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Applications in Statistical Computing pp 219–232Cite as

Economically Designed Bayesian np Control Charts Using Dual Sample Sizes for Long-Run Processes

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Abstract

The implementation of a control chart requires the determination of three design parameters: the sample size, the sampling interval, and the control limits under which the production process will be stopped for potential repair. For a static control chart, the design parameters are maintained at the same level from an inspection epoch to another. Several research papers showed that adopting dynamic control charts in which one or more of the design parameters are allowed to vary from an inspection epoch to another leads to substantial cost savings compared to the classical ones. In this paper, we develop the expected long-run costs of two Bayesian np schemes, namely, the basic Bayesian and the Bayes-n charts for processes operating over an infinite horizon length. Optimal solutions leading to least-cost plans are searched for different sets of process and cost parameters. Experimental results show that moving from classical np control charts to Bayesian ones results in significant economic savings.

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Author information

Authors and Affiliations

  1. Department of Quantitative Methods and Computer Sciences, Higher Institute of Management of Sousse (ISG), University of Sousse, Sousse, Tunisia

    Imen Kooli

  2. Dhofar University, Box 2509, Salalah, 211, Oman

    Mohamed Limam

Authors
  1. Imen Kooli
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  2. Mohamed Limam
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Corresponding author

Correspondence to Imen Kooli .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Dortmund University of Applied Sciences and Arts, Dortmund, Germany

    Nadja Bauer

  2. Faculty of Statistics, TU Dortmund University, Dortmund, Germany

    Katja Ickstadt

  3. Institute for Empirical Research and Statistics, FOM University of Applied Sciences, Essen, Germany

    Karsten Lübke

  4. School of Business Studies, HOST University of Applied Sciences Stralsund, Stralsund, Germany

    Gero Szepannek

  5. Department of Information Systems, University of Münster, Münster, Germany

    Heike Trautmann

  6. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maurizio Vichi

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Kooli, I., Limam, M. (2019). Economically Designed Bayesian np Control Charts Using Dual Sample Sizes for Long-Run Processes. In: Bauer, N., Ickstadt, K., Lübke, K., Szepannek, G., Trautmann, H., Vichi, M. (eds) Applications in Statistical Computing. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-030-25147-5_14

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