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Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence
by
Zhu, Jianghong
, Li, Yanlai
, Wang, Rui
in
consensus-reaching process
/ Failure analysis
/ failure mode and effects analysis
/ Failure modes
/ Feasibility studies
/ Fuzzy logic
/ Fuzzy sets
/ geometric Bonferroni mean
/ multi-attribute border approximation area comparison
/ preference interdependence
/ Product development
/ Risk assessment
/ Risk management
2018
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Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence
by
Zhu, Jianghong
, Li, Yanlai
, Wang, Rui
in
consensus-reaching process
/ Failure analysis
/ failure mode and effects analysis
/ Failure modes
/ Feasibility studies
/ Fuzzy logic
/ Fuzzy sets
/ geometric Bonferroni mean
/ multi-attribute border approximation area comparison
/ preference interdependence
/ Product development
/ Risk assessment
/ Risk management
2018
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Do you wish to request the book?
Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence
by
Zhu, Jianghong
, Li, Yanlai
, Wang, Rui
in
consensus-reaching process
/ Failure analysis
/ failure mode and effects analysis
/ Failure modes
/ Feasibility studies
/ Fuzzy logic
/ Fuzzy sets
/ geometric Bonferroni mean
/ multi-attribute border approximation area comparison
/ preference interdependence
/ Product development
/ Risk assessment
/ Risk management
2018
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Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence
Journal Article
Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence
2018
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Overview
Failure mode and effects analysis is an effective and powerful risk evaluation technique in the field of risk management, and it has been extensively used in various industries for identifying and decreasing known and potential failure modes in systems, processes, products, and services. Traditionally, a risk priority number is applied to capture the ranking order of failure modes in failure mode and effects analysis. However, this method has several drawbacks and deficiencies, which need to be improved for enhancing its application capability. For instance, this method ignores the consensus-reaching process and the correlations among the experts’ preferences. Therefore, the aim of this study was to present a new risk priority method to determine the risk priority of failure modes under an interval-valued Pythagorean fuzzy environment, which combines the extended Geometric Bonferroni mean operator, a consensus-reaching process, and an improved Multi-Attributive Border Approximation area Comparison approach. Finally, a case study concerning product development is described to demonstrate the feasibility and effectiveness of the proposed method. The results show that the risk priority of failure modes obtained by the proposed method is more reasonable in practical application compared with other failure mode and effects analysis methods.
Publisher
MDPI AG
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