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Quality Control with R pp 3–28Cite as

An Intuitive Introduction to Quality Control with R

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

Abstract

This chapter introduces Quality Control by means of an intuitive example. Furthermore, that example is used to illustrate how to use the R statistical software and programming language for Quality Control. A description of R outlining its advantages is also included in this chapter, all in all paving the way to further investigation throughout the book.

Keywords

  • Intuitive Example
  • Assignable Cause
  • Control Charts
  • Upper Specification Limit (USL)
  • Shewhart

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    http://en.Wikipedia.org/wiki/Six_Sigma.

  2. 2.

    See more about free software at http://gnu.org/philosophy/free-sw.en.html.

  3. 3.

    Lean, or Lean Manufacturing, is a quality methodology based on the reduction of waste.

  4. 4.

    r4stats.com/articles/popularity.

  5. 5.

    http://cran.r-project.org.

  6. 6.

    http://blog.revolutionanalytics.com/local-r-groups.html.

  7. 7.

    http://www.revolutionanalytics.com.

  8. 8.

    http://www.rstudio.com.

  9. 9.

    http://www.openanalytics.eu.

  10. 10.

    http://www.tibco.com.

  11. 11.

    http://stackoverflow.com/tags/r.

  12. 12.

    http://www.r-project.org.

  13. 13.

    April 2015.

  14. 14.

    http://bioconductor.org.

  15. 15.

    http://omegahat.org.

  16. 16.

    http://github.org.

  17. 17.

    http://rdocumentation.org.

  18. 18.

    Check at http://www.java.com.

  19. 19.

    http://www.qualitycontrolwithr.com.

  20. 20.

    Visit http://www.miktex.com for a LaTeX distribution for Windows.

  21. 21.

    If there are missing or outdated packages, RStudio will ask for permission to install or update them. Just answer yes.

References

  1. Cano, E.L., Moguerza, J.M., Redchuk, A.: Six Sigma with R. Statistical Engineering for Process Improvement. Use R!, vol. 36. Springer, New York (2012). http://www.springer.com/statistics/book/978-1-4614-3651-5

  2. Chambers, J.M.: Software for Data Analysis. Programming with R. Statistics and Computing. Springer, Berlin (2008)

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  3. Free Software Foundation, Inc.: Free Software Foundation website. http://gnu.org (2014). Accessed 10 July 2014

  4. Hornik, K.: R FAQ. http://CRAN.R-project.org/doc/FAQ/R-FAQ.html (2014)

  5. Ihaka, R., Gentleman, R.: R: a language for data analysis and graphics. J. Comput. Graph. Stat. 5, 299–314 (1996)

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  6. ISO TC69/SC1–Terminology and Symbols: ISO 3534-1:2006 - Statistics – Vocabulary and symbols – Part 1: General statistical terms and terms used in probability. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40145 (2010)

  7. ISO TC69/SC1–Terminology and Symbols: ISO 3534-2:2006 - Statistics – Vocabulary and symbols – Part 2: Applied statistics. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40147 (2014)

  8. ISO TC69/SC4–Applications of statistical methods in process management: ISO 11462-1:2001 - Guidelines for implementation of statistical process control (SPC) – Part 1: Elements of SPC. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=33381 (2012)

  9. ISO TC69/SC4–Applications of statistical methods in process management: ISO 7870-2:2013 - Control charts – Part 2: Shewhart control charts. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40174 (2013)

  10. ISO TC69/SC4–Applications of statistical methods in process management: ISO 22514-1:2014 - Statistical methods in process management – Capability and performance – Part 1: General principles and concepts. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=64135 (2014)

  11. ISO TC69/SC4–Applications of statistical methods in process management: ISO 7870-1:2014 - Control charts – Part 1: General guidelines. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=62649 (2014)

  12. ISO TC69/SC6–Measurement methods and results: ISO 5725-1:1994 - Accuracy (trueness and precision) of measurement methods and results – Part 1: General principles and definitions. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=11833 (2012)

  13. ISO TC69/SC6–Measurement methods and results: ISO 10576-1:2003 - Statistical methods – Guidelines for the evaluation of conformity with specified requirements – Part 1: General principles. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=32373 (2014)

  14. Leisch, F.: Sweave: dynamic generation of statistical reports using literate data analysis. In: Härdle, W., Rönz, B. (eds.) Compstat 2002 — Proceedings in Computational Statistics, pp. 575–580. Physica, Heidelberg (2002). http://www.stat.uni-muenchen.de/~leisch/Sweave

  15. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2015). http://www.R-project.org/

  16. Shewhart, W.: Economic Control of Quality in Manufactured Products. Van Nostrom, New York (1931)

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Author information

Authors and Affiliations

  1. Department of Computer Science and Statistics, Rey Juan Carlos University, Madrid, Spain

    Emilio L. Cano & Javier M. Moguerza

  2. Statistics Area, DHEP, The University of Castilla-La Mancha, Ciudad Real, Spain

    Emilio L. Cano

  3. ENUSA Industrias Avanzadas, Madrid, Spain

    Mariano Prieto Corcoba

Authors
  1. Emilio L. Cano
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  2. Javier M. Moguerza
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  3. Mariano Prieto Corcoba
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Cano, E.L., Moguerza, J.M., Corcoba, M.P. (2015). An Intuitive Introduction to Quality Control with R. In: Quality Control with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-24046-6_1

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