• Proceedings of the KIEE Conference
• /
• 1998.11b
• /
• pp.493-495
• /
• 1998

Robust design is one method to make manufacturing less sensitive to manufacturing process. Also it is cost effective technique to improve the quality process. This method uses statistically planned experiments to vary settings of important process control parameters. In this paper we apply fuzzy optimization and fuzzy logic system to robust design concept. First a method which uses fuzzy optimization in obtaining optimum settings by measured data from experiments will be presented. Second, fuzzy logic system is made to reduce experiments using experiments results consisted with key control parameter combinations. Then optimum parameter set points are obtained by the descrebed first fuzzy optimization method after prediction the results of each parameter combinations considering each control parameter variations by nonsingleton fuzzy logic system concept.

• Structural Engineering and Mechanics
• /
• v.86 no.2
• /
• pp.249-260
• /
• 2023

The uncertainties involved in structural performances are of importance when the optimum number and property of seismic retrofit devices are determined. This paper proposes a seismic retrofit design framework for asymmetric soft-first-story buildings, considering uncertainties in the soil condition and seismic retrofit device. The effect of the uncertain parameters on the structural performance is used to find a robust and optimal seismic retrofit solution. The framework finds a robust and optimal seismic retrofit solution by finding the optimal locations and mechanical properties of the seismic retrofit device for different realizations of the uncertain parameters. The structural performance for each realization is computed to evaluate the effect of the uncertainty parameters on the seismic performance. The framework utilizes parallel processing to decrease the computationally intensive nonlinear dynamic analysis time. The framework returns a robust design solution that satisfies the given limit state for every realization of the uncertain parameters. The proposed framework is applied to the seismic retrofit design of a five-story asymmetric soft-first-story case study structure retrofitted with a viscoelastic damper. Robust optimal parameters for retrofitting a structure to satisfy the limit state for the different realizations of the uncertain parameter are found using the proposed framework. According to the performance evaluation results of the retrofitted structure, the developed framework is proved effective in the seismic retrofit of the asymmetric structure with inherent uncertainties.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.11
• /
• pp.180-187
• /
• 2003

A CAD-based seamless design system for MEMS named DS/MEMS was developed which performs coupled-field analysis, optimal and robust design. DS/MEMS has been developed by means of integrating commercial codes and inhouse code-SolidWorks, FEMAP, ANSYS and CA/MEMS. This strategy results in versatility that means to include various analysis model, corresponding analyses and approximated design sensitivity analysis and user friendliness that design variables are taken to be selectable directly from a CAD model, that the problem is formulated under a window environment and that the manual job during optimization process is almost eliminated. DS/MEMS works on a parametric CAD platform, integrating CAD modeling, analysis, and optimization. Nonlinear programming algorithms, the Taguchi method, and response surface method are made available for optimization. One application problem is taken to illustrate the proposed methodology and show the feasibility of DS/MEMS as a practical tool.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.8
• /
• pp.24-32
• /
• 2006

Using a deterministic design optimization, the effect of uncertainty can result in violation of constraints and deterioration of performances. For this reason, design optimization is required to guarantee reliability for constraints and ensure robustness for an objective function under uncertainty. Therefore, this study drew Monte Carlo Simulation(MCS) for the evaluation of reliability and robustness, and selected an artificial neural network as an approximate model that is suitable for MCS. Applying to the aero-structural optimization problem of aircraft wing, we can explore robuster optima satisfying the sigma level of reliability than the baseline.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.13 no.2
• /
• pp.83-91
• /
• 2003

Pantograph design Process must be considered in terms of stability of aerodynamics and reduction of aeroacoustics. Furthermore pantograph needs to be insensible to severe circumstance condition like typhoon, tunnel, a change of season. In this paper, robust design of panhead sections is conducted based on the Taguchi's design of experiment method. In the aeroacoustic noise analysis, an acoustic analogy using the Ffowcs Williams and Hawkings(FW-H) equation is used to calculate the flow induced sound pressure level in aeroacoustics. From the near-field CFD analysis data, the far-field noise is predicted at the positions of 25 m away from Pantograph. Based on aerodynamic(CFD) and aeroacoustic(FW-H) analysis data, the optimal sizing and Positioning of panhead elements are determined using robust design optimization method. Design parameters such as thickness, length and radius are controllable factors, while outdoor air temperature and atmospheric pressure are considered as uncontrollable factors in the context of Taguchi's approach. A number of CFD simulation and aeroacoustic analysis are performed based on orthogonal arrays. In this paper, two-step optimization method is used as a parameter design procedure. It is executed using signal to noise(S/N) ratio and analysis of means(ANOM) method. So Thus, an optimal level of design parameters Is extracted to minimize the disconnection ration between contact strips and catenary system, and reduce the far-field aeroacoustic noise.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.5
• /
• pp.1-7
• /
• 2008

This paper presents not only the robust stabilization technique but also robust non-fragile controller design method for discrete-time singular systems and static state feedback controller with multiplicative uncertainty. The condition for the existence of robust stabilization controller, the admissible controller design method, and the measure of non-fragility in controller are proposed via LMI(linear matrix inequality) approach. In order to get the maximum measure of non-fragility, the obtained sufficient condition can be rewritten as LMI optimization form in terms of transformed variable. Therefore, the presented robust non-fragile controller for discrete-time singular systems guarantees robust stability in spite of parameter uncertainty and controller fragility. Finally, a numerical example is given to show the validity of the design method.

• Nuclear Engineering and Technology
• /
• v.54 no.11
• /
• pp.4181-4194
• /
• 2022

Main steam safety valves are commonly used in nuclear power plants to provide final protections from overpressure events. Blowdown and dynamic stability are two critical characteristics of safety valves. However, due to the parameter sensitivity and multi-parameter features of safety valves, using traditional method to design and/or optimize them is generally difficult and/or inefficient. To overcome these problems, a surrogate model-based valve design optimization is carried out in this study, of particular interest are methods of valve surrogate modeling, valve parameters global sensitivity analysis and valve performance optimization. To construct the surrogate model, Design of Experiments (DoE) and Computational Fluid Dynamics (CFD) simulations of the safety valve were performed successively, thereby an ensemble surrogate model (E-AHF) was built for valve blowdown and stability predictions. With the developed E-AHF model, global sensitivity analysis (GSA) on the valve parameters was performed, thereby five primary parameters that affect valve performance were identified. Finally, the k-sigma method is used to conduct the robust optimization on the valve. After optimization, the valve remains stable, the minimum blowdown of the safety valve is reduced greatly from 13.30% to 2.70%, and the corresponding variance is reduced from 1.04 to 0.65 as well, confirming the feasibility and effectiveness of the optimization method proposed in this paper.

• Transactions of the Society of Information Storage Systems
• /
• v.1 no.2
• /
• pp.137-142
• /
• 2005

In this paper, we propose a new servo system design strategy to reduce the position error signal(PES) and track mis-registration(TMR) in magnetic disk drive systems. The proposed method provides a systematic design procedure based on the plant model and an optimal solution via an optimization with a 'Robust Random Neighborhood Search(RRNS)' algorithm. In addition, it guarantees the minimum PES level as well as stability to parametric uncertainties. Furthermore, the proposed method can be used to estimate the performance at the design stage and thus can reduce the cost and time for the design of the next generation product. The reduction of PES as well as robust stability is demonstrated by simulation and experiments.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.556-567
• /
• 1998

Robust design in industry is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio(SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure. in the two different experimental design(product array, combined array) approaches.

• Journal of Korean Society for Quality Management
• /
• v.26 no.4
• /
• pp.88-100
• /
• 1998

Robust design in industry is an a, pp.oach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise raio(SN) to achieve the a, pp.opriate set of operating conditions where variablity around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure in the two different experimental design(product array, combined array) a, pp.oaches.