• Korean Management Science Review
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• v.24 no.2
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• pp.73-80
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• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1829-1836
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• 2004

This study presents the performance optimization of hypervelocity launcher system by using the experimentall data. During the optimization, the RSM (Response Surface Method) is adopted to find the operating parameters that could maximize the projectile speed. To construct a reliable response surface model, 3 full factorial method is used with the selected design variables, such as piston mass and 2 driver fill pressure. Nine test data could successfully construct the reasonable response surface, which used to yield the optimal operational conditions of the system using the genetic algorithm. The optimization results are confirmed by the experimental test with a good accuracy. Thus, the optimization can improve the performance of the facility.

• Food Science of Animal Resources
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• v.43 no.2
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.92-99
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• 2007

In this paper, optimization of the vaned centrifugal compressor was carried out at a given mass flow rate condition. Firstly, impeller optimization was conducted using response surface method (RSM) which is one of optimization methods. After the optimization of the impeller was completed, diffuser optimization was performed with the optimized impeller. In these processes, Navier-Stokes solver was used to calculate the flow inside the centrifugal compressor. And the optimization is performed with Box-Behnken design method which is efficient for fitting second-order response surfaces to reduce the number of calculations required. As a result, compared with the reference model, the efficiency and the pressure ratio of the optimized impeller and diffuser are found to be increased. The performance at off-design conditions is presented.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.439-443
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• 2002

In this study, three-dimensional incompressible viscous flow analysis and optimization using response surface method are presented for the design of a jet fan. Steady, incompressible, three-dimensional Reynolds averaged Wavier-Stokes equations are used as governing equations, and standard k-$\epsilon$ turbulence model is chosen as a turbulence model. Governing equations are discretized using finite volume method. Sweep angles and maximum thickness of blade are used as design variables for the shape optimization of the impeller in response surface method. The experimental points which are needed to construct response surface are obtained from the D-optimal design and Full Factorial design and relations between design variables and response surface are examined.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.3
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• pp.292-298
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• 2017

Numerical analysis for various design parameters should be preceded by optimal design of composite materials. Numerous studies have been conducted on the bolting of interconnecting beams. In this study, the response surface method was applied to optimize the design of bolted joints connected by laminated wood composite beams. The response surface was created by combining the FEA code for composite analysis and the algorithm for forming the response surface. Optimization on this response surface was performed with a genetic algorithm to derive the results. The determination of the optimum bolt-hole position for the connection of composite beams is an optimization problem. Tsai-Wu composite failure index, maximum deflection, and simple von Mises stress are set as the objective functions. It has been proved that the design results of the optimized bolt-hole are superior to the design performance of the existing conventional bolt-hole position.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.81-89
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• 2005

The response surface method is the statistical method which can be applied to the non-sensitivity based optimization. The response surface which is constructed by the least square method contains only the polynomial terms so that the global maximum and minimum points are easily obtained. In this paper, this response surface method is utilized to optimize the crashworthiness of auto-body members. As the first step, the thickness of a simple circular tube is optimized to confirm the application of the response surface method to the crashworthiness. Optimization of the thickness on the front side member is, then, performed with the constructed response surface of the absorbed energy and deformation. Optimization results demonstrate that the absorbed energy and the deformation pattern of the front side member is improved in the viewpoint of enhancement of the crashworthiness.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.166-171
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• 2004

In this study, shape optimization of micro-static mixer with a cantilever beam was accomplished for mixing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.453-458
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• 2005

Weight minimization of double-deck train carbody is imperative to reduce cost and extend life-time of train. It is required to decide 36 thickness of aluminum extruded panels. However, the design variables are two many to tract. moreover, one execution of structural analysis of double-deck carbody is time-consuming. Therefore, we adopt approximation technique to save computational cost of optimization process. Response surface model is used to apporximate static response of double-deck carbody. To obtain plausible response surface model, orthogonal array is empolyed as design of experiment(DOE). Design improvement by approximate model-based optimization is described. Accuracy and efficiency of optimization by using response surface model are discussed.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.4
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• pp.750-769
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• 2015

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.