The Experts below are selected from a list of 14346 Experts worldwide ranked by ideXlab platform
Felix T S Chan - One of the best experts on this subject based on the ideXlab platform.
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AMWRPN: Ambiguity Measure Weighted Risk Priority Number Model for Failure Mode and Effects Analysis
IEEE Access, 2018Co-Authors: Yongchuan Tang, Deyun Zhou, Felix T S ChanAbstract:The relative importance of each Risk factor in failure mode and effects analysis (FMEA) should be addressed properly. Intuitively, in the assessments coming from the FEMA experts, there exists a potential judgement on which Risk factor has a higher weight for the FMEA item. Based on this cognition and perspective, a new ambiguity measure weighted Risk Priority Number (AMWRPN) for FMEA is proposed. AMWRPN takes into consideration of the relative weight of different Risk factors by measuring the ambiguity degree of the experts' assessments. If the assessment of an expert has a certain belief on the judgement, then the relative importance of the corresponding Risk factor will be higher than the uncertain one; and vice versa. The ambiguity measure (AM) in the framework of the Dempster-Shafer evidence theory (DST) has been used to construct the exponential weight of each Risk factor in AMWRPN. In comparison with the weight factor basing on fuzzy sets theory or other theories in the DST framework, the AM-based weight factor for uncertainty measure of the subjective assessment ensures the internal coordination of the proposed method. An application of the proposed method in aircraft turbine rotor blade verifies the effectiveness of the new Risk Priority Number model.
Yongchuan Tang - One of the best experts on this subject based on the ideXlab platform.
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Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis
Entropy, 2020Co-Authors: Haixia Zheng, Yongchuan TangAbstract:Failure mode and effects analysis (FMEA), as a commonly used Risk management method, has been extensively applied to the engineering domain. A vital parameter in FMEA is the Risk Priority Number (RPN), which is the product of occurrence (O), severity (S), and detection (D) of a failure mode. To deal with the uncertainty in the assessments given by domain experts, a novel Deng entropy weighted Risk Priority Number (DEWRPN) for FMEA is proposed in the framework of Dempster–Shafer evidence theory (DST). DEWRPN takes into consideration the relative importance in both Risk factors and FMEA experts. The uncertain degree of objective assessments coming from experts are measured by the Deng entropy. An expert’s weight is comprised of the three Risk factors’ weights obtained independently from expert’s assessments. In DEWRPN, the strategy of assigning weight for each expert is flexible and compatible to the real decision-making situation. The entropy-based relative weight symbolizes the relative importance. In detail, the higher the uncertain degree of a Risk factor from an expert is, the lower the weight of the corresponding Risk factor will be and vice versa. We utilize Deng entropy to construct the exponential weight of each Risk factor as well as an expert’s relative importance on an FMEA item in a state-of-the-art way. A case study is adopted to verify the practicability and effectiveness of the proposed model.
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AMWRPN: Ambiguity Measure Weighted Risk Priority Number Model for Failure Mode and Effects Analysis
IEEE Access, 2018Co-Authors: Yongchuan Tang, Deyun Zhou, Felix T S ChanAbstract:The relative importance of each Risk factor in failure mode and effects analysis (FMEA) should be addressed properly. Intuitively, in the assessments coming from the FEMA experts, there exists a potential judgement on which Risk factor has a higher weight for the FMEA item. Based on this cognition and perspective, a new ambiguity measure weighted Risk Priority Number (AMWRPN) for FMEA is proposed. AMWRPN takes into consideration of the relative weight of different Risk factors by measuring the ambiguity degree of the experts' assessments. If the assessment of an expert has a certain belief on the judgement, then the relative importance of the corresponding Risk factor will be higher than the uncertain one; and vice versa. The ambiguity measure (AM) in the framework of the Dempster-Shafer evidence theory (DST) has been used to construct the exponential weight of each Risk factor in AMWRPN. In comparison with the weight factor basing on fuzzy sets theory or other theories in the DST framework, the AM-based weight factor for uncertainty measure of the subjective assessment ensures the internal coordination of the proposed method. An application of the proposed method in aircraft turbine rotor blade verifies the effectiveness of the new Risk Priority Number model.
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Combination of rating conflict in failure mode and effects analysis based on generalized combination rule
Proceedings of the 2016 International Forum on Management Education and Information Technology Application, 2016Co-Authors: Xuelian Zhou, Feng Liu, Yongchuan TangAbstract:generalized combination rule (GCR), Risk Priority Number (RPN), conflict combination Abstract. Failure mode and effects analysis (FMEA) is a preventive tool to keep the bad product from going to the consumers. Experts in a FMEA group often have different evaluations to each failure mode, and this will lead to conflict ratings for each failure mode, then how to manage the conflict to get the Risk Priority Number (RPN) more reasonable is still an open issue. In this paper, the generalized combination rule (GCR) in generalized evidence theory (GET) is introduced to manage the conflicts from different experts in a FMEA group. And the conflicts are modeled as the empty set, which corresponds to the incomplete knowledge or experience among the experts in the FMEA group. In this way, this paper provides a new FMEA model to combine the rating conflict. A real case study to the rotor blades of an aircraft turbine shows the effectiveness and merits of the proposed approach.
Gabriele Patrizi - One of the best experts on this subject based on the ideXlab platform.
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Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation
IEEE Access, 2020Co-Authors: Marcantonio Catelani, Diego Galar, Lorenzo Ciani, Gabriele PatriziAbstract:A wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a Risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the Risk Priority Number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine.
Hong-zhong Huang - One of the best experts on this subject based on the ideXlab platform.
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Risk Analysis of Propulsion System based on Similarity Measure and Weighted Fuzzy Risk Priority Number in FMEA
International Journal of Turbo & Jet-engines, 2018Co-Authors: Hang Zhou, Yuan-jian Yang, Hong-zhong HuangAbstract:Abstract Due to the epistemic uncertainty, it is difficult for the experts to give precise parameter values in Risk Priority Number (RPN) evaluations. To overcome this drawback, a hybrid method is proposed by integrating the concepts of fuzzy set theory, weight analysis and similarity value measure of fuzzy Numbers. The analysis process is divided into two phases to identify the hazard source. The first phase uses fuzzy Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA), then the main potential failure modes can be determined. The importance analysis of basic events can be calculated using fuzzy set theory and weight analysis. In the second phase, the multiple failure modes and component correlations are modelled using the Fuzzy Risk Priority Number (FRPN) evaluation and the Similarity Measure Value Method (SMVM). The proposed method has been applied to the Risk analysis of a satellite propulsion system to show the effectiveness and applicability.
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Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations
International Journal of Turbo & Jet-engines, 2014Co-Authors: Luping Gan, Yuan-jian Yang, Shun-peng Zhu, Hong-zhong HuangAbstract:Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correla tions in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) Risk Priority Number (RPN) method. The epis temic uncertainty of Risk variables and parameters are characterized by fuzzy Number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy Risk Priority Number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure pro babilities of each MCS. Compared to the case where de pendency among multiple failure modes is not consid ered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quan titative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reas sess the Risk Priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and com pressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and Risk Priority assessment of struc tural system under failure correlations.
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multiple failure modes analysis and weighted Risk Priority Number evaluation in fmea
Engineering Failure Analysis, 2011Co-Authors: Ningcong Xiao, Hong-zhong Huang, Yanfeng Li, Liping He, Tongdan JinAbstract:Traditionally, failure mode and effects analysis (FMEA) only considers the impact of single failure on the system. For large and complex systems, since multiple failures of components exist, assessing multiple failure modes with all possible combinations is impractical. Pickard et al. [1] introduced a useful method to simultaneously analyze multiple failures for complex systems. However, they did not indicate which failures need to be considered and how to combine them appropriately. This paper extends Pickard’s work by proposing a minimum cut set based method for assessing the impact of multiple failure modes. In addition, traditional FMEA is made by addressing problems in an order from the biggest Risk Priority Number (RPN) to the smallest ones. However, one disadvantage of this approach is that it ignores the fact that three factors (Severity (S), Occurrence (O), Detection (D)) (S, O, D) have the different weights in system rather than equality. For examples, reasonable weights for factors S, O are higher than the weight of D for some non-repairable systems. In this paper, we extended the definition of RPN by multiplying it with a weight parameter, which characterize the importance of the failure causes within the system. Finally, the effectiveness of the method is demonstrated with numerical examples.
Marcantonio Catelani - One of the best experts on this subject based on the ideXlab platform.
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Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation
IEEE Access, 2020Co-Authors: Marcantonio Catelani, Diego Galar, Lorenzo Ciani, Gabriele PatriziAbstract:A wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a Risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the Risk Priority Number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine.
