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Frontiers in Statistical Quality Control 13
This contributed book focuses on major aspects of statistical quality control, shares insights into important new developments in the field, and adapts established statistical quality control methods for use in e.g. big data, network analysis and medical applications. The content is divided into two parts, the first of which mainly addresses statistical process control, also known as statistical process monitoring. In turn, the second part explores selected topics in statistical quality control, including measurement uncertainty analysis and data quality. The peer-reviewed contributions gathered here were originally presented at the 13th International Workshop on Intelligent Statistical Quality Control, ISQC 2019, held in Hong Kong on August 12-14, 2019. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of statistical quality control.
Frontiers in Statistical Quality Control 12
This book provides insights into important new developments in the area of statistical quality control and critically discusses methods used in on-line and off-line statistical quality control. The book is divided into three parts: Part I covers statistical process control, Part II deals with design of experiments, while Part III focuses on fields such as reliability theory and data quality. The 12th International Workshop on Intelligent Statistical Quality Control (Hamburg, Germany, August 16 – 19, 2016) was jointly organized by Professors Sven Knoth and Wolfgang Schmid. The contributions presented in this volume were carefully selected and reviewed by the conference’s scientific program committee. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of quality control.
Applied Quantitative Finance
This book presents solutions for many practical problems in quantitative finance. The e-book design of the text connects theory and computational tools in an innovative way. All "quantlets" for calculation of examples in the text are executable on an XploRe Quantlet Server (XQS) and can be modified by the reader via the internet. The electronic edition can be downloaded from the web.
Frontiers in Statistical Quality Control 11
The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments. The majority of the papers deal with statistical process control, while acceptance sampling and design of experiments are also treated to a lesser extent. The book is organized into four thematic parts, with Part I addressing statistical process control. Part II is devoted to acceptance sampling. Part III covers the design of experiments, while Part IV discusses related fields. The twenty-three papers in this volume stem from The 11th International Workshop on Intelligent Statistical Quality Control, which was held in Sydney, Australia from August 20 to August 23, 2013. The event was hosted by Professor Ross Sparks, CSIRO Mathematics, Informatics and Statistics, North Ryde, Australia and was jointly organized by Professors S. Knoth, W. Schmid and Ross Sparks. The papers presented here were carefully selected and reviewed by the scientific program committee, before being revised and adapted for this volume.
Advances in Stochastic Models for Reliablity, Quality and Safety
Fast technological development produces systems of ever-increasing complex ity. The demand for reliable functioning of these systems has become more and more important. Thus, there is a need for highly reliable technical devices and systems, for monitoring and controlling their functioning and for planning maintenance and corrective actions to fulfill given requirements considering eco nomic limitations. These tasks reflect the wide field of engineering activities that are accompa nied by and based on a wide range of stochastical models. The book presents the main contributions to a workshop on Stochastic Models of Reliability, Qual ity, and Safety held in Schierke near Magdeburg, Germany. This workshop was part of a series of meetings that take place every two years organized by the Society of Reliability, Quality and Safety. The basic idea of these workshops is to bring together theorists, applied statisticians, and practitioners to exchange experiences and ideas of common interest. The book contains recent results in reliability and related fields. The presentation aims at making at least a part of the results accessible to engineers.
An Introduction to Discrete-Valued Time Series
A much-needed introduction to the field of discrete-valued time series, with a focus on count-data time series Time series analysis is an essential tool in a wide array of fields, including business, economics, computer science, epidemiology, finance, manufacturing and meteorology, to name just a few. Despite growing interest in discrete-valued time series—especially those arising from counting specific objects or events at specified times—most books on time series give short shrift to that increasingly important subject area. This book seeks to rectify that state of affairs by providing a much needed introduction to discrete-valued time series, with particular focus on count-data time s...
Advances in Stochastic Models for Reliablity, Quality and Safety
In 24 papers from a 1997 workshop near Magdeburg, Germany, theoreticians, applied statisticians, and practitioners discuss their current work and compare and evaluate models and methods. Within sections on lifetime analysis, reliability analysis, network analysis, and process control, they consider such topics as acceptance regions and their application in lifetime estimation, stochastic models for the return of used devices, a unified approach to the reliability of recurrent structures, and controlling a process with three different states. Annotation copyrighted by Book News, Inc., Portland, OR
Frontiers in Statistical Quality Control 7
This volume treats the four main categories of Statistical Quality Control: General SQC Methodology, On-line Control including Sampling Inspection and Statistical Process Control, Off-line Control with Data Analysis and Experimental Design, and, fields related to Reliability. Experts with international reputation present their newest contributions.
Frontiers in Statistical Quality Control 6
In the 1920's, Walter Shewhart visualized that the marriage of statistical methods and manufacturing processes would produce reliable and consistent quality products. Shewhart (1931) conceived the idea of statistical process control (SPC) and developed the well-known and appropriately named Shewhart control chart. However, from the 1930s to the 1990s, literature on SPC schemes have been "captured" by the Shewhart paradigm of normality, independence and homogeneous variance. When in fact, the problems facing today's industries are more inconsistent than those faced by Shewhart in the 1930s. As a result of the advances in machine and sensor technology, process data can often be collected on-li...
