Adaptive EWMA control charts with time-varying smoothing parameter

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Abstract

Time-weighted charts like EWMA or CUSUM are designed to be optimal to detect a specific shift. This feature, however, can make the chart suboptimal for some other shifts.If, for instance, the charts are designed to detect a small shift, then, they can be inefficient to detect moderate or large shifts. In the literature, several alternatives have been proposed to circumvent this limitation, like the use of control charts with variable parameters or adaptive control charts. This paper aims to propose new adaptive EWMA control charts (AEWMA) based on the assessment of a potential misadjustment, which is translated into a time-varying smoothing parameter. The resulting control charts can be seen as a smooth combination between Shewhart and EWMA control charts, which could be efficient for a wide range of shifts. Markov chain procedures are established to analyse and design the proposed charts. Comparisons with other adaptive and traditional control charts show the advantages of our proposals.

Keywords

Adaptive control charts Average run length EWMA CUSUM Statistical process control Misadjustment 

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Notes

Acknowledgements

Authors gratefully acknowledge the financial support received from the Spanish MEC, under grant ECO2012-38442 and ECO2015-66593, and the Peruvian Programa Nacional de Innovación para la Competitividad y Productividad (Innóvate Perú) under the contract 377-PNICP-PIAP-2014.

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Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  • Willy Ugaz
    • 1
    • 4
  • Ismael Sánchez
    • 1
    • 2
    • 3
  • Andrés M. Alonso
    • 1
    • 3
  1. 1.Department of StatisticsUniversidad Carlos III de MadridLeganésSpain
  2. 2.Department of Industrial Engineering and SystemsUniversidad de PiuraPiuraPerú
  3. 3.Department of Statistics and Instituto Flores de LemusUniversidad Carlos III de MadridGetafeSpain
  4. 4.Department of Industrial Engineering and SystemsUniversidad de PiuraMirafloresPerú

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