2021
DOI: 10.1016/j.tws.2021.108257
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Implementation of a novel Six Sigma multi-objective robustness optimization method based on the improved response surface model for bumper system design

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Cited by 12 publications
(7 citation statements)
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“…Results were analyzed using Spearman's rank correlation test [35]. Spearman's rank correlation test can be applied using the following equations: (13) In equations; d k : The difference between the two data set values; K : Number of data; Z : It is defined as a test statistic.…”
Section: The Moora Model's Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Results were analyzed using Spearman's rank correlation test [35]. Spearman's rank correlation test can be applied using the following equations: (13) In equations; d k : The difference between the two data set values; K : Number of data; Z : It is defined as a test statistic.…”
Section: The Moora Model's Resultsmentioning
confidence: 99%
“…They showed that the design with multiple load cases presents a general optimum. Wang et al [13] performed a Six Sigma sturdiness optimization process based on the developed model for thin-wall structures. Kim et al [14] investigated the elastic metal bumper's behavior under the hyper-speed impact.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Cross-validation was used to test the prediction accuracy of the second-order response surface model [33]. Figure 14a,b shows the simulated value of the 10 verification points versus the predicted values from the developed response surface model, where f is the predicted value of longitudinal resonant frequency and f act is the simulated value of the longitudinal resonant frequency.…”
Section: Approximate Model Validationmentioning
confidence: 99%
“…It can also be seen in the literature that the functional performance, structural integrity, and reliability of fuel booster pumps are often affected by various uncertainties including material variability and model uncertainty [ 15 , 16 , 17 , 18 , 19 , 20 ]. Therefore, in engineering practice, component failures (e.g., fatigue failure) that exist in the fuel booster pump arise randomly in nature due to the following reasons: the material properties of these components generally show a certain variability due to stochastically distributed defects; geometrical tolerances of these components are inevitable due to the manufacturing process or design margins [ 21 ]; expert cognition in reliability varies between different experts due to their different backgrounds and experience [ 22 ]; and operational data (e.g., time between failures (TBFs) and TTRs) and types of maintenance costs (corrective and preventive maintenance) are uncertain due to different maintenance strategies [ 23 ].…”
Section: Introductionmentioning
confidence: 99%