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Frontiers in Statistical Quality Control 12: Frontiers in Statistical Quality Control

Editat de Sven Knoth, Wolfgang Schmid
en Limba Engleză Hardback – 16 iun 2018
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.
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Specificații

ISBN-13: 9783319752945
ISBN-10: 3319752944
Pagini: 390
Ilustrații: XVII, 366 p. 85 illus., 26 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.72 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Frontiers in Statistical Quality Control

Locul publicării:Cham, Switzerland

Cuprins

Chapter 1. Phase I Distribution-Free Analysis with the R Package dfphase1.- Chapter 2. Assessment of Shewhart Control Chart Limits in Phase I Implementations under Various Shift and Contamination Scenarios.- Chapter 3. New results for two-sided CUSUM-Shewhart control charts.- Chapter 4. Optimal Design of the Shiryaev–Roberts Chart: Give Your Shiryaev–Roberts a Headstart.- Chapter 5. On ARL-unbiased charts to monitor the traffic intensity of a single server queue.- Chapter 6. Risk-Adjusted Exponentially Weighted Moving Average Charting Procedure Based on Multi-Responses.- Chapter 7. A Primer on SPC and Web Data.- Chapter 8. The Variable-Dimension Approach in Multivariate SPC.- Chapter 8. Distribution Free Bivariate Monitoring of Dispersion.- Chapter 9. Monitoring and diagnosis of causal relationships among variables.- Chapter 10. Statistical monitoring of multi-stage processes.- Chapter 11. Control Charts for Time-Dependent Categorical Processes.- Chapter 12. Monitoring ofshort series of dependent observations using a XWAM control chart.- Chapter 13. Challenges in Monitoring Non-Stationary Time Series.- Chapter 14. Design of Experiments: A Key to Successful Innovation.- Chapter 15. D-Optimal Three-Stage Unbalanced Nested Designs for the Determination of Measurement Precision.- Chapter 16. Sampling inspection by variables under Weibull distribution and Type I censoring.- Chapter 17. Approximate Log-linear Cumulative Exposure Time Scale Model by Joint Moment Generating Function of Covariates.- Chapter 18. A Critique of Bayesian Approaches within Quality Improvement.- Chapter 19. A Note on the Quality of Biomedical Statistics.

Notă biografică

Sven Knoth studied Mathematics at the Technical Universities of Chemnitz and Novosibirsk, Russia. At the TU Chemnitz he received his diploma in 1990 and his doctorate in 1995 with a thesis on “Quasi-stationarity of CUSUM Schemes for Erlang Distributions”. After serving as a postdoc at the Department of Biostatistics, Heinrich Heine University in Düsseldorf until the end of 1996, he switched to the European University Viadrina in Frankfurt (Oder), where he completed his postdoctoral studies in 2003. From 2004 to 2009 he worked as Senior Process Engineer and SPC Coordinator at the Advanced Mask Technology Center (AMTC) in Dresden. In April 2009 he became a Professor of Computational Statistics at the Helmut Schmidt University, the University of the Federal Armed Forces in Hamburg. Sven Knoth is the author of 40 research papers on statistics. His main research areas are SPC, implementing statistical algorithms in software, and applying statistics in the engineering world. He is currently associate editor of the journal Computational Statistics.
Wolfgang Schmid studied Mathematics at the University of Ulm, Germany. He received his diploma in 1982 and his doctorate in 1984 with a thesis on “Localisation of outliers in autoregressive processes”. In 1991 he completed his postdoctoral studies with a thesis on “Outlier Tests and Outlier Identification in Time Series”.  After research stays in Ulm, Trier and Stuttgart, he became a full professor of Statistics at the European University Viadrina in Frankfurt (Oder) in 1995. Wolfgang Schmid is the author of over 130 research papers on statistics. His main research areas include statistical process control, statistics in finance, and environmetrics. He is currently associate editor of Sequential Analysis and of AStA-Advances in Statistical Analysis and since 2012 President of the German Statistical Society.
 

Textul de pe ultima copertă

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.

Caracteristici

Describes new developments in the area of statistical quality control Presents a variety of applications of experimental design Discusses methods used in on-line and off-line statistical quality control Provides selected and reviewed contributions from the 12th International Workshop on Intelligent Statistical Quality Control