• Knowledge Management Research
• /
• v.20 no.3
• /
• pp.39-47
• /
• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.813-817
• /
• 2002

This paper presents the reliability analysis technique on the dynamic characteristics of the torsion beam consisting the suspension system of passenger car. We utilize response surface method (RSM) and Monte Carlo simulation to obtain the response surface model that describes the limit state function for the natural frequencies of the torsion beam. Using the response surface model and the design optimization technique, we have obtained the optimized section considering the reliability of the torsion beam structure.

• Progress in Superconductivity and Cryogenics
• /
• v.6 no.1
• /
• pp.18-21
• /
• 2004

This paper presents the optimization for shape design of a field coil used High Temperature Superconducting Motor (HTSM). In materials of HTSM, critical current Ic is more sensitive to magnetic fields directed along the axis or the unit cell ($B_{\bot}$). Thus, in the shape design of the HTS magnet. the maximum $B_{\bot}$ should be reduced to limit Ic. In order to reduce the maximum $B_{\bot}$, the shape optimization of the magnet, which is used for the field coil of HTSM, is necessary. It can be accomplished by using Response Surface Methodology (RSM). Finally, the result of RSM is verified by comparison with these experimental results.

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

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2003.10a
• /
• pp.145-150
• /
• 2003

The present study aims to optimize the performance of the Two-Stage Gas Gun by using the experimentally obtained data. RSM(Response Surface Method) was adopted in the optimization process to find the operating parameter than can maximize the projectile speed with the minimum number of tests. To decide the test points which results can consist of the response surface, 3$^{k}$ full factorial method was used, and the design variables were chosen with piston mass and 2$^{nd}$ driver fill pressure. The response surface was composed by nine test results and consequently the optimization was done with GENOCOP III, inherently GA code, in order to seek the optimal test point. The optimal test condition from the response surface was verified by the experiment. Results showed that the optimization process with response surface can successfully predict the test results fairly well. This study shows the possibility of performance optimization for the experimental facilities using numerical optimization algorithm.

• Proceedings of the KIEE Conference
• /
• 2007.04c
• /
• pp.74-76
• /
• 2007

A hybrid optimization method is proposed for cogging torque reducing in BLDC motor. The proposed hybrid optimization method comprises a response surface method (RSM) and a gradient search method (GSM). The RSM is effective and global method in optimization problem but having large approximation error. The GSM is accurate and fast search method for optimal solution but having local behavior. To reduce approximation error and computation time a hybrid method (RSM+GSM) is proposed method. To illustrate the effectiveness of the proposed method, a comparison between conventional RSM and the proposed hybrid method is made. A simulation results verify that the hybrid method can achieve favorable design performance.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.1
• /
• pp.64-68
• /
• 2012

In this paper, a design method for minimizing the cogging torque of an Interior Permanent Magnet Motor (IPM) is proposed based on a hybrid algorithm. The suggested optimization algorithm is based on a combination of the Response Surface Method (RSM) and Simplex Method. The results show that the proposed method provides improved characteristics compared to the conventional methods, such as a shorter calculation time and the acquisition of a more correct solution.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.6
• /
• pp.461-468
• /
• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

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

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.972-975
• /
• 2004

In order to reduce the noise of BLDC motor, a systematic optimization procedure for rotor structure is presented. The noise index is defined as the sum of volume velocity of FE-model that are calculated at the dominant frequencies during dehydration process, which is based on the principle of radiation simple volume source. Then, the five design variables are selected to represent the shape and layout or rotor structure. This discrete design optimization problem for minimizing the noise index is solved by 3-level orthogonal array based effect analysis. Finally, the response surface method (RSM) combined optimization approach is employed for more refining the approximate optimum.