2026-10-30T01:52:48Zhttps://bayburt-rdlopen.rawdatalibrary.net/oai/requestoai:bayburt-rdlopen.rawdatalibrary.net:bayburt/133922026-10-29T19:52:14Zopenairedrivercom_bayburt_10000col_bayburt_10001com_bayburt_10007col_bayburt_10223An I-optimal experimental design-embedded nonlinear lexicographic goal programming model for optimization of controllable design factorsOzdemir, Akincontrollable design factorsI-optimal experimental designnonlinear lexicographic goal programmingoptimizationQuality improvementOptimal 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.Taylor and Francis Ltd.2021Articlehttps://rdlopen.rawdatalibrary.net/r/bayburt/13392https://doi.org/10.1080/0305215x.2020.17323650305-215XenEngineering Optimizationinfo:eu-repo/semantics/openAccessinfo:eu-repo/semantics/articlehttps://bayburt-rdlopen.rawdatalibrary.net/tr/items/bayburt/13392