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Analysis of variance (ANOVA) was applied to find the significant parameters.
Dimensional analysis was applied to find relationships between the dimensionless parameters in the numerical simulation.
Design of experiment approach was applied to find out the optimal experimental conditions.
Plackett Burman design was applied to find the optimal ingredients and conditions to improve yields.
In the experiments, a static loading was applied to find failure surface and deformations for each case.
Afterwards, a central composite design methodology combined with desirability function approach was applied to find out the optimal experimental conditions.
Fractional Factorial design was applied to find optimum condition of process parameters and found that optimum percent.
The Analysis of variance (ANOVA) was applied to find the importance of operative parameters and their effects.
Box Behnken design methodology combined with desirability function approach was applied to find out the optimal experimental conditions.
The desirability functions methodology (DFM) was applied to find out the maximum specific PHE removal rate (Rs).
FMEA (failure mode and effect analysis) was applied to find the effective stress factor on the reliability of the sensor.
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