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Quality Control with R

An ISO Standards Approach

  • Book
  • © 2015

Overview

  • Demonstrates the power and extensibility of R in sophisticated quality control applications
  • Develops the fundamental concepts of the R programming language in an accessible, self-contained way, with numerous examples illustrating the connections to best practices in quality control
  • Written for a general audience, with a special aim towards quality control practitioners without a previous background in the R programming language
  • Contains several helpful indices that serve as quick references for ISO standards as well as R packages and functions discussed in the book

Part of the book series: Use R! (USE R)

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Table of contents (10 chapters)

  1. Fundamentals

  2. Statistics for Quality Control

  3. Delimiting and Assessing Quality

  4. Control Charts

Keywords

About this book

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.

                                                   

























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Authors and Affiliations

  • Department of Statistics and Operations Campus de Fuenlabrada, Rey Juan Carlos University, Madrid, Spain

    Emilio L. Cano, Javier Martinez Moguerza

  • ENUSA Industrias Avanzadas, Madrid, Spain

    Mariano Prieto

About the authors

Emilio L. Cano is Adjunct Lecturer at the University of Castilla-La Mancha and Research Assistant Professor at Rey Juan Carlos University. He also collaborates with the Spanish Association for Quality as trainer for in-company courses. He has more than 14 years of experience in the private sector as statistician.

Javier M. Moguerza is Associate Professor in Statistics and Operations Research at University Rey Juan Carlos. He publishes mainly in the fields of Mathematical Programming and Machine Learning. Currently, he is leading national and international research ICT projects funded by public and private organizations. He belongs to the Global Young Academy, and has been a member since 2010.

Mariano Prieto Corcoba is Continuous Improvement Manager at ENUSA Industrias Avanzadas. He has 30 years of experience in the fields of nuclear engineering and quality. He collaborates with the Spanish Association for Quality as a trainer in Six Sigma Methodology. Currently he is President of the Subcommittee of Statistical Methods of AENOR, the Spanish Association for Standardization and Certification.                                          












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