• Food Science of Animal Resources
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• v.37 no.1
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• pp.139-146
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• 2017

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1262-1269
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• 2005

Thrust of linear motor is one of the important factor to specify motor performance. Maximum thrust can be obtained by increasing the current in conductor and is relative to the sizes of conductor and magnet. But, the current and the size of conductor have an effect on temperature of linear motor. Therefore, it is practically important to find design results that can effectively maximize the thrust of linear motor within limited range of temperature. Finite element analysis was applied to calculate thrust and the temperature of the conductor was calculated by the thermal resistance. The diameter of copper wire among design variables has discrete value and number of turns must be integer. Considering these facts, special techinque for optimum design is presented. To reduce excessive computation time of thrust in optimization, the design variables was redefined by analysis of variance and second order regression model for thrust was determined by response surface metheodology. As a result, it is shown that the proposed method has an advantage in optimum design of linear motor.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.95-104
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• 2022

This study investigates the complex mechanism of work-family conflict affecting counterproductive behavior of employees based on resource conservation theory and 417 valid samples by using polynomial regression and response surface analysis. Counterproductive work behavior refers to any intentional behavior of an individual that has potential harm to the legitimate interests of the organization or its stakeholders. Results show that first, work-to-family conflict (WFC) and family-to-work conflict (FWC) had four matching types. Compared with "high WFC-low FWC," "low WFC-high FWC" and "low WFC-low FWC" matching conditions, the employee self-control resource depletion and counterproductive work behavior (CWB) are at their highest under "high WFC-high FWC" congruence matching condition. Second, the joint effect of WFC and FWC has a U-shaped relationship with counterproductive behavior. Compared with the "high WFC-low FWC" match state, the level of CWB in the "low WFC-high FWC" match state is higher. Third, the depletion of self-control resources played a mediating role in the effect of WFC on counterproductive behavior. Fourth, emotional intelligence moderated the relationship between the congruence of WFC and FWC and self-control resource depletion. Emotional intelligence was higher, and the positive relationship between the congruence of WFC and FWC and self-control resource depletion was weaker.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.81-89
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• 2023

The purpose of this study is to demonstrate the potential enhancement of the flavonoid contents from Agastache rugosa, which can be obtained as raw materials for functional products in the food medicine industry by identifying important factors for efficient preparation to save costs and time in terms of economic factors. For this reason, response surface methodology using Box-Behnken design was used to optimize the extraction conditions for the maximum yield of seven major compounds from A. rugosa. The optimum conditions were obtained with an ethanol concentration of 60.0%, a temperature of 50 ℃, and an extraction time of 33.6 min, meaning that the regression analysis fits the experimental data well. Under these conditions, the seven major compounds 1-7 had observed values of 2.169, 2.135, 0.697, 2.485, 0.105, 1.247, and 0.551%, respectively. These results show that the observed values are in good agreement with the predicted values in the regression model. This process for optimization study exhibited a basic protocol for obtaining stable ingredients from A. rugosa that are appropriate for the development of effective functional products.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.989-996
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• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.141-149
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• 2017

Due to the inaccuracy of micro-machining, various special processing methods have been investigated recently. Among them, pulse electrochemical machining is a promising machining method with the advantage of no residual stress and thermal deformation. Because the cross section of the wire electrode used in this study is circular, wire-pulse electrochemical machining is suitable for micro-hole machining. By applying the response surface methodology, the experimental plan was made of three factors and three levels: machining time, duty factor, and voltage. The regression equation was obtained through experiments. Then, by referring to the main effect diagram, we fixed the duty factor and machining time with little relevance, and solved the equation for the target 900 microns to obtain the voltage value. The results obtained from the response surface methodology were approximately those of the target value when the actual experiment was carried out. Therefore, it is concluded that the optimal conditions for hole processing can be obtained by the response surface methodology.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.2
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• pp.209-217
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• 2015

Generally welding is one of the most important processes to have a strong influence on the quality and productivity from a manufacture-based industry such as shipbuilding, automotive and machinery. The GMA(Gas Metal Arc) welding process involves large number of interdependent welding parameters which may affect product quality, productivity and cost effectiveness. To solve such problems, mathematical models are required to select the welding parameters for GMA welding process. In this study, the GMA welding process was studied using the information generated during the welding. The statistical analysis of a generalized regression approach was conducted by the following three methods: Firstly using the mathematical model (linear regression, 2nd regression); Secondly GA(Genetic Algorithm) with intelligent models; And finally using response surface analysis of models to develop the relationships between welding parameters and bead width as welding quality.

• Proceedings of the KWS Conference
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• 2004.05a
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• pp.39-41
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• 2004

This study is to optimize the condition of pulse parameters using the response surface method in micro pulse TIG welding of pleated type metallic filter. The input parameters used were pulse current, base current, pulse duty, frequency and welding speed and the hydraulic pressure was used as the output parameter. The central composite design was designed using second order regression model, As the results, the optimal welding condition to manufacture the pleated type metallic filter was obtained.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1628-1633
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• 2016

This paper derives an effective shape of the ferromagnetic pole pieces (low-speed rotor) for the reduction of transmission torque ripple in a magnetic-geared machine based on a Box-Behnken design (BBD). In particular, using a non-linear finite element method (FEM) based on 2-D numerical analysis, we conduct a numerical investigation and analysis between independent variables (selected by the BBD) and reaction variables. In addition, we derive a regression equation for reaction variables according to the independent variables by using multiple regression analysis and analysis of variance (ANOVA). We assess the validity of the optimized design by comparing characteristics of the optimized model derived from a response surface analysis and an initial model.