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Monitoring Process Variability Using EWMA

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Springer Handbook of Engineering Statistics

Part of the book series: Springer Handbooks ((SHB))

Abstract

During the last decade, the use of the exponentially weighted moving average (EWMA) statistic as a process-monitoring tool has become more and more popular in the statistical process-control field. If the properties and design strategies of the EWMA control chart for the mean have been thoroughly investigated, the use of the EWMA as a tool for monitoring process variability has received little attention in the literature. The goal of this chapter is to present some recent innovative EWMA-type control charts for the monitoring of process variability (i.e. the sample variance, sample standard-deviation and the range). In the first section of this chapter, the definition of an EWMA sequence and its main properties will be presented together with the commonly used procedures for the numerical computation of the average run length (ARL). The second section will be dedicated to the use of the EWMA as a monitoring tool for the process position, i.e. sample mean and sample median. In the third section, the use of the EWMA for monitoring the sample variance, sample standard deviation and the range will be presented, assuming a fixed sampling interval (FSI) strategy. Finally, in the fourth section of this chapter, the variable sampling interval adaptive version of the EWMA-S 2 and EWMA-R control charts will be presented.

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Abbreviations

ARL:

average run length

CDF:

cumulative distribution function

CUSUM:

cumulative sum

EWMA:

exponentially weighted moving average

FSI:

fixed sampling interval

PDF:

probability density function

VSI:

variable sampling intervals

i.i.d.:

of independent and identically distributed

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Author information

Authors and Affiliations

  1. Qualité Logistique Industrielle et Organisation, Université de Nantes and IRCCyN UMR CNRS 6597 Institut Universitaire de Technologie de Nantes, 2 avenue du Professeur Jean Rouxel, BP 539-44475, Carquefou, France

    Philippe Castagliola

  2. Dipartimento di Ingegneria Industriale e Meccanica, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy

    Giovanni Celano

  3. Department Industrial and Mechanical Engineering, University of Catania, avenale Andrea Doria 6, 95125, Catania, Italy

    Sergio Fichera

Authors
  1. Philippe Castagliola
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  2. Giovanni Celano
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  3. Sergio Fichera
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Corresponding authors

Correspondence to Philippe Castagliola , Giovanni Celano or Sergio Fichera .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, Rutgers the State University of New Jersey, 96 Frelinghuysen Road, 08854, Piscataway, NJ, USA

    Hoang Pham Prof.

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© 2006 Springer-Verlag

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Castagliola, P., Celano, G., Fichera, S. (2006). Monitoring Process Variability Using EWMA. In: Pham, H. (eds) Springer Handbook of Engineering Statistics. Springer Handbooks. Springer, London. https://doi.org/10.1007/978-1-84628-288-1_17

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  • DOI: https://doi.org/10.1007/978-1-84628-288-1_17

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-806-0

  • Online ISBN: 978-1-84628-288-1

  • eBook Packages: EngineeringEngineering (R0)

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