• Title/Summary/Keyword: Multiple response surface optimization

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Optimization of HPLC-tandem mass spectrometry for chlortetracycline using response surface analysis

  • Bae, Hyokwan;Jung, Hee-Suk;Jung, Jin-Young
    • Environmental Engineering Research
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    • v.23 no.3
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    • pp.309-315
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    • 2018
  • Chlortetracycline (CTC) is one of the most important compounds in antibiotic production, and its distribution has been widely investigated due to health and ecological concerns. This study presents systematic approach to optimize the high-performance liquid chromatography-tandem mass spectrometry for analyzing CTC in a multiple reaction monitoring mode ($479{\rightarrow}462m/z$). One-factor-at-a-time (OFAT) test with response surface analysis (RSA) was used as optimization strategy. In OFAT tests, the fragmentor voltage, collision energy, and ratio of acetonitrile in the mobile phase were selected as major factors for RSA. The experimental conditions were determined using a composite in cube design (CCD) to maximize the peak area. As a result, the partial cubic model precisely predicted the peak area response with high statistical significance. In the model, the (solvent composition) and (collision $energy^2$) terms were statistically significant at the 0.1 ${\alpha}$-level, while the two-way interactions of the independent variables were negligible. By analyzing the model equation, the optimum conditions were derived as 114.9 V, 15.7 eV, and 70.9% for the fragmentor voltage, collision energy, and solvent composition, respectively. The RSA, coupled with the CCD, offered a comprehensive understanding of the peak area that responds to changes in experimental conditions.

A Study on Simultaneous Optimization of Multiple Response Surfaces (다중 반응표면분석에서의 최적화 문제에 관한 연구)

  • Yoo, Jeong-Bin
    • Journal of Korean Society for Quality Management
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    • v.23 no.3
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    • pp.84-92
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    • 1995
  • A method is proposed for the simultaneous optimization of several response functions that depend on the same set of controllable variables and are adequately represented by a response surface model (polynomial regression model) with the same degree and with constraint that the individual responses have the target values. First, the multiple responses data are checked for linear dependencies among the responses by eigenvalue analysis. Thus a set of responses with no linear functional relationships is used in developing a function that measures the distance estimated responses from the target values. We choose the optimal condition that minimizes this measure. Also, under the different degree of importance two step procedures are proposed.

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Response Surface Approximation for Fatigue Life Prediction and Its Application to Multi-Criteria Optimization With a Priori Preference Information (피로수명예측을 위한 반응표면근사화와 순위선호정보를 가진 다기준최적설계에의 응용)

  • Baek, Seok-Heum;Cho, Seok-Swoo;Joo, Won-Sik
    • 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.

Design of Railway Vehicle Wheel Profile Suitable for Dual-rail Profile (듀얼 레일 형상에 적합한 철도차량의 차륜 형상 설계)

  • Byon, Sung-Kwang;Lee, Dong-Hyeong;Choi, Ha-Young
    • 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.

Optimal Design of Permanent Magnet Linear Synchronous Motor(PMLSM) Considering Multiple Response by Response Surface Methodology(RSM) (영구자석 선형 동기전동기(PMLSM)의 반응표면법(RSM)을 이용한 다중 반응 최적설계)

  • Kim Sung-Il;Nam Hyuk;Kim Young-Kyoun;Hong Jung-Pyo;Cho Han-Ik
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.1097-1099
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    • 2004
  • This paper deals with the optimal design of a slotless type of permanent magnet linear synchronous motor (PMLSM). Response surface methodology, one of the optimization methods, is used to consider multiple response of the PMLSM. That is, it is applied to obtain more average thrust and less thrust ripple than prototype PMLSM. To analyze quickly, characteristic analysis of the PMLSM is performed by space harmonic method and final results of optimized PMLSM are compare with those of prototype PMLSM through finite element analysis.

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A literature review on RSM-based robust parameter design (RPD): Experimental design, estimation modeling, and optimization methods (반응표면법기반 강건파라미터설계에 대한 문헌연구: 실험설계, 추정 모형, 최적화 방법)

  • Le, Tuan-Ho;Shin, Sangmun
    • Journal of Korean Society for Quality Management
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    • v.46 no.1
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    • pp.39-74
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    • 2018
  • Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

Optimization of Physical Conditions for Caviar Analog Preparation Using Calcium-alginate Gel Capsules

  • Ji, Cheong-Il;Cho, Sueng-Mock;Yun, Young-Soo;Kim, Seon-Bong
    • 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.

Mixture response surface methodology for improving the current operating condition (현재의 공정조건을 향상시키기 위한 혼합물 반응표면 방법론)

  • Lim, Yong-B.
    • Journal of Korean Society for Quality Management
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    • v.38 no.3
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    • pp.413-424
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    • 2010
  • Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

Response Surface Approximation for Fatigue Life Prediction and Its Application to Compromise Decision Support Problem (피로수명예측을 위한 반응표면근사화와 절충의사결정문제의 응용)

  • Baek, Seok-Heum;Cho, Seok-Swoo;Jang, Deuk-Yul;Joo, Won-Sik
    • 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.

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A Case Study on the Optimum Formulation of Coffee by a Mixture Experiment Design (혼합물실험계획에 의한 커피혼합비율 최적화에 대한 연구)

  • Lee, Jong-Seong;Moon, Je-Woong
    • 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.

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