Robust Optimization of a Plunger for the Cooling Process of a Panel in CRT
Kwangki Lee, Kwang Lee, Dong Choi · 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference · 2004
The procedure for robust optimization combined with Kriging metamodel, generated from design of computer experiments, and fuzzy multi-criteria optimization is proposed. Design of computer experiments is employed in order to explore the engineer's design space and to build Kriging metamodels for facilitating the effective solutions to the multi-criteria optimization problems. The Kriging metamodels provide an efficient means to model rapidly and optimize the trade-off between various conflicting goals of multi-criteria objectives, as like a robust optimization of a plunger in CRT (cathode ray tubes) manufacturing process. The plunger model for the cooling process in CRT is integrated and automated with ANSYS and FLUENT within EMDIOS framework, started from the automatic mesh-generation in I-DEAS by using the log file and batch process. The robust optimization of a plunger in the cooling process is performed under the six design variables and two objectives by the Kriging metamodel-based optimization technique. The fuzzy multi-criteria optimization is then introduced and investigated to manipulate the engineer’s confidence level in the optimization process because the fuzzy model can be used to quantify the engineer’s degree of certainty, the so-called confidence level, in the range from 0 to 1.