Knoth / Schmid Frontiers in Statistical Quality Control 11

2015
ISBN: 978-3-319-12355-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 393 Seiten, eBook

Reihe: Frontiers in Statistical Quality Control

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.

Zielgruppe

Research

Autoren/Hrsg.

Knoth, Sven

Schmid, Wolfgang

Inhaltsverzeichnis

Part I
- Statistical Process Control: Social Network Monitoring: Aiming to Identify Periods of Unusually Increased Communications Between Parties of Interest
byRoss Sparks
.- Some Recent Results on Monitoring the Rate of a Rare Event
by William H. Woodall and Anne G. Ryan
.- Statistical Perspectives on “Big Data”
by Fadel M. Megahed and L. Allison Jones-Farmer
.- Statistical Control of Multiple-stream Processes – a Literature Review
by Eugenio K. Epprecht.-
Regenerative Likelihood Ratio Control Schemes
by Emmanuel Yashchin
.- Variance Charts for Time Series – A Comparison Study
by Taras Lazariv and Wolfgang Schmid
.- On ARL-unbiased control charts
by Sven Knoth and Manuel Cabral Morais
.- Optimal Cumulative Sum Charting Procedures Based on Kernel Densities
by Jessie Y. Su, Fah Fatt Gan, and Xu Tang
.- A Simple Approach for Monitoring Process Mean and Variance
Simultaneously by Su-Fen Yang and Barry C. Arnold
.- Comparison of Phase II Control Charts Based on Variable Selection Methods
by Giovanna Capizzi and Guido Masarotto
.- The Use of Inequalities of Camp-Meidell Type in Nonparametric Statistical Process
Monitoring by Rainer Göb and Kristina Lurz
.- Strategies to Reduce the Probability of a Misleading Signal
by Manuel Cabral Morais, Patrícia Ferreira Ramos and António Pacheco
.- Characteristics of Economically Designed CUSUM and Control Charts
by Erwin Saniga, Darwin Davis, Alireza Faraz, Thomas McWilliams, JamesLucas
.- SPC of Processes with Predicted Data - Application of the Data Mining Methodology
by Olgierd Hryniewicz
.- Shewhart’s Idea of Predictability and Modern Statistics
by Alessandro Di Bucchianico and Edwin R. van den Heuvel
.-
Part II
- Acceptance Sampling: Sampling Inspection by Variables with an Additional Acceptance Criterion
byPeter-Th. Wilrich
.- Fractional Acceptance Numbers for Lot Quality
by K. Govindaraju and G. Jones
.- Sampling Plans for Control-Inspection Schemes Under Independent and Dependent Sampling Designs With Applications to Photovoltaics
by Ansgar Steland
.-
Part III
- Design of Experiments: An Overview of Designing Experiments for Reliability Data
by G. Geoffrey Vining, Laura J. Freeman, and Jennifer L.K. Kensler
.- Bayesian D-Optimal Design Issues for Binomial Generalized Linear Model Screening Designs
by Edgar Hassler, Douglas C. Montgomery, and Rachel T. Silvestrini
.- Bayesian Lasso with Effect Heredity Principle
by Hidehisa Noguchi, Yoshikazu Ojima, Seiichi Yasui
.-
Part IV
- Related Areas: Comparative Study of Time Scales in Optimal Time Scale Analysis of Field Reliability Data
by Watalu Yamamoto and Kazuki Takeshita
.- Why the Naive Bayesian Classifier for Clinical Diagnostics or Monitoring can Dominate the Proper one Even for Massive Data
by Hans - J. Lenz
.