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A parameters reduction method for monitoring multiple linear regression profiles

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Abstract

In certain applications of statistical process control, it is possible to model quality of a product or process using a multiple linear regression profile. Some methods exist in the literature which could be used for monitoring multiple linear regression profiles. However, the performance of most of these methods deteriorates as the number of regression parameters increases. In this paper, we specifically concentrate on phase II monitoring of multiple linear regression profiles and propose a new dimension reduction method to overcome the dimensionality problem of some of the existing methods. The robustness, effectiveness, and limitations of the proposed method are also discussed. Simulation results show that in term of average run length criterion, the proposed method outperforms the traditional methods and has comparable performance with another dimension reduction method in the literature.

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Authors and Affiliations

  1. Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran

    Amirhossein Amiri

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

    Majid Eyvazian & Rassoul Noorossana

  3. LPMC and Department of Statistics, School of Mathematical Sciences, Nankai University, Tianjin, China

    Changliang Zou

Authors
  1. Amirhossein Amiri
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  2. Majid Eyvazian
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  3. Changliang Zou
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  4. Rassoul Noorossana
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Corresponding author

Correspondence to Amirhossein Amiri.

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Amiri, A., Eyvazian, M., Zou, C. et al. A parameters reduction method for monitoring multiple linear regression profiles. Int J Adv Manuf Technol 58, 621–629 (2012). https://doi.org/10.1007/s00170-011-3406-3

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  • DOI: https://doi.org/10.1007/s00170-011-3406-3

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