A novel quality risk evaluation framework for complex equipment development integrating PHFS-QFD and grey clustering
Grey Systems: Theory and Application
ISSN: 2043-9377
Article publication date: 28 November 2023
Issue publication date: 15 January 2024
Abstract
Purpose
The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.
Design/methodology/approach
A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.
Findings
The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.
Originality/value
This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.
Keywords
Acknowledgements
The authors would like to thank the associate editor and the anonymous reviewers for their insightful and constructive comments that improve this study. This work was supported by the National Natural Science Foundation of China (Nos. 72201133, 72101109, 72074200).
Citation
Wang, H., Wang, D., Wang, P. and Fang, Z. (2024), "A novel quality risk evaluation framework for complex equipment development integrating PHFS-QFD and grey clustering", Grey Systems: Theory and Application, Vol. 14 No. 1, pp. 144-159. https://doi.org/10.1108/GS-07-2023-0065
Publisher
:Emerald Publishing Limited
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