• 대한기계학회논문집A
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• 제28권9호
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• pp.1368-1383
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• 2004

Robust design has been developed with the expectation that an insensitive design can be realized. That is, a product designed by robust design should be insensitive to external noises or tolerances. Robust design can be classified into three methods: (1) The Taguchi method (2) robust optimization (3) robust design by the axiomatic approach. In this paper, each method is reviewed and investigated. Pros and cons fur each method are discussed and a future direction for development is proposed.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.836-840
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• 2006

Design optimization of layered plates bonding process is conducted to achieve high product quality by considering uncertainties in a manufacturing process. During the cooling process of the sequential sub-processes, different thermal expansion coefficients lead to residual stress and displacement. thus resulting in defects on the surface of the adherent. So robust process optimization is performed to minimize the residual stress mean and variation of the assembly while constraining the distortion as well as the instantaneous maximum stress to the allowable limits. In robust process optimization, the dimension reduction (DR) method is employed to quantify both reliability and quality of the layered plate bonding. Using this method. the average and standard deviation is estimated. Response surface is constructed using the statistical data obtained by the DRM for robust objectives and constraints. from which the optimum solution is obtained.

• 대한기계학회논문집A
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• 제26권8호
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• pp.1719-1726
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• 2002

Design variables and design parameters are rarely deterministic in practice. Robust optimal design takes into consideration of the uncertainties in the design variables and parameters. Robust optimization methodology with probability constraints requires a lot of system analyses fer calculating failure probability of each constraint. By introducing an envelope function to reduce the number of constraints, efficiency of robust optimization techniques can be considerably improved. Through four illustrative examples, it is shown that the number of system analyses is greatly decreased while little differences in the optimum results are observed.

• 한국소음진동공학회논문집
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• 제16권3호
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• pp.298-306
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• 2006

In our previous paper, we developed a robust saturation controller for the linear time-invariant (LTI) system involving both actuator's saturation and structured real parameter uncertainties. This controller can only guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. But we cannot analytically make any comment on control performance of this controller. In this paper, we suggest a method to use linear matrix inequality (LMI) optimization problem which can analytically explain control performance of this robust saturation controller only in nominal system. The availability of design method using LMI optimization problem for this robust saturation controller is verified through a numerical example for the building with an active mass damper (AMD) system.

• 대한기계학회논문집A
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• 제25권9호
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• pp.1483-1492
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• 2001

A robust optimization procedure is applied to determine the design of the laminated composite plates with buckling constraints. In order to investigate the variation effect to the whole performance of a structure, both design variables and system parameters are assumed as random variables about their nominal values. The robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required. Considering the information of uncertainty, robust optima for the buckling load of the laminated composite plates with cut-out is obtained. The robustness of the structures is compared to that of the deterministic optimization using scaling factors.

• 대한기계학회논문집A
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• 제31권1호
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• pp.113-120
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• 2007

Design optimization of layered plates bonding process is conducted by considering uncertainties in a manufacturing process, in order to reduce the crack failure arising due to the residual stress at the surface of the adherent which is caused by different thermal expansion coefficients. Robust optimization is peformed to minimize the mean as well as its variance of the residual stress, while constraining the distortion as well as the instantaneous maximum stress under the allowable reliability limits. In this optimization, the dimension reduction (DR) method is employed to quantify the reliability such as mean and variance of the layered plate bonding. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. The obtained robust optimal solution is verified by the Monte Carlo simulation.

• Earthquakes and Structures
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• 제11권2호
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1763-1768
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• 2003

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

• Journal of Magnetics
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• 제19권4호
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• pp.385-392
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• 2014

Uncertainties in loads, materials and manufacturing quality must be considered during electromagnetic devices design. This paper presents an effective methodology for robust optimization design based on the variance decomposition in order to keep higher accuracy of the robustness prediction. Sobol' theory is employed to estimate the response variance under some specific tolerance in design variables. Then, an optimal design is obtained by adding a criterion of response variance upon typical optimization problems as a constraint of the optimization. The main contribution of this paper is that the proposed method applies the variance decomposition to obtain a more accurate variance of the response, as well save the computational cost. The performance and robustness of the proposed algorithms are investigated through a numerical experiment with both an analytic function and the TEAM 22 problem.

• 대한기계학회논문집A
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• 제24권1호
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• pp.215-224
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• 2000

In order to reduce the variation effects of uncertainties in the engineering environments, new robust optimization method, which considers the uncertainties in design process, is proposed. Both design variables and system parameters are considered as random variables about their nominal values. To ensure the robustness of performance function, a new objective is set to minimize the variance of that function. Constraint variations are handled by introducing probability constraints. Probability constraints are solved by the advanced first order second moment (AFOSM) method based on the reliability theory. The proposed robust optimization method has an advantage that the second derivatives of the constraints are not required. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.