Frontiers in Statistical Quality Control 13

1. Front Matter

   Pages i-xvi

   PDF

2. Statistical Process Control

   1. Front Matter

      Pages 1-1

      PDF

   2. Use of Conditional False Alarm Metric in Statistical Process Monitoring

      • Anne R. Driscoll, William H. Woodall, Changliang Zou

      Pages 3-12

   3. Design Considerations and Trade-offs for Shewhart Control Charts

      • Rob Goedhart

      Pages 13-23

   4. On the Calculation of the ARL for Beta EWMA Control Charts

      • Sven Knoth

      Pages 25-44

   5. Flexible Monitoring Methods for High-yield Processes

      • Tahir Mahmood, Ridwan A. Sanusi, Min Xie

      Pages 45-63

   6. An Average Loss Control Chart Under a Skewed Process Distribution

      • Su-Fen Yang, Shan-Wen Lu

      Pages 65-76

   7. ARL-Unbiased CUSUM Schemes to Monitor Binomial Counts

      • Manuel Cabral Morais, Sven Knoth, Camila Jeppesen Cruz, Christian H. Weiß

      Pages 77-98

   8. Statistical Aspects of Target Setting for Attribute Data Monitoring

      • Emmanuel Yashchin, Aaron Civil, Jeff Komatsu, Paul Zulpa

      Pages 99-119

   9. MAV Control Charts for Monitoring Two-State Processes Using Indirectly Observed Binary Data

      • Olgierd Hryniewicz, Katarzyna Kaczmarek-Majer, Karol R. Opara

      Pages 121-142

   10. Monitoring Image Processes: Overview and Comparison Study

       • Yarema Okhrin, Wolfgang Schmid, Ivan Semeniuk

       Pages 143-163

   11. Parallelized Monitoring of Dependent Spatiotemporal Processes

       • Philipp Otto

       Pages 165-183

   12. Product’s Warranty Claim Monitoring Under Variable Intensity Rates

       • Wenpo Huang, Wei Jiang, Chengyou Shi

       Pages 185-196

   13. A Statistical (Process Monitoring) Perspective on Human Performance Modeling in the Age of Cyber-Physical Systems

       • Fadel M. Megahed, L. Allison Jones-Farmer, Miao Cai, Steven E. Rigdon, Manar Mohamed

       Pages 197-228

   14. Monitoring Performance of Surgeons Using a New Risk-Adjusted Exponentially Weighted Moving Average Control Chart

       • Fah F. Gan, Wei L. Koh, Janice J. Ang

       Pages 229-245

   15. Exploring the Usefulness of Functional Data Analysis for Health Surveillance

       • Zezhong Wang, Inez Maria Zwetsloot

       Pages 247-264

   16. Rapid Detection of Hot-Spot by Tensor Decomposition with Application to Weekly Gonorrhea Data

       • Yujie Zhao, Hao Yan, Sarah E. Holte, Roxanne P. Kerani, Yajun Mei

       Pages 265-286

   17. An Approach to Monitoring Time Between Events When Events Are Frequent

       • Ross Sparks, Aditya Joshi, Cecile Paris, Sarvnaz Karimi

       Pages 287-299

3. Selected Topics from Statistical Quality Control

   1. Front Matter

      Pages 301-301

      PDF

   2. Analysis of Measurement Precision Experiment with Ordinal Categorical Variables

      • Tomomichi Suzuki, Jun-ichi Takeshita, Mayu Ogawa, Xiao-Nan Lu, Yoshikazu Ojima

      Pages 303-315

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.

• statistical quality control
• quality control
• experimental design
• statistical process control
• big data
• process monitoring
• network analysis
• control charting
• data quality
• lifetime analysis
• 62-06, 62P30, 62L99, 62N05, 62K99
• quality control, reliability, safety and risk

• Department of Mathematics and Statistics, Helmut Schmidt University, Hamburg, Germany

  Sven Knoth

• Department of Statistics, European University Viadrina, Frankfurt (Oder), Germany

  Wolfgang Schmid

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.