A Methodology for Quality Indicator Factors and Levels Using AHP and Fuzzy Theory in an Aviation System

Purpose: The purpose of this study is to identify quality indicator factors and their levels for the effective implementation of quality assurance procedures in the defense sector and to propose a systematic methodology for their evaluation. As a preliminary study, the research focuses on the development of quality indicators using an aviation system as a case study.Methods: This study was conducted with failure mode and effects analysis(FMEA) as its theoretical foundation. First, the factors were derived by applying the analytic hierarchy process(AHP) and fuzzy theory. Furthermore, the prioritization of the quality factor' levels was established through a proposed methodology combining weight sum model and weight product model approaches using expert weights, as well as the center of gravity and the center of area from fuzzy theory.Results: The 12 quality indicator factors were selected based on the FMEA. The AHP was applied to assess the relative influence among these 12 factors, and quantitative validity of expert judgments was ensured using expert weighting and fuzzy theory. Consistency of the AHP results was verified through the consistency index and consistency ratio. The priority of the quality indicator factors was determined in the order of defect type, manufacturing process step, and defect frequency.Conclusion: This study identifies quality indicator factors applicable to quality assurance activities through an aviation system case and proposes a methodology for deriving the priorities of levels among these factors. The methodology can be expressed in terms of results corresponding to the severity, occurrence, and detection of FMEA, and it is integrated within a hierarchical structure using AHP and fuzzy theory. In addition, by incorporating expert weights, the study compensates for the limitations associated with expert judgments.