• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.730-739
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• 2005

A common problem encountered in product or process design is the selection of optimal parameter levels which involve simultaneous consideration of multiresponse variables. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. To date, various methods have been proposed for the optimization stage, including the desirability function approach and loss function approach. In this paper, we first propose a framework classifying the existing studies and then propose some promising directions for future research.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.377-380
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• 2006

A common problem encountered in product or process design is the selection of optimal parameter levels which involve simultaneous consideration of multiresponse variables. To date, various methods have been proposed for multiresponse optimization. In this paper, we briefly review the existing methods and then discuss some recent advances in this field.

• Clean Technology
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• v.21 no.1
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• pp.62-67
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• 2015

We have developed a versatile method for the preparation of chemically linked graphene/multi-walled carbon nanotubes (MWNTs) hybrid materials via simple acid-catalyzed dehydration reaction between graphene oxide (GO) and amine-functionalized MWNTs (af-MWNTs). In this condition, ketone (-C=O) groups in GO and primary amine (-NH₂) moieties in af-MWNTs readily react to form imine (-C=N-) linkage. The chemical structures of graphene/MWNTs hybrid materials have been investigated using various microscopic and spectroscopic measurements. As a result of the synergetic effects of hybrid materials such as improved surface area and the superior structural restoration of graphitic networks, the hybrid materials demonstrate improved capacitance with excellent long-term stability. Furthermore, controlled experiments were conducted to optimize the weight ratio of graphene/MWNTs in hybrid materials. The highest capacitance of 132.4 F/g was obtained from the GM7.5 material, in which the weight ratio between graphene and MWNTs was adjusted to 7.5/1, in 1M KOH electrolyte at a scan rate of 100 mV/s.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2922-2927
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• 2008

The test of engine performance using the engine dynamometer needs technical researchers and facilities. A variety of CAE analysis programs and DoE(Design of Experiments) are used to analyze data efficiently instead of tests. The study got data from simulations of WAVE that used to model the SI engine to identify performance of engine. DoE makes it possible to know effectiveness of factors for power, BSFC, volume efficiency and find optimum condition in each factor through minimizing number of experiments. CA50 has effect on power and BSFC as volume efficiency is related with cylinder liner temperature and heat coefficients. The final result in DoE could be identified of consistency above 98% after substituting the data to WAVE.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.28-28
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• 2009

최근 전세계적으로 유가 상승 및 배기가스 배출 저감과 관련된 각종 환경규제에 대응하기 위하여 선진 자동차회사들은 $CO_2$ 배출 저감 기술과 기존 내연기관 차량의 연비향상을 위해 엔진성능 개선, 구동시스템의 최적화, 차량 경량화, 공기저항 감소 등에 초점을 맞춰 차량의 연비향상과 배기가스 규제에 대응하고 있다. 특히, 자동차 중량의 30%를 차지하는 차체의 경량화는 엔진효율을 높여 자동차의 성능향상을 극대화시키고, 그로 인해 연비향상을 도모할 수 있으므로 환경오염 방지와 연료절감에 가장 적합하고 효과적인 방법이다. 이에 기존의 강재에 비해 비중이 낮으면서 유사한 강도와 내식성이 뛰어난 알루미늄 합금의 차체 적용에 대한 연구가 진행되고 있다. 본 연구에서는 자동차 Door에 알루미늄 합금(Al 5052)의 적용 가능성을 판단하기 위해 반응표면분석법(Response surface methodology)을 이용하여 저입열 Pulse MIG 용접 공정변수를 최적화하였다. 첫째, 저입열 Pulse MIG 용접에서 용접 공정 변수(용접전압, 용접속도, Gap)의 변화가 비드 형상에 미치는 영향에 대해 평가하였다. 요인분석법을 이용하여 용접 공정 변수와 비드 형상 변수와의 주효과와 교호작용효과를 분석하였고, 이를 통해 비드 형상 변수에 영향을 크게 미치는 용접 공정변수를 선별하여 다중회귀분석을 통해 용접 공정 변수 변화에 따른 비드형상 예측 회귀모델을 제안하였다. 둘째, 자동차 Door 생산 현장에서 박판 알루미늄 합금 겹치기 용접 이음부의 0~1 mm 갭 발생에 대해 강건한 용접조건을 제시하기 위해 반응표면법(Response surface methodology)을 이용하여 저입열 Pulse MIG 용접 공정 변수를 최적화하였고, 그 적용 가능성을 확인하였다.

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.316-320
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• 2024

To optimize the emulsion stability and antibacterial activity against Escherichia coli (E. coli) of cosmeceuticals using Scutellaria baicalensis extracts and olive wax as natural emulsifiers, we conducted a study. The independent variables were the amounts of Scutellaria baicalensis extracts and olive wax added. The response variables included the emulsion stability index (ESI) of the cosmeceuticals product and the inhibition diameter against E. coli. Through central composite design-response surface methodology (CCD-RSM), we obtained a statistically significant and reliable regression equation within a 95% confidence interval. By optimizing multiple responses, we determined that the optimal emulsification conditions that satisfied both ESI and E. coli inhibition diameter were 3.7 wt% of Scutellaria baicalensis extracts and 2.7 wt% of olive wax. The predicted ESI and E. coli inhibition diameter were 97.9% and 9.7 mm, respectively. When actual experiments were conducted under the optimal conditions, the measured ESI and E. coli inhibition diameter were 95.0% and 9.4 mm, respectively, with an average error rate of 3.2 ± 0.4%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7061-7070
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• 2015

Multi-Response Surface Optimization aims at finding the optimal setting of input variables considering multiple responses simultaneously. The Weighted Mean Squared Error (WMSE) minimization approach, which imposes a different weight on the two components of mean squared error, squared bias and variance, first obtains WMSE for each response and then minimizes all the WMSEs at once. Most of the methods proposed for the WMSE minimization approach to date are classified into the prior preference articulation approach, which requires that a decision maker (DM) provides his/her preference information a priori. However, it is quite difficult for the DM to provide such information in advance, because he/she cannot experience the relationships or conflicts among the responses. To overcome this limitation, this paper proposes a posterior preference articulation method to the WMSE minimization approach. The proposed method first generates all (or most) of the nondominated solutions without the DM's preference information. Then, the DM selects the best one from the set of nondominated solutions a posteriori. Its advantage is that it provides an opportunity for the DM to understand the tradeoffs in the entire set of nondominated solutions and effectively obtains the most preferred solution suitable for his/her preference structure.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.751-756
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• 2003

Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP) . In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance and we wish to certify that qualitative level of problem solution is excellent.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.335-345
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• 2005

In personalized marketing, it is important to maximize customer satisfaction and marketing efficiency. As personalized campaigns are frequently performed, several campaigns are frequently run simultaneously. The multiple recommendation problem occurs when we perform several personalized campaigns simultaneously. This implies that some customers may be bombarded with a considerable number of campaigns. We raise this issue and formulate the multi-campaign assignment problem to solve the issue. We propose dynamic programming method and various heuristic algorithms for solving the problem. With field data, we also present experimental results to verify the importance of the problem formulation and the effectiveness of the proposed algorithms.

• Korean Journal of Food Science and Technology
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• v.29 no.4
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• pp.752-757
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• 1997

Crude papain extracted at optimum condition was purified with an ethanol precipitation method. Four factors of protein recovery method were optimized by response surface methodology (RSM) and the function was expressed in terms of a quadratic polynomial equation. Adequacy of the model equation for optimum response values was tested and optimum conditions of protein recovery were 38.2 mg/mL of protein, ethanol concentration of 40% and precipitation temperature of $-8^{\circ}C$. The experimental value (68.97%) for recovery yield was closed to the predicted value (77.28%) under these conditions.