Skip to main content
  • Book
  • © 2019

Statistical Quality Technologies

Theory and Practice

  • Enriches understandings of the state-of-the-art statistical methodologies for quality control, acceptance sampling and reliability assessment
  • Provides the background mathematical and statistical models and methods using simple and comprehensible terms with illustrative examples
  • Features the latest development in statistical methods for quality technologies that aimed at bridging the theoretical methodology development with real world industrial applications

Part of the book series: ICSA Book Series in Statistics (ICSABSS)

Buy it now

Buying options

eBook USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (16 chapters)

  1. Front Matter

    Pages i-xix
  2. Statistical Process Control

    1. Front Matter

      Pages 1-1
    2. Enhanced Cumulative Sum Charts Based on Ranked Set Sampling

      • Mu’azu Ramat Abujiya, Muhammad Hisyam Lee
      Pages 79-108
    3. A Survey of Control Charts for Simple Linear Profile Processes with Autocorrelation

      • Jyun-You Chiang, Hon Keung Tony Ng, Tzong-Ru Tsai, Yuhlong Lio, Ding-Geng Chen
      Pages 109-126
  3. Acceptance Sampling Plans

    1. Front Matter

      Pages 151-151
    2. Economical Sampling Plans with Warranty

      • Jyun-You Chiang, Hon Keung Tony Ng, Tzong-Ru Tsai, Yuhlong Lio, Ding-Geng Chen
      Pages 211-230
  4. Reliability Testing and Designs

    1. Front Matter

      Pages 255-255
    2. Robust Design in the Case of Data Contamination and Model Departure

      • Linhan Ouyang, Chanseok Park, Jai-Hyun Byun, Mark Leeds
      Pages 347-373

About this book

This book explores different statistical quality technologies including recent advances and applications. Statistical process control, acceptance sample plans and reliability assessment are some of the essential statistical techniques in quality technologies to ensure high quality products and to reduce consumer and producer risks. Numerous statistical techniques and methodologies for quality control and improvement have been developed in recent years to help resolve current product quality issues in today’s fast changing environment. Featuring contributions from top experts in the field, this book covers three major topics: statistical process control, acceptance sampling plans, and reliability testing and designs. The topics covered in the book are timely and have a high potential impact and influence to academics, scholars, students and professionals in statistics, engineering, manufacturing and health.

Editors and Affiliations

  • Department of Mathematical Sciences, University of South Dakota, Vermillion, USA

    Yuhlong Lio

  • Department of Statistical Science, Southern Methodist University, Dallas, USA

    Hon Keung Tony Ng

  • Department of Statistics, Tamkang University, New Taipei, Taiwan

    Tzong-Ru Tsai

  • Department of Statistics, University of Pretoria, Pretoria, South Africa

    Ding-Geng Chen

About the editors

Yuhlong Lio is a professor in the Department of Mathematical Science at the University of South Dakota. His research interest is in theoretical and methodology developments in mathematics and includes reliability inferences, kernel-smooth estimation, and mathematical modeling. Dr. Lio has been invited as a referee to review papers for more than 30 international and peer-review journals including Applied Mathematics and Computation, Applied Mathematical Modeling, Journal of Quality Technology and  IEEE Transactions on Reliability, among others. Dr. Lio currently serves on the advisory board for Journal of Statistics and Mathematics and as associate editor for Journal of Statistical Computation and Simulation and Electronic Journal of Applied Statistical Analysis. Dr. Lio received his BS in mathematics from Nation Cheng Kung University, Taiwan, his MS in mathematics from National Central University, Taiwan, and his PhD. in Statistics from University of South Carolina, USA.



Hon Keung Tony Ng is a professor of statistical science with the Southern Methodist University, Dallas, TX, USA. He is an associate editor of Communications in Statistics, Computational Statistics, IEEE Transactions on Reliability, Journal of Statistical Computation and Simulation, Naval Research Logistics, Sequential Analysis and Statistics and Probability Letters. His research interests include reliability, censoring methodology, ordered data analysis, nonparametric methods, and statistical inference. He has published more than 100 research papers in refereed journals. He is the co-author of the book Precedence-Type Tests and Applications (2006, with Balakrishnan) and co-editor of Ordered Data Analysis, Modeling and Health Research Methods (Springer 2015, ed. with Choudhary, Nagaraja). Professor Ng is a fellow of the American Statistical Association,an elected senior member of IEEE and an elected member of the International Statistical Institute.



Tzong-Ru Tsai is the dean of the College of Business and Management and a professor in the Department of Statistics at Tamkang University in New Taipei City, Taiwan. His main research interests include quality control and reliability analysis. He has served as a consultant with extensive expertise in statistical quality control, reliability assessment on highly reliable products, and design of experiments for many companies in the past years. He is an associate editor of the Journal of Statistical Computation and Simulation. Dr. Tsai has been invited as a referee to review papers for more than 20 peer-review journals, including IEEE Transactions on Reliability, Quality Engineering, and Quality and Reliability Engineering International.  He has published more than 70 research papers in refereed journals.



Ding-Geng (Din) Chen is the Wallace H. Kuralt Distinguished Professor and Director of the Consortium for Statistical Development and Consultation (CSDC) in the School of Social Work, and is jointly appointed as a clinical professor in the Department of Biostatistics at the UNC Gillings School of Global Health. He is an elected fellow of American Statistical Association. As a professor in biostatistics, he is interested in developing biostatistical methodologies in clinical trials, meta-analysis, Bayesian statistics and their applications to public health. As a professor in social work, he is interested in developing Bayesian social and health intervention research, cusp catastrophe modelling, statistical causal inferences, propensity score and structural-equation models (SEM). He is PI/Co-PI for several NIH R01 research projects in biostatistical methodology development and public health applications.


Bibliographic Information

Buy it now

Buying options

eBook USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access