Ozdemir, Akin2024-10-042024-10-0420210305-215X1029-0273https://doi.org/10.1080/0305215X.2020.1732365http://hdl.handle.net/20.500.12403/2966Optimal experimental designs are effective offline quality improvement techniques used to enhance existing products and develop new products for a constrained design region. For some practical situations, I-optimal experimental designs may be the most suitable way to construct optimal experimental design points, by addressing prediction variance to generate a measure of prediction performance over the non-standard experimental design region. The purpose of this article is three-fold: (1) the I-optimality criterion is selected for minimizing the average prediction variance; (2) fitted mean and variance response models are found; and (3) a nonlinear lexicographic goal programming model incorporating an I-optimal experimental design is proposed to find the optimum settings of controllable design factors. Comparison studies and a numerical example are provided to illustrate the effectiveness of the proposed methodology for improvement of the quality of products.eninfo:eu-repo/semantics/closedAccessQuality improvementI-optimal experimental designcontrollable design factorsnonlinear lexicographic goal programmingoptimizationArticle53339240710.1080/0305215X.2020.17323652-s2.0-85082113157Q2WOS:000524163900001Q2