• International Journal of Aeronautical and Space Sciences
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• 제16권2호
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• pp.137-147
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• 2015

Hypersonic vehicles exhibit distinct dynamic and static characteristics, such as unstable dynamics, strict altitude angle limitation, large control bandwidth, and unconventional system sensitivity. In this study, compromise relations between the dynamic features and static performances for hypersonic vehicles are investigated. A compromise optimal design for hypersonic vehicles is discussed. A parametric model for analyzing the dynamic and static characteristics is established, and then the optimal performance indices are provided according to the different design goals. A compromise optimization method to balance the dynamic and static characteristics is also discussed. The feasibility of this method for hypersonic vehicles is demonstrated.

• 한국시뮬레이션학회논문지
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• 제14권3호
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• pp.43-54
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• 2005

For the effective design of automated distribution center composed of Automated Storage/Retrieval System, Automated Guided Vehicle System, and Conveyor System, we proposed an analysis method to determining. design and control parameters with multiple performance objectives using Compromise Programming, which can resolve the dilemma of conflicting objectives. The Evolution Strategy generates the optimal solutions for each objectives. The Analytic Hierarchy Process selects the best solution among the alternatives generated from Evolution Strategy. The Regression Analysis formulates the objective functions for each objectives. By reducing deviations between goal values and target values generated from Analytic Hierarchy Process, Compromise Programming determines design and control parameters by compromising the multiple objectives formulated using Regression Analysis. When the parameters of system are changed, this proposed analysis method has a benefit of reducing costs and time without repeating whole simulation run.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• 품질경영학회지
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• 제29권3호
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• pp.49-65
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• 2001

This paper presents new compromise ALT plan which is applied to situations that true relationship between stress and parameters is not known exactly. The assumed failure distribution of this study is one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. The method of applying the stress is constant, and the censoring mechanism is Type I censoring. Compared with existing compromise plans under true simple linear model in terms of statistical efficiency, the efficiency of new compromise plan is better than the corresponding other compromise ones in most cases. For case when true model is quadratic, this plan can be used without any severe loss in statistical efficiency. The proposed new compromise ALT plan is illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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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.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.62-72
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• 1999

Taguchi´s parameter design is to determine the optimal settings of design parameters of a product or a process such that the characteristics of a product exhibit small variabilities around their targer values. His analysis of the problem has focused only on a single characteristic or response. However the quality of most products is seldom defined by a characteristic, and is rather the composite of a great number of characteristics which are often interrelated and nearly always measured in a variety of units. The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by unvariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. One existing case study is solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, the desirability functions, and EXTOPSIS model.

• 대한기계학회논문집A
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• 제33권2호
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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.

• 대한산업공학회지
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• 제38권3호
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• pp.198-207
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• 2012

In product or process parameter design, the case of multiple performance characteristics appears more commonly than that of a single characteristic. Numerous methods have been developed to deal with such multi-characteristic parameter design (MCPD) problems. Among these, this paper considers three representative methods, which are respectively based on the desirability function (DF), grey relational analysis (GRA), and principal component analysis (PCA). These three methods are then used to solve the MCPD problems in ten case studies reported in the literature. The performance of each method is evaluated for various combinations of its algorithmic parameters and alternatives. Relative performances of the three methods are then compared in terms of the significance of a design parameter and the overall performance value corresponding to the compromise optimal design condition identified by each method. Although no method is significantly inferior to others for the data sets considered, the GRA-based and PCA-based methods perform slightly better than the DF-based method. Besides, for the PCA-based method, the compromise optimal design condition depends much on which alternative is adopted while, for the GRA-based method, it is almost independent of the algorithmic parameter, and therefore, the difficulty involved in selecting an appropriate algorithmic parameter value can be alleviated.

• 품질경영학회지
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• 제24권3호
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• pp.111-132
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• 1996

Taguchi's parameter design is to determine optimal settings of design parameters of a product or a process such that the characteristics of a product exhibit small variabilities around their target values. His analysis of the problem has focused only on a single characteristic or response, but the quality of most products is seldom defined by a characteristic, and is rather the composite of a great number of characteristics which are often interrelated and nearly always measured in a variety of units. The critical problem in dealing with multiple characteristics is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, the EXTOPSIS Model using SN ratio which can be optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Two existing case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, and the desirability function.

• 산업경영시스템학회지
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• 제23권55호
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• pp.1-11
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• 2000

Taguchi's robust design methodology has focus only a single characteristic or response, but the quality of most products is seldom defined by a characteristics, and is rather the composite of a family of characteristics which are often interrelated and nearly always measured in a variety of units. The multiple characteristics problem is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Also, We propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision.