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A neural network-based control scheme for monitoring start-up processes and short runs

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Abstract

Traditional control charts are commonly used as a monitoring tool in long-run processes. However, such control charts, due to the need for phase I analysis, are not suitable for start-up processes or short runs. Q control charts have been developed to help monitor start-up processes and short runs. In this article, a back propagation network is proposed for detecting a mean shift in start-up processes and short runs. In-control run length distribution of the control scheme is estimated using simulation study to provide information about the possibility of a false alarm within a specified number of observations. Performance of the proposed control scheme is assessed using different performance measures. It is shown numerically that the proposed control scheme outperforms the CUSUM of Q charts in detecting small to moderate mean shifts.

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Authors and Affiliations

  1. Industrial Engineering Department, Mazandaran University of Science and Technology, Babol, Iran

    M. Garjani

  2. Industrial Engineering Department, Iran University of Science and Technology, Tehran, 16846-13114, Iran

    R. Noorossana

  3. Industrial Engineering Department, Islamic Azad University, Research and Science Branch, Tehran, Iran

    A. Saghaei

Authors
  1. M. Garjani
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  2. R. Noorossana
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  3. A. Saghaei
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Correspondence to M. Garjani.

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Garjani, M., Noorossana, R. & Saghaei, A. A neural network-based control scheme for monitoring start-up processes and short runs. Int J Adv Manuf Technol 51, 1023–1032 (2010). https://doi.org/10.1007/s00170-010-2672-9

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  • DOI: https://doi.org/10.1007/s00170-010-2672-9

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