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A fuzzy-based multi-stage quality control under the ISO 9001:2015 requirements

Author

Listed:
  • Matteo Mario Savino
  • Alessandro Brun
  • Chen Xiang

Abstract

This work focuses on the problem of non conformity (NC) characterisation in quality management systems (QMS) and introduces a fuzzy inference engine (FE) for NC analysis based on multi-stage quality control. The research has a twofold objective: 1) to characterise NCs based on risk analysis principles, 2) to define NC priorities. The FE is implemented according to the main requirements of the new ISO 9001:2015 Standard regarding risk analysis and NC assessment. The methodology was tested within an assembly line of mechanical components, where a number of NCs were detected and classified with respect to multiple features. Within this classification, risk analysis is explored through the use of failure mode effects and criticality analysis (FMECA). A risk criticality index (RCI) is defined and evaluated, which addresses NC criticality and the relative action priorities. [Received 28 January 2016; Revised 25 March 2016; Accepted 24 June 2016]

Suggested Citation

  • Matteo Mario Savino & Alessandro Brun & Chen Xiang, 2017. "A fuzzy-based multi-stage quality control under the ISO 9001:2015 requirements," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 11(1), pages 78-100.
    • Handle: RePEc:ids:eujine:v:11:y:2017:i:1:p:78-100
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    Cited by:

    1. Riya Sureka & Satish Kumar & Deepraj Mukherjee & Christina Theodoraki, 2023. "What restricts SMEs from adopting sophisticated capital budgeting practices?," Small Business Economics, Springer, vol. 60(1), pages 265-290, January.
    2. Fatima Bennouna & Driss Amegouz & Aicha Sekhari, 2021. "Investigating the Impact of QSE Integration on Process Performances: An Empirical Study in Moroccan Companies," Post-Print hal-04170942, HAL.

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