leads to varying control chart performance across different practitioners. In this dissertation we derive new control chart limits that take this effect into account.
Download or read book Enhancements to Control Charts for Monitoring Process Dispersion and Location written by Saddam Akber Abbasi and published by . This book was released on 2012 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control charts are widely used to monitor stability and performance of processes with an aim of detecting abnormal variations in process parameters. Control charts typically work in two phases: the retrospective phase (Phase I) and the monitoring phase (Phase II). Phase I involves estimating the in-control state of a process by using a historical dataset, whereas, in Phase II the focus mainly lies in the quick detection of process parameters from their in-control values. Chapter 2 of this thesis investigates a wide range of Shewhart type dispersion control charts in Phase II for normal and a variety of non-normal parent distributions. These charts are based on the sample range, the sample standard deviation, the inter-quartile range, Downton's estimator, the average absolute deviation from median, the median absolute deviation, Sn and Qn estimates. The Phase I analysis of these charts together with the charts based on the pooled sample standard deviation and the distribution-free scale rank statistic is investigated in Chapter 3. The performance of a variety of Phase II EWMA dispersion charts is evaluated and compared in Chapter 4, using different run length characteristics (the average run length, the median run length and the standard deviation of the run length distribution). The overall effectiveness of these EWMA charts is examined using the extra quadratic loss and the relative ARL measures. Chapter 5 investigates the effect of two component measurement error (model) on the performance of the EWMA location chart, for the monitoring of analytical measurements. The two component model proposed by Rocke and Lorenzato (1995) combines both additive and multiplicative errors in analytical measurements in a single model. It is shown that the two component measurement error can seriously effect the detection ability of the EWMA location chart and this effect can be reduced by the use of multiple measurements at each sample point. A cost function approach is used to determine appropriate choices of the sample size and the number of multiple measurements per sample to maximize the detection ability of the EWMA chart in presence of two component measurement error. Chapter 6 proposes two run rule schemes for the CUSUM dispersion chart. The run length characteristics of the proposed schemes are evaluated using the Markov chain approach and compared with the simple dispersion CUSUM and the relevant EWMA dispersion charts for individual observations. Finally, Chapter 7 proposes a nonparametric progressive mean control chart for the quick detection of out-of-control signals in the process target or location. This thesis, in general, will help quality practitioners to choose efficient control charts for the monitoring of process dispersion and location.
Download or read book Introduction to Statistical Process Control written by Peihua Qiu and published by CRC Press. This book was released on 2013-10-14 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon
Download or read book EWMA Control Charts in Statistical Process Monitoring written by Inez Maria Zwetsloot and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In today's world, the amount of available data is steadily increasing, and it is often of interest to detect changes in the data. Statistical process monitoring (SPM) provides tools to monitor data streams and to signal changes in the data. One of these tools is the control chart. The topic of this dissertation is a special control chart: the exponentially weighted moving average (EWMA) chart. A control chart plots the data together with two control limits. A control chart signals a (possible) change when the plotted data exceeds the control limits. A control chart performs well if it signals changes in the data quickly, without triggering frequent false alarms. Before a control chart can be set up, estimates of the process parameters are needed. To this end an initial data set is collected. In practice this data set often contains outliers, recording errors, and other data quality issues. These so-called 'contaminations' are problematic as they influence the parameter estimates. We investigate robust estimation methods to ensure accurate estimation of the process parameters. We propose a new estimation method based on screening and show that this new method outperforms existing estimation methods, when the type of contaminations is unknown. In the second phase of this dissertation we study the effect of estimation on the performance of the EWMA chart and give recommendations regarding its design. We show that traditionally designed charts have very variable performance. We study an alternative design procedure based conditional performance which provides control over the variability in performance."--Samenvatting auteur.
Download or read book Control Charts 55 Success Secrets 55 Most Asked Questions on Control Charts What You Need to Know written by Gregory Blanchard and published by Emereo Publishing. This book was released on 2014-10-25 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new control charts Guide that will give you all. 'Control charts', as well recognized like 'Shewhart charts' (after Walter A. Shewhart) either 'process-behavior charts', in mathematical analytic procedure command are implements applied to decide if a production either trade procedure is in a state of mathematical analytic command. There has never been a control charts Guide like this. It contains 55 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about control charts. A quick look inside of some of the subjects covered: Richard Branson - Honours and awards, Statistical process control - History, Dorian Shainin - Lot Plot, Joseph Juran - Management theory, Joseph M. Juran Management theory, Quality circle - Empirical studies of quality circles, Quality Circles - Empirical studies of quality circles, Capital Cities (band) - History, Lean production - Overview, Control chart Types of charts, Outkast discography, Quality storyboard - Worker participation in managerial diagnosis, Change (Vanessa Amorosi album), CUSUM - Example, Control chart Criticisms, Production Part Approval Process - PPAP elements, Applied engineering (field), Social network change detection, Bangerz - Commercial performance, Vysochanskii-Petunin inequality - Properties, Control chart Performance of control charts, Process Window Index - Statistical process control, Statistical control - History, Control chart Calculation of standard deviation, Operations management - Modeling, Quality assurance - Wartime production, List of business theorists - S, Lean manufacturing - Overview, The Ultimate Collection (Electric Light Orchestra album) - Chart, Control chart Overview, and much more...
Download or read book Sequential Control of Non Stationary Processes by Nonparametric Kernel Control Charts written by Wolfgang Schmid and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies nonparametric control charts to sequentially monitor dependent stochastic processes in continuous time with arbitrary but smooth drift functions m(t) to detect fast changes of m(t). Such methods are of particular interest when monitoring financial time series in order to detect rapid changes of the process mean. We provide a generalized framework for nonparametric process control where a process is regarded as out-of-control if the derivative of the process mean is to large. For a rich class of control charts based on linear smoothers it is shown how to design appropriate control charts guaranteeing an in-control average run length greather than or equal to a prescribed value. Further, a fundamental property of control charts concerning the average run length in the presence of positive autocorrelation, first estabilished for the EWMA chart applied to a Gaussian process, is extended to the case that it is applied to linear kernel smoothers. In addition, we study control charts based on local linear estimators. The performance of the proposed charts is compared by simulation studies.
Download or read book Nonparametric Statistical Process Control written by Subhabrata Chakraborti and published by John Wiley & Sons. This book was released on 2019-04-29 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique approach to understanding the foundations of statistical quality control with a focus on the latest developments in nonparametric control charting methodologies Statistical Process Control (SPC) methods have a long and successful history and have revolutionized many facets of industrial production around the world. This book addresses recent developments in statistical process control bringing the modern use of computers and simulations along with theory within the reach of both the researchers and practitioners. The emphasis is on the burgeoning field of nonparametric SPC (NSPC) and the many new methodologies developed by researchers worldwide that are revolutionizing SPC. Over the last several years research in SPC, particularly on control charts, has seen phenomenal growth. Control charts are no longer confined to manufacturing and are now applied for process control and monitoring in a wide array of applications, from education, to environmental monitoring, to disease mapping, to crime prevention. This book addresses quality control methodology, especially control charts, from a statistician’s viewpoint, striking a careful balance between theory and practice. Although the focus is on the newer nonparametric control charts, the reader is first introduced to the main classes of the parametric control charts and the associated theory, so that the proper foundational background can be laid. Reviews basic SPC theory and terminology, the different types of control charts, control chart design, sample size, sampling frequency, control limits, and more Focuses on the distribution-free (nonparametric) charts for the cases in which the underlying process distribution is unknown Provides guidance on control chart selection, choosing control limits and other quality related matters, along with all relevant formulas and tables Uses computer simulations and graphics to illustrate concepts and explore the latest research in SPC Offering a uniquely balanced presentation of both theory and practice, Nonparametric Methods for Statistical Quality Control is a vital resource for students, interested practitioners, researchers, and anyone with an appropriate background in statistics interested in learning about the foundations of SPC and latest developments in NSPC.
Download or read book Multivariate Bayesian Process Control written by Zhijian Yin and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Control Charts for First Order Autoregressive Analysis with an Exogenous Variable written by Becky M. Vela and published by . This book was released on 2012 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Control Charts and Machine Learning for Anomaly Detection in Manufacturing written by Kim Phuc Tran and published by . This book was released on 2022 with total page 0 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.
