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Multivariate process capability analysis applied to AISI 52100 hardened steel turning

  • R. S. Peruchi
  • P. Rotela Junior
  • T. G. Brito
  • J. J. J. Largo
  • P. P. Balestrassi
ORIGINAL ARTICLE
  • 117 Downloads

Abstract

Hard turning operations have been extensively investigated owing to their ability to reduce process cycle time, increase process flexibility, ensure high-dimensional accuracy, and enable machining without a cutting fluid. These processes are rather common for dealing with multiple quality characteristics. To evaluate the process ability and meet customer needs, multivariate statistical techniques are recommended for estimating the capability indices. Principal component analysis can be applied to reducing the problem dimension and estimate process capability indices. The aim of this study was to assess the capability of AISI 52100 hardened steel turning operations and achieve process specifications. Multivariate process capability indices were calculated to assess five roughness parameters of surface finishing. By using a weighted approach of principal component analysis, a new method is proposed for estimating the process capability indices. The results highlight not only the relevance of conducting a multivariate capability analysis in the case of actual machining but also how successfully the proposed method was performed.

Keywords

Process capability index Hard turning Roughness Principal component analysis 

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Notes

Funding information

The authors would like to express their gratitude to the Brazilian agencies Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for supporting this research.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2017

Authors and Affiliations

  • R. S. Peruchi
    • 1
  • P. Rotela Junior
    • 1
  • T. G. Brito
    • 2
  • J. J. J. Largo
    • 2
  • P. P. Balestrassi
    • 2
  1. 1.Department of Industrial EngineeringFederal University of ParaíbaJoão PessoaBrazil
  2. 2.Institute of Industrial Engineering and ManagementFederal University of ItajubáItajubáBrazil

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