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MPCI: An R Package for Computing Multivariate Process Capability Indices

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  • Santos-Fernández, Edgar
  • Scagliarini, Michele

Abstract

Manufacturing processes are often based on more than one quality characteristic. When these variables are correlated the process capability analysis should be performed using multivariate statistical methodologies. Although there is a growing interest in methods for evaluating the capability of multivariate processes, little attention has been given to developing user friendly software for supporting multivariate capability analysis. In this work we introduce the package MPCI for R, which allows to compute multivariate process capability indices. MPCI aims to provide a useful tool for dealing with multivariate capability assessment problems. We illustrate the use of MPCI package through both simulated and real examples.

Suggested Citation

  • Santos-Fernández, Edgar & Scagliarini, Michele, 2012. "MPCI: An R Package for Computing Multivariate Process Capability Indices," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i07).
    • Handle: RePEc:jss:jstsof:v:047:i07
    DOI: http://hdl.handle.net/10.18637/jss.v047.i07
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    Cited by:

    1. Linhan Ouyang & Yizhong Ma & Jianxiong Chen & Zhigang Zeng & Yiliu Tu, 2016. "Robust optimisation of Nd: YLF laser beam micro-drilling process using Bayesian probabilistic approach," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6644-6659, November.

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