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.

About the Author

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 60 research papers and he is an Associate Editor of the journals Computational Statistics and Quality Engineering.

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 2012-2020 he was the President of the German Statistical Society.

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