Frontiers in Statistical Quality Control 14

This book examines major areas of statistical quality control, with a focus on sharing insights into important new developments in the field and adapting established statistical quality control methods for use in various fields of application, including business, finance, environmental science, engineering and health. It is divided into two parts, the first addressing statistical process monitoring and the second exploring selected topics in statistical quality control, including the design of experiments and data quality.

Compiling peer-reviewed contributions originally presented at the 14th International Workshop on Intelligent Statistical Quality Control, ISQC 2023, held in Washington, DC, USA, on August 15-17, 2023, the book bridges the gap between theory and practice, making it of interest to both researchers and practitioners in the field of statistical quality control.

Preface.- May 16, 1924 – 2024: Celebrating the Centenary of Shewhart’s Quality Control Chart.- Statistical Process Control Charting: A View of the Fundamental Definitions and Terminology.- Individual-Moving Range (IMR) Control Charts — Another Look Utilizing Accurate Numerical Algorithms.- A Comparison of the MEWMA and the Double MEWMA Control Charts Using the Criterion of First to Signal.- The Sequential Normal Scores Approximation as a Bridge Between Parametric and Nonparametric Statistical Process Monitoring.- Monitoring the Value at Risk with Applications to Finance.- Phase I of Spatiotemporal Profile Monitoring for Functional Data.- Monitoring Color Image Processes.- A Change-Point-Detection Chart for Detecting Process Mean Drifts with an Application for Monitoring the Shape of the Salton Sea.- Structural Health Monitoring with Functional Data: Two Case Studies.- Data, Statistics and Language: Exploring Similarities in Data Processing and Analysis for Decision Support on Unmanned Aerial Vehicle (UAV) and Care Unit Intensive (CUI) Cases.- Augmentation of No-Confounding 16-Run Fractional Factorial Designs.- Statistical Quality Control in Oshibori Rental Business.- Detecting manipulated Data Sets using Benford’s Law.

Sven Knoth is a Professor of Computational Statistics at the Helmut Schmidt University, the University of the Federal Armed Forces, Hamburg, Germany. His main research areas include statistical process control, implementation of statistical algorithms in software, and applications of statistics in engineering. He has authored more than 80 research papers and he is an Associate Editor of the journals Quality Engineering, Computational Statistics, Quality Reliability Engineering and Journal of Quality Technology.

Wolfgang Schmid is a Professor of Statistics at the European University Viadrina, Frankfurt (Oder), Germany. His main research areas include statistical process control, statistics in finance, spatial statistics, and environmetrics. He has authored more than 160 research papers and he is an Associate Editor of Sequential Analysis, AStA Advances in Statistical Analysis, and Journal of Multivariate Analysis. Between 2012 and 2020 he was the President of the German Statistical Society.