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- W2401805611 abstract "This research proposes an approach for optimizing fuzzy multiple responses using desirability function and fuzzy regression. Each response repetition is transformed into signal to noise ratio then modeled using statistical multiple regression. A trapezoidal fuzzy regression model is formulated for each response utilizing the statistical regression coefficients. The most desirable response values and the deviation function are determined for each response. Finally, four optimization models are formulated for the trapezoidal membership fuzzy numbers to obtain optimal factor level at each number. A a case study is employed for illustration. In conclusion, the proposed approach successfully dealt with inherent variability and fuzziness in multiple responses. This shall be valuable to process and product engineers for optimizing fuzzy multiple responses in manufacturing applications on the Taguchi method." @default.
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- W2401805611 date "2013-01-01" @default.
- W2401805611 modified "2023-09-26" @default.
- W2401805611 title "Optimization of Multiple Responses in the Taguchi Method Using Desirability Function and Fuzzy Regression" @default.
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