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A mixed control chart to monitor the process

Author

Listed:
  • Muhammad Aslam
  • Muhammad Azam
  • Nasrullah Khan
  • Chi-Hyuck Jun

Abstract

In this paper, we propose a mixed control chart to monitor the process quality using attribute data combined with variable data. The proposed control chart proceeds like an np control chart based on the number of nonconforming parts but requires variable data only when the decision is indeterminate. The control coefficients are determined by considering the in-control and the out-of-control average run lengths for various specified parameters. The extensive tables are provided for the industrial use. The advantages of the proposed control chart are discussed over the traditional np control chart.

Suggested Citation

  • Muhammad Aslam & Muhammad Azam & Nasrullah Khan & Chi-Hyuck Jun, 2015. "A mixed control chart to monitor the process," International Journal of Production Research, Taylor & Francis Journals, vol. 53(15), pages 4684-4693, August.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:15:p:4684-4693
    DOI: 10.1080/00207543.2015.1031354
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    Cited by:

    1. Nasrullah Khan & Muhammad Aslam & Kyung-Jun Kim & Chi-Hyuck Jun, 2017. "A mixed control chart adapted to the truncated life test based on the Weibull distribution," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 43-55.
    2. Simões, Felipe Domingues & Costa, Antonio Fernando Branco & Machado, Marcela Aparecida Guerreiro, 2020. "The Trinomial ATTRIVAR control chart," International Journal of Production Economics, Elsevier, vol. 224(C).
    3. Jose Jorge Muñoz & Manuel J. Campuzano & Jaime Mosquera, 2022. "Optimized np Attribute Control Chart Using Triple Sampling," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
    4. Ho, Linda Lee & Aparisi, Francisco, 2016. "ATTRIVAR: Optimized control charts to monitor process mean with lower operational cost," International Journal of Production Economics, Elsevier, vol. 182(C), pages 472-483.

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