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Performance evaluation of production systems monitored by statistical process control and off-line inspections

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  • Colledani, Marcello
  • Tolio, Tullio

Abstract

Quality and productivity performance measures are very often considered in separate phases of the production system design process. However, the production system architecture affects the efficiency of the quality control system as well as the quality control configuration has an impact on the performance of the production system. The paper proposes a new analytical method for evaluating the performance of production systems in which statistical process control (SPC) techniques are implemented. Machines behaviour is monitored by measuring quality characteristics of the produced parts through off-line inspection devices and sampling inspections. The numerical results show the good accuracy of the proposed method, provide new insight in the relations among the two areas and pave the way to the joint design of production logistics and quality control systems.

Suggested Citation

  • Colledani, Marcello & Tolio, Tullio, 2009. "Performance evaluation of production systems monitored by statistical process control and off-line inspections," International Journal of Production Economics, Elsevier, vol. 120(2), pages 348-367, August.
  • Handle: RePEc:eee:proeco:v:120:y:2009:i:2:p:348-367
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    References listed on IDEAS

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    Cited by:

    1. Bouslah, B. & Gharbi, A. & Pellerin, R., 2016. "Joint economic design of production, continuous sampling inspection and preventive maintenance of a deteriorating production system," International Journal of Production Economics, Elsevier, vol. 173(C), pages 184-198.
    2. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean Pierre, 2013. "Joint production and major maintenance planning policy of a manufacturing system with deteriorating quality," International Journal of Production Economics, Elsevier, vol. 146(2), pages 575-587.
    3. Dusadeerungsikul, Puwadol Oak & Nof, Shimon Y., 2024. "Precision agriculture with AI-based responsive monitoring algorithm," International Journal of Production Economics, Elsevier, vol. 271(C).
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    5. Muhammad Babar Ramzan & Shehreyar Mohsin Qureshi & Sonia Irshad Mari & Muhammad Saad Memon & Mandeep Mittal & Muhammad Imran & Muhammad Waqas Iqbal, 2019. "Effect of Time-Varying Factors on Optimal Combination of Quality Inspectors for Offline Inspection Station," Mathematics, MDPI, vol. 7(1), pages 1-18, January.
    6. Scarf, Philip A. & Cavalcante, Cristiano A.V., 2012. "Modelling quality in replacement and inspection maintenance," International Journal of Production Economics, Elsevier, vol. 135(1), pages 372-381.
    7. Anna Rotondo & Paul Young & John Geraghty, 2013. "Quality risk prediction at a non-sampling station machine in a multi-product, multi-stage, parallel processing manufacturing system subjected to sequence disorder and multiple stream effects," Annals of Operations Research, Springer, vol. 209(1), pages 255-277, October.
    8. Puchkova, Alena & McFarlane, Duncan & Srinivasan, Rengarajan & Thorne, Alan, 2020. "Resilient planning strategies to support disruption-tolerant production operations," International Journal of Production Economics, Elsevier, vol. 226(C).
    9. Pinheiro de Lima, Edson & Gouvea da Costa, Sergio E. & Angelis, Jannis Jan & Munik, Juliano, 2013. "Performance measurement systems: A consensual analysis of their roles," International Journal of Production Economics, Elsevier, vol. 146(2), pages 524-542.

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