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

Autorentext
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.

Zusammenfassung

Inhalt
An Intuitive Introduction to Quality Control with R.- An Introduction to R for Quality Control.- The Seven Quality Control Tools in a Nutshell: R and ISO Approaches.- R and ISO Standards for Quality Control.- Modeling Quality with R.- Data Sampling for Quality Control with R.- Acceptance Sampling with R.- Quality Specifications and Process Capability Analysis with R.- Control Charts with R.- Nonlinear Profiles with R.