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The relation between the desirability function (d i ) and the factor fraction (X i ) is divided sectionally as the desirability scale, see Fig. 1.
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Furthermore, in order to find the best compromise between several responses, the desirability function was optimized the responses successfully.
The scale of desirability emphasises a relationship between the affecting factor via factor fraction (X i ) and the desirability function by the intervals of the desirable degree.
Additionally, the desirability function approach was applied to acquire the preeminent compromise between the multiple responses.
A composite desirability value is obtained for the multi-responses using individual desirability values from the desirability function analysis.
The desirability function approach has been employed in order to find the best compromise between the different experimental responses.
Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach.
The desirability function technique is utilized to optimize the responses.
It was clearly noticed that the multi-responses of the desirability function improved the machine process.
The optimal separation conditions were estimated using the desirability function.
The desirability function was used to select optimum separation conditions.
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