• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.450-453
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• 1997

There are many studies about optimization using genetic algorithm and desirability function. It's very important to find the optimal value of something like response surface or regression model. In this study I ind~cate the problem using the old type desirability function, and suggest the new type desirabhty functton that can fix the problem better, and simulate the model. Then I'll suggest the form of desirability function to find the optimum value of response surfaces which are made by mean and standard deviation using genetic algorithm and new type desirability function.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2009년도 추계학술대회
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• pp.565-572
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• 2009

This paper presents the optimization steps with weight and importance of estimated characteristic values in the multiresponse surface analysis(MRA). The research introduces the shape parameter of individual desirability function for relaxation and tighening of specification bounds. The study also proposes the combinded desirability function using arithmetic, geometric and harmonic means considering the measurement unit and numerical pattern.

• 한국기계가공학회지
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• 제19권9호
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• pp.1-8
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• 2020

In this study, the optimal design of the multi-cavity mold layout and packing pressure for the automobile TCU connector cover is determined based on the injection molding analysis and the desirability function method for multi-characteristic optimization. The design characteristics to be optimized are the warpage and sink marks of the product, the scrap of the feed system, and the clamping force. The optimal design is determined by performing injection molding analysis and desirability analysis for design alternatives defined by a complete combination of five mold layouts and six-level packing pressure. The optimal design shows that the desirability values for individual characteristics are quite high and balanced, and the resulting values of individual characteristics are satisfactorily low.

• 한국경영과학회지
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• 제30권1호
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• pp.95-104
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• 2005

A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation which may amplify the variance of response. It is called POE (propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameter setting, a new desirability function is proposed by considering POE as well as distance-to-target of response and response variance. The proposed method is illustrated using a rubber product case in Ribeiro et al. (2000).

• 품질경영학회지
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• 제43권3호
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• pp.341-358
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• 2015

Purpose: This paper presents graphic methods and desirability function approach to determine best vibration reducing configuration for Surion helicopter. Many flight tests were executed and nine vibration levels in cockpit, cabin, and engine room were measured in each test and analyzed to find optimal configuration. Methods: Graphic analysis methods such as matrix, scatter, and box plots are used to identify better vibration-reducing flight test conditions. As an integrated measure of the performance of 9 vibration levels desirability function approach is adopted. Results: Three vibration reducing configurations are found to be proper and one configuration is recommended. Conclusion: It is expected to be helpful to adopt graphic and desirability function methods presented in this paper in developing new products or systems like helicopters. For efficient and effective flight testing of helicopters, it will be necessary to have consistently homogeneous environment for flight testing and applying design of experiments techniques and analyzing test data.

• International Journal of Quality Innovation
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• 제7권3호
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• pp.46-57
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• 2006

The desirability function approach to multiple response optimization is a useful technique for the analysis of experiments in which several responses are optimized simultaneously. But the existing methods have some defects, and have to be modified to some extent. This paper proposes a new method to combine the individual desirabilities.

• 설비공학논문집
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• 제17권6호
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• pp.587-595
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• 2005

The heat and flow characteristics in a parallel-flow heat exchanger were examined numerically to obtain its optimal design variables. A desirability function approach was introduced to optimize its performance with respect to the design parameters over the design domain. By varying the importance of heat transfer and pressure drop which are out put variables, the optimal values of the design parameters are examined. As a result, the us-age of the desirability function is very effective for the optimization of the design variables in a heat exchanger since the changes of optimal values are physically appropriate by varying the importance of each output variable.

• 품질경영학회지
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• 제25권1호
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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.

• 산업경영시스템학회지
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• 제33권1호
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• pp.1-9
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• 2010

Quality design methodologies have received constituent attention from a number of researchers and practitioners for more than twenty years. Specially, the quality design for drug products must be carefully considered because of the hazards involved in the pharmaceutical industry. Conventional pharmaceutical formulation design problems with mixture experiments have been typically studied under the assumption of an unconstrained experimental region with a single quality characteristic. However, real-world pharmaceutical industrial situations have many physical limitations. We are often faced with multiple quality characteristics with constrained experimental regions. ln order to address these issues, the main objective of this paper is to propose a robust desirability function (RDF) model using a desirability function (DF) and mean square error (MSE) to simultaneously consider a number of multiple quality characteristics. This paper then present L-pseudocomponents and U-pseudocomponents to handle physical constraints. Finally, a numerical example shows that the proposed RDF can efficiently be applied to a pharmaceutical process design.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.183-188
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• 2005

Although it is widely used to find an optimum setting of manufacturing process parameters in a variety of engineering fields, the Taguchi method has a difficulty in dealing with multi-response situations in which several response variables should be considered at the same time. For example, electrode wear, surface roughness, and material removal rate are important process response variables in an electrical discharge machining (EDM) process. A simultaneous optimization should be accomplished. Many researches from various disciplines have been conducted for such multi-response optimizations. One of them is a fuzzy logic approach presented by Lin et al. [1]. They showed that two response characteristics are converted into a single performance index based upon fuzzy logic. However, it is pointed out that information regarding relative importance of response variables is not considered in that method. In order to overcome this problem, a desirability function can be adopted, which frequently appears in the statistical literature. In this paper, we propose a novel approach for the multi-response optimization by incorporating fuzzy logic into desirability function. The present method is illustrated by an EDM data of Lin and Lin [2].