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A review on optimisation of part quality inspection planning in a multi-stage manufacturing system

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  • Mohammad Rezaei-Malek
  • Mehrdad Mohammadi
  • Jean-Yves Dantan
  • Ali Siadat
  • Reza Tavakkoli-Moghaddam

Abstract

In multi-stage manufacturing systems, optimisation of part quality inspection planning (PQIP) problem means to determine the optimal time, place and extent of inspection activities for assessing the significant quality characteristics of products while maximising the system efficiency. An inspection activity is capable of detecting the produced defects partially and accordingly prevents further processing of them in downstream and more importantly avoids them to reach customers. In this paper, the existing researches on the optimisation of the part quality inspection are surveyed from the viewpoint of the considered production system characteristics; the applied modelling approaches and solution methodologies. This review found that although numerous works have been already done on the PQIP, the development of multi-objective optimisation frameworks considering real production constraints under parameters uncertainty is necessary. Also, by the Industry 4.0 trend, the creation of integrated models aiming to plan the inspection, maintenance and production activities simultaneously, seems to be an important potential future research direction.

Suggested Citation

  • Mohammad Rezaei-Malek & Mehrdad Mohammadi & Jean-Yves Dantan & Ali Siadat & Reza Tavakkoli-Moghaddam, 2019. "A review on optimisation of part quality inspection planning in a multi-stage manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4880-4897, August.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4880-4897
    DOI: 10.1080/00207543.2018.1464231
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    Cited by:

    1. Jun-Qiang Wang & Yun-Lei Song & Peng-Hao Cui & Yang Li, 2023. "A data-driven method for performance analysis and improvement in production systems with quality inspection," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 455-469, February.
    2. Mohamed Ismail & Noha A. Mostafa & Ahmed El-assal, 2022. "Quality monitoring in multistage manufacturing systems by using machine learning techniques," Journal of Intelligent Manufacturing, Springer, vol. 33(8), pages 2471-2486, December.
    3. Hauck, Zsuzsanna & Rabta, Boualem & Reiner, Gerald, 2023. "Coordinating quality decisions in a two-stage supply chain under buyer dominance," International Journal of Production Economics, Elsevier, vol. 264(C).

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