Optimal design of the double sampling X̄ chart with estimated parameters based on median run length

Wei Lin Teoh*, Michael Boon Chong Khoo, Philippe Castagliola, S. Chakraborti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

55 Citations (Scopus)


The double sampling (DS) X̄ chart when the process parameters are unknown and have to be estimated from a reference Phase-I dataset is studied. An expression for the run length distribution of the DS X̄ chart is derived, by conditioning and taking parameter estimation into account. Since the shape and the skewness of the run length distribution change with the magnitude of the mean shift, the number of Phase-I samples and sample sizes, it is shown that the traditional chart's performance measure, i.e. the average run length, is confusing and not a good representation of a typical chart's performance. To this end, because the run length distribution is highly right-skewed, especially when the shift is small, it is argued that the median run length (MRL) provides a more intuitive and credible interpretation. From this point of view, a new optimal design procedure for the DS X̄ chart with known and estimated parameters is developed to compute the chart's optimal parameters for minimizing the out-of-control MRL, given that the values of the in-control MRL and average sample size are fixed. The optimal chart which provides the quickest out-of-control detection speed for a specified shift of interest is designed according to the number of Phase-I samples commonly used in practice. Tables are provided for the optimal chart parameters along with some empirical guidelines for practitioners to construct the optimal DS X̄ charts with estimated parameters. The optimal charts with estimated parameters are illustrated with a real application from a manufacturing company.

Original languageEnglish
Pages (from-to)104-115
Number of pages12
JournalComputers and Industrial Engineering
Publication statusPublished - Jan 2014


  • Conditional run length
  • Double sampling (DS) X̄ chart
  • Optimal design
  • Parameter estimation
  • Statistical process control
  • Unconditional run length

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)


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