• Food Science of Animal Resources
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• v.39 no.1
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• pp.114-120
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• 2019

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. As a design for a response surface experiment, a central composite design (CCD) with multiple runs at the center point is frequently used. However, sometimes there exist situations where some among the responses at the center point are outliers and these outliers are overlooked. Since the responses from center runs are those from the same experimental conditions, there should be no outliers at the center point. Outliers at the center point ruin statistical analysis. Thus, the responses at the center point need to be looked at, and if outliers are observed, they have to be examined. If the reasons for the outliers are not errors in measuring or typing, such outliers need to be deleted. If the outliers are due to such errors, they have to be corrected. Through a re-analysis of a dataset published in the Korean Journal for Food Science of Animal Resources, we have shown that outlier elimination resulted in the increase of the maximum possible R-square that the modeling of the data can obtain, which enables us to improve the quality of response surface analysis.

• Transactions on Electrical and Electronic Materials
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• v.7 no.2
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• pp.81-86
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• 2006

In this paper, the response surface modeling of the control of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatment is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. After the design of experiments is performed, the process model is then explored using the response surface methodology. The analysis of variance is used to analyze the statistical significance and the effect plots are also investigated to examine the relationship between the process parameters and the response.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.4
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• pp.56-68
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• 2014

This paper presents an experiment on the modeling, analysis, prediction and optimization of machining parameters used during the turning process of the low-carbon steel known as ST40. The parameters used to develop the model are the cutting speed, the feed rate, and the depth of the cut. The experiments were carried out under various conditions, with three level of parameters and two different treatments for each level (with and without a lubricant), to determine the effects of the parameters on the surface roughness and electric current consumption. These effects were investigated using response surface methodology (RSM). A second-order model is used to predict the values of the surface roughness and the electric current consumption from the results of experiments which collected preliminary data. The results of the experiment and the predictions of the surface roughness and electric current consumption under both treatments were found to be nearly identical. This result shows that the feed rate is the main factor that influences the surface roughness and electric current consumption.

• Transactions on Electrical and Electronic Materials
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• v.7 no.6
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• pp.297-300
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• 2006

The response surface modeling of the pretilt angle control using ion-beam (IB) alignment on nitrogen doped diamond-like carbon (NDLC) thin film layer is investigated. This modeling is used to analyze the variation of the pretilt angle under various process conditions. IB exposure angle and IB exposure time are considered as input factors. The analysis of variance technique is settled to analyze the statistical significance, and effect plots are also investigated to examine the relationships between the process parameters and the response. The model can allow us to reliably predict the pretilt angle with respect to the varying process conditions.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1882-1887
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• 2003

The response surface method (RSM) became one of famous meta modeling techniques, however its approximation errors give designers several restrictions. Classical RSM uses the least squares method (LSM) to find the best fitting approximation models from the all given data. This paper discusses how to construct RSM efficiently and accurately using moving least squares method (MLSM) with sensitivity information. In this method, several parameters should be determined during the construction of RSM. Parametric study and optimization for these parameters are performed. Several difficulties during approximation processes are described and numerical examples are demonstrated to verify the efficiency of this method.

• 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 Information Technology Application
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• v.3 no.3
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• pp.1-24
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• 2001

This paper introduces the genetic programming algorithm(GP), which can approximate highly nonlinear functions, as a tool for the modeling of response surfaces. When the response surfaces is approximated, the very small or minimal teaming set should be used, and thus it is almost certain that GP trees will show overfilling that must be avoided at all costs. We present a novel method, calledDDBS(DirectionalDerivative-Based Smoothering), which very effectively eliminates the unwanted behaviors of GP trees such as large peaks, oscillations, and also overfitting. Four illustrative numerical examples are given to demonstrate the performance of the genetic programming algorithm that adopts DDBS.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.173-176
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• 1999

Frequency responses of the surface acoustic wave(SAW) filters are simulated by using the impulse modeling. The simulation technique of the SAW filters is to use the Fourier transformation to make a correspondence between the impulse response of the filter and the taps in the delay line. Since the Fourier series must be truncated after a finite number of terms, window functions are often used to weight the coefficients to obtain the desirable side-lobe level and bandwidth. The filter design is operated through the iterative simulation procedures. The design process is capable of yielding filters with optimized frequency response characteristics.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.366-371
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• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.

• International Journal of Korean Welding Society
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• v.2 no.2
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• pp.47-50
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• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.