A perspective of a dual response surface model with a desirability function
The use of response surface analysis is an effective method to improve the quality of products and processes. Along the same line, a dual response surface-based robust parameter design model may reduce product or process variability by selecting levels of input variables. In many products and processes, the researchers and practitioners may need to deal with a desirable response. Therefore, this paper proposes a new dual response surface model-based robust parameter design model with a desirability function to obtain a set of optimal operating conditions for multiple responses while minimizing the product or process variation as possible as. The proposed methodology is efficient and it improves the quality of the products by decreasing the variability in the process. The comparative studies show that proposed method is effective and outperforms the existing procedures. © 2018 Institute of Industrial Engineers (IIE). All rights reserved.
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