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

Matteo Mario Savino, Alessandro Brun and Chen Xiang

European Journal of Industrial Engineering, 2017, vol. 11, issue 1, 78-100

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]

Keywords: fuzzy inference engine; quality management systems; QMS; non-conformity; risk assessment; failure mode effects and criticality analysis; FMECA; ISO 9001; fuzzy logic; quality control; risk criticality index; quality standards. (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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