• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.377-390
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• 2011

A common problem encountered in product or process design is the selection of optimal parameter levels which involves simultaneous consideration of multiple response variables. This is called a multiresponse problem. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. Up to date, various methods have been proposed for the optimization, including the desirability function approach and loss function approach. In this paper, the existing studies in multiresponse optimization are reviewed and a future research direction is then proposed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.117-126
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• 1992

This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables. The method, called the Pairwise Comparison Stochastic Cutting Plane (PCSCP) method, combines good features from interactive multiple objective mathematical programming methods and response surface methodology. The major characteristics of the PCSCP algorithm are: (1) it interacts progressively with the decision maker (DM) to obtain his preferences, (2) it uses good experimental design to adequately explore the decision space while reducing the burden on the DM, and (3) it uses the preference information provided by the DM and the sampling error in the responses to reduce the decision space. This paper presents the basic concepts of the PCSCP method along with its performance for solving randomly selected test problems.

• Fisheries and Aquatic Sciences
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• v.10 no.3
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• pp.103-112
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• 2007

High prices, overfishing, and contamination have limited the availability of natural caviar as a food product. We attempted to apply encapsulation by calcium-alginate gel membranes to caviar analog preparation in an effort to produce a high-quality replacement for natural caviar. Physical conditions of stirring speed $(X_1,\;rpm)$ and gelation time $(X_2,\;min)$ as the independent variables for gelation were optimized by response surface methodology. Sphericity $(Y_1,\;%)$, diameter $(Y_2,\;mm)$, membrane thickness $(Y_3,\;mm)$, rupture strength $(Y_4,\;g)$, and rupturing deformation $(Y_5,\;mm)$ were used as the dependent variables to compare characteristics of the capsules for caviar analogs with natural caviar. The values of the independent variables as evaluated by multiple response optimization were $X_1=-0.1271 (278 rpm) and $X_2=0.4436$ (12.2 min), respectively. Predicted values of the four dependent variables were $Y_1=97.7%,\;Y_2=2.97mm,\;Y_4=1,465g,\;and\;Y_5=1.15mm$. Membrane thickness $(Y_3)$ was eliminated from the dependent variables for multiple response optimization because it could not be measured with an image analyzer. The experimental values prepared under the optimal conditions for verification nearly coincided with the predicted values and satisfied the conditions of natural caviar.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.114-126
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• 2009

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.30-37
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• 2017

When a wheel profile of a train-tram is designed, both train and tram tracks should be considered. This study designed a wheel profile that enables high-speed driving(200km/h) on the train track and low speed driving on the tram track with multiple sharp curves. The study used the approximation optimization method to reduce cost and time, used the sequential quadratic programming method as the optimized algorithm, and the central composite design and response surface method as an approximate model. The optimized wheel shape based on this approximation optimization method reduced wear of the initial wheel showed a better performance in terms of derailment and lateral force.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.453-458
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• 2009

This paper presents a numerical evaluation of the flow rate of air conditioner outdoor unit as function of shroud design parameters. To determine the optimal design parameters, we investigated the flow rate by changing bell mouth height, fan height, fan guide height, fan width. The evaluation of the relative priority of the design parameters was performed to choose three important parameters in order to use a response surface method. The flow rate of the optimum model, compared to that of the base model, was increased by about 6.25%.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.11
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• pp.599-605
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• 2009

This paper presents a numerical evaluation of the flow rate of air conditioner outdoor unit by investigating the effects of fan location and shroud shape. To determine optimal design parameters, we investigated the exhaust flow rate by changing shroud height, fan height, fan guide height, and fan width. The 3rd order central composite design was performed to select three most important parameters affecting the exhaust flow rate. According to the result of response surface method, the exhaust flow rate of the optimum model increased by 6.25% compared to that of the base model.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.83-87
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• 2002

Many industrial products such as paints, ink and adhesives are composed of the ingredients of a mixture. In mixture experiments, the characteristics of quality(response) depends only on the proportions of the ingredients and does not depend on the total amount of the mixture. This article discusses the constrained mixture experimental design, the data analysis, and the optimum formulation of ingredients based on the two quality characteristics - taste and flavor. It IS shown that efficient designs can be constructed from D-optimal criterion. Special cubic models were selected as the final mixture response surfaces for both reponses. The desirability function was used for the optimization of the two responses.