• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.2
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• pp.14-21
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• 2019

In recent years, the use of composite structures has become commonplace in various fields such as aerospace, architecture, and civil engineering. In this study, A method is proposed to find optimal position of bolt hole for fastening of composite structure. In the case of composites, stress distribution is very complicated, and design optimization based on this phenomenon increases difficulty. In selecting the optimum position of the bolt hole, the response surface method(rsm), which is a method of optimization, was applied. A response surface was created based on design points by multiple finite element analyzes. The position of the bolt hole that minimizes the stress when bolting on the response surface was found. The distribution of the stress at the position of the optimal hole was much lower than that of the initial design. Based on the results of this study, it is possible to increase the design safety factor of the structure by appropriately selecting the position of the bolt hole according to various load types when designing the structure and civil structure.

• Structural Engineering and Mechanics
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• v.86 no.5
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• pp.647-661
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• 2023

It is recognized that the installation of energy dissipation devices, such as the tuned mass damper (TMD), decreases the dynamic response of structures, however, the best parameters of each device persist hard to determine. Unlike many works that perform only a deterministic optimization, this work proposes a complete methodology to minimize the dynamic response of footbridges by optimizing the parameters of multiple tuned mass dampers (MTMD) taking into account uncertainties present in the parameters of the structure and also of the human excitation. For application purposes, a steel footbridge, based on a real structure, is studied. Three different scenarios for the MTMD are simulated. The proposed robust optimization problem is solved via the Circle-Inspired Optimization Algorithm (CIOA), a novel and efficient metaheuristic algorithm recently developed by the authors. The objective function is to minimize the mean maximum vertical displacement of the footbridge, whereas the design variables are the stiffness and damping constants of the MTMD. The results showed the excellent capacity of the proposed methodology, reducing the mean maximum vertical displacement by more than 36% and in a computational time about 9% less than using a classical genetic algorithm. The results obtained by the proposed methodology are also compared with results obtained through traditional TMD design methods, showing again the best performance of the proposed optimization method. Finally, an analysis of the maximum vertical acceleration showed a reduction of more than 91% for the three scenarios, leading the footbridge to acceleration values below the recommended comfort limits. Hence, the proposed methodology could be employed to optimize MTMD, improving the design of footbridges.

• 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.

• 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.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.56-68
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• 1997

The object of multiresponse optimization is to determine conditions on hte independent variables that lead to optimal or nearly optimal values of the response variables. Derringer and Suich (1980) extended Harrington's (1965) procedure by introducing more general transformations of the response into desirability functions. The core of the desirability a, pp.oach condenses a multivariate optimization into a univariate one. But because of the subjective nature of this a, pp.oach, inexperience on the part of the user in assessing a product's desirability value may lead to inaccurate results. To compensate for this defect, a weighted desirability function is introduced which takes into consideration the vriances of the responses.

• 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.

• 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 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.