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A new multivariate gage R&R method for correlated characteristics

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  • Peruchi, Rogério Santana
  • Balestrassi, Pedro Paulo
  • de Paiva, Anderson Paulo
  • Ferreira, João Roberto
  • de Santana Carmelossi, Michele

Abstract

This article explores how measurement systems having correlated characteristics are analyzed through studies of gage repeatability and reproducibility (GR&R). The main contribution of this research is the proposal of a method for multivariate analysis of a measurement system, a method that considers the weighted principal components (WPC). To prove its efficiency, what was first evaluated were the measurements of the roughness parameters obtained from AISI 12L14 steel turning machined with carbide tools. This GR&R study considers 12 parts, 3'operators, 4'replicates, and 5'responses (Ra, Ry, Rz, Rq and Rt). The data set has a correlation structure that determines 86.2% of explanation for the first principal component. As another step in proving the method's efficiency, the study generates simulated data with different correlation structures for measurement systems classified as acceptable, marginal, and unacceptable. The proposed method is compared with classical univariate and multivariate methods. It was observed that, compared to the other methods, the WPC was more robust in estimating the assessment indexes of a multivariate measurement system.

Suggested Citation

  • Peruchi, Rogério Santana & Balestrassi, Pedro Paulo & de Paiva, Anderson Paulo & Ferreira, João Roberto & de Santana Carmelossi, Michele, 2013. "A new multivariate gage R&R method for correlated characteristics," International Journal of Production Economics, Elsevier, vol. 144(1), pages 301-315.
    • Handle: RePEc:eee:proeco:v:144:y:2013:i:1:p:301-315
    DOI: 10.1016/j.ijpe.2013.02.018
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    References listed on IDEAS

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    Cited by:

    1. de Oliveira, Lucas Guedes & Aquila, Giancarlo & Balestrassi, Pedro Paulo & de Paiva, Anderson Paulo & de Queiroz, Anderson Rodrigo & de Oliveira Pamplona, Edson & Camatta, Ulisses Pessin, 2020. "Evaluating economic feasibility and maximization of social welfare of photovoltaic projects developed for the Brazilian northeastern coast: An attribute agreement analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    2. Mohammed Abduljaleel & Habshah Midi & Mostafa Karimi, 2019. "Outlier Detection In The Analysis Of Nested Gage R&R, Random Effect Model," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 31-56, September.
    3. Abduljaleel Mohammed & Midi Habshah & Karimi Mostafa, 2019. "Outlier Detection In The Analysis Of Nested Gage R&R, Random Effect Model," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 31-56, September.

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