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Design of an optical pattern in a light-guide panel ͑LGP͒ has relied on empirical methods. However, the characteristics of developing liquid-crystal display ͑LCD͒ products such as frequent design modifications, various design conditions, and a short development period make it difficult for the empirical design approach to cope with various design requirements for size, shape, and optical performance of the LCD products. The most important tasks for the design of LGPs are improving average illuminance and the uniformity of the backlight unit. To meet these requirements, a design for an incoupling and an outcoupling part of the LGP is presented. These two parts can be designed in two separate phases: the first for the incoupling part and the second for the outcoupling part. The shape of serration in the incoupling part was first determined by design of experiments, and the dot patterns in the outcoupling part were subsequently determined by a density-based approach with progressive quadratic response surface modeling. Using this design approach, the illuminance was increased from 2241 lx in the initial design to 2299 lx in the optimal design, and its uniformity also increased from 38% to 82%.

Hantool Engineering, Korea 3) Research & Development Division, Hyundai Motors Group, Abstract : In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

Reliability-Based Design Optimization (RBDO) is an effective method to handle an optimization problem constrained by reliability performance. In spite of its great benefits, one of the most challenging issues for implementing RBDO is associated with very intensive computational demands of Reliability Analysis (RA). Moreover, an accurate and efficient RA method is indispensible to apply RBDO to practical engineering design problems. Among various RA methods, an enhanced Dimension Reduction (eDR) method is the most popular one due to the high computational efficiency. It is very desirable to obtain an accurate and efficient RA result by using the minimum number of sampling points. But, it is difficult to determine it. That is because it depends on the nonlinearity of a constraint from approximating a model and the degree of uncertainty from integrating a design factor. In this research, eDR method with variable sampling points has been studied and proposed to resolve the early mentioned difficulties. The main idea of the suggested method is to employ a different number of axial sampling points for each random design factor. It is according to the nonlinearity of a constraint and the degree of uncertainty of each random design factor. For each random variable, it begins to use three points first and decides to stop or increase the axial sampling points based upon the proposed criteria in this study. In case of increasing sampling points, it is incremented by one sampling point and ended up five sampling points at most. As it shown in the result, the efficiency of eDR method with variable sampling points for each random variable is superior to the one with fixed sampling points without sacrificing any accuracy. Through the three representative RA problems, it is verified that the proposed RA method generates the result 26.5% more efficiently on average than the conventional eDR method with fixed sampling points. Furthermore, the Performance Measure Approach (PMA) was used to evaluate the performance of RBDO using the new RA method. For the comparison, three mathematical and one engineering RBDO problems were solved by both eDR method with variable sampling points and conventional one with fixed sampling points. Finally, the comparison results clearly demonstrate that RBDO using the suggested RA method is superior to the conventional one in terms of accuracy and efficiency.