• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.585-595
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• 2001

A second-order response surface model is often used to approximate the relationship between a response factor and a set of explanatory factors. In this article, we deal with canonical analysis in response surface models. For the interpretation of the geometry of second-order response surface model, standard errors and confidence intervals for the eigenvalues of the second-order coefficient matrix play an important role. If the confidence interval for some eigenvalue includes 0 or the estimate of some eigenvalue is very small (near to 0) with respect to other eigenvalues, then we are able to delete the corresponding canonical factor. We propose a formulation of criterion which can be used to select canonical factors. This criterion is based on the IMSE(=Integrated Mean Squared Error). As a result of this method, we may approximately write the canonical factors as a set of some important explanatory factors.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.514-517
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• 2002

We investigated response characteristics of twisted nematic (TN) cell with different nematic liquid crystals (NLCs) and cell gap d on a rubbed polyimide (PI) surface. High transmittance and fast response time of the TN cell on the rubbed PI surface were achieved by using high birefringence (${\Delta}n$) and low cell gap d. The response time of TN cell on the rubbed PI surface was measured 5.1 ms. The transmittance and response time of the TN cell on the rubbed PI surface decreased with decreasing ${\Delta}nd$.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.9
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• pp.808-811
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• 2002

We investigated response characteristics of twisted nematic (TN) cell with different nematic liquid crystals (NLCs) and cell gap d on a rubbed polyimide (PI) surface. High transmittance and fast response time of the TN cell on the rubbed PI surface were achieved by using high birefringence (Δn) and low cell gap d. The response time of TN cell on the rubbed PI surface was measured 5.1 ms. The transmittance and response time of the TN cell on the rubbed PI surface decreased with decreasing Δnd.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.582-588
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• 2010

This paper presents the Application of Response Surface Method for Optimal Transfer Conditions of MLCC Alignment System. his paper is composed of two parts: (1) Testing performance verification of MLCC alignment system, compared with manual operation; (2) Applying response surface method to figuring out the optimal transfer conditions of MLCC transfer system. Based on the successfully developed MLCC alignment system, the optimal transfer conditions have been explored by using RSM. The simulations using $ADAMS^{(R)}$ has been performed according to the cube model of CCD. By using $MiniTAB^{(R)}$, we have established the model of response surface based on the simulation results. The optimal conditions resulted from the response optimization tool of $MiniTAB^{(R)}$ has been verified by being assigned to the prototype of MLCC alignment system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.510-513
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• 2004

This paper represents the response surface model for the cell gap on the flexible liquid crystal display (LCD) process. Using response surface methodology (RSM). D-optimal design is carried out to build the design space and the cell gap is characterized by the quadratic model. The statistical analysis is used to verify the response surface model. This modeling technique can predict the characteristics of the desired response, cell gap, varying with process conditions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.42-48
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• 2006

In this study, a repetitive response surface enhancement technique (RRSET) is proposed as a new system approximation method for the efficient multidisciplinary design and optimization (MDO). In order to represent the highly nonlinear behavior of the response with second order polynomials, RRSET introduces a design space transformation using stretching functions and repetitive response surface improvement. The tentative optimal point is repetitively included to the set of experimental points to better approximate the response surface of the system especially near the optimal point, hence a response surface with significantly improved accuracy can be generated with very small experimental points and system iterations. As a system optimizer, the simulated annealing, which generates a global design solution is utilized. The proposed technique is applied to several numerical examples, and demonstrates the validity and efficiency of the method. With its improved approximation accuracy, the RRSET can contribute to resolve large and complex system design problems under MDO environment.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.557-578
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• 2007

In Response Surface Methodology (RSM), rotatability is a natural and highly desirable property. For second order general correlated regression model, the concept of robust rotatability was introduced by Das (1997). In this paper a new measure of robust rotatability for second order response surface designs with correlated errors is developed and illustrated with an example. A comparison is made between the newly developed measure with the previously suggested measure by Das (1999).

• Journal of Korean Society for Quality Management
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• v.25 no.2
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• pp.102-111
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• 1997

In this paper I discuss a method of constructing the confidence region for the logistic response surface model. The construction involves a, pp.ication of a general fitting procedure because the log odds is linear in its parameters. Estimation of parameters of the logistic response surface model can be accomplished by maximum likelihood, although this requires iterative computational method. Using the asymptotic results, asymptotic covariance of the estimators can be obtained. This can be used in the construction of confidence regions for the parameters and for the logistic response surface model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.894-900
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• 2000

Optimization of chassis frame is performed according to the minimization of eleven responses representing one total frame weight, three natural frequencies and seven strength limits of chassis frame that are analyzed by using each response surface model from D-optimal design of experiments. After each response surface model is constructed form D-optimal design and random orthogonal array, the main effect and sensitivity analyses are successfully carried out by using this approximated regression model and the optimal solutions are obtained by using a nonlinear programming method. The response surface models and the optimization algorithms are used together to obtain the optimal design of chassis frame. The eleven-polynomial response surface models of the thirteen frame members (design factors) are constructed by using D-optimal Design and the multi-disciplinary design optimization is also performed by applying dual response analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1257-1260
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• 2005

Grinding process has unique characteristics compared with other machining processes. The cutting edges of the grinding wheel don't have uniformity and act differently on the workpiece at each grinding. The response surface analysis is one of various methods for optimizing and evaluating the process parameters to achieve the desired output. In this study, the effect of the grinding parameters on outcomes of the surface grinding was analyzed experimently. To predict the grinding outcomes and to select the grinding conditions before grinding, the second-order response surface models for the grinding force and the surface roughness were developed.