• Journal of Microbiology and Biotechnology
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• v.8 no.1
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• pp.81-88
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• 1998

The determination of appropriate parameters and parameter conditions is very important for the optimization of production of target materials. Taguchi's method has been used widely as the basis for development trials and optimization during industrial process design. Reaction variables which influence product yield are easily determined and their effects are revealed by just a few reactions, negating the need for extensive experimental investigation. There are usually some factors that are responsible for variations in process characteristics, so called noise factors. Controlling noise factors is very costly and difficult or impossible. Taguchi's experimental design method was examined to determine the control factor's level that is less sensitive to the changes in environmental conditions and other noise factors without control of noise factors. In this study, optimization of lipase-catalyzed production of lysophosphatidic acid (LPA) which has various physiological functions was performed by Taguchi's method. We obtained LPA yields ($66.5\%$) with low variance (5.32) at 400 RPM, molar ratio of 40 : 3 (mol) (fatty acid: G-3-P), 48 h, and $50^{\circ}C$. Thus, bioactive LPA with a desired fatty acid moiety could be produced with high yields and low variance despite various environmental noise factors.

• 한국데이터정보과학회:학술대회논문집
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• 2003.05a
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• pp.65-75
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• 2003

In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was suggested by Welch et. al. (1990) and studied by others. In these studies, only single response variable was considered. We propose how to simultaneously optimize multiple responses when we use the combined array approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.55
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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.

• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.27-36
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• 2000

The Robust Design method uses a mathematical tool called orthogonal arrays to study a large number of decision variables with a small number of experiments. It also uses a new measure of quality, called signal-to-noise (S/N) ratio, to predict the quality from the customer's perspective. Thus, the most economical product and process design from both manufacturing and customers' viewpoints can be accomplished at the smallest, affordable development cost. Many companies, big and small, high-tech and low-tech, have found the Robust Design method valuable in making high-quality products available to customers at a low competitive price while still maintaining an acceptable profit margin. A study to analyze and solve problems of a biochemical process experiment has presented in this paper. We have taken Taguchi's parameter design approach, specifically orthogonal array, and determined the optimal levels of the selected variables through analysis of the experimental results using S/N ratio.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.367-373
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• 2013

In this article, we deal with a design problem for determining the levels of noise factors in the Taguchi method. First, the proposed levels by Taguchi method is reviewed in case of smaller-the-better performance characteristics. We obtain the optimal levels of noise factors minimizing the mean square error of SN(signal to Noise) ratio and compare the optimal levels with the levels proposed by Taguchi method under the first and second order models. Secondly, the concept of V-optimality is applied to determining the levels of noise factors.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.610-621
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• 1998

In parameter design introduced by Taguchi, we analyze a signal-to-noise(SN) ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing SN ratios is presented, which can be used to several quality characteristics simultaneously in parameter design. To develop such multivariate SN ratios, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Agricultural and Biosystems Engineering
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• v.1 no.1
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• pp.7-15
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• 2000

Optimization was considered from three perspectives : minimum grain loss, minimum damaged grain loss, and minimum power consumption. Factors affecting combine performance were classified as control, adjustable, and environmental. Control and adjustable factors were optimized by the parameter design developed by Taguchi. Environmental factors were used as input for optimization. Optimum range for control and adjustable factors are presented. Parameter design was adequate to obtain the optimum levels of control factors and optimum range of adjustable factors.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.67-78
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• 1999

In parameter design introduced by Taguchi, we analyze a performance measure, so called SN ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing performance measures is presented, which can be used to control several quality characteristics simultaneously in parameter design. To develop such multivariate performance measures, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.714-726
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• 1993

Optimization was considered from three perspectives ; minimum grain loss, minimum damaged grain loss, and minimum power consumption. Factors affecting combine performance were classified as control , adjustable , and environmental. Control and adjustable factors were optimized by the parameter design developed by Tajuchi. Environmental factors were used as input for optimization Optimum range for control and adjustable factors are presented. Parameter design was adequate to obtain the optimum levels of control factors and optimum range of adjustable factors.

• Journal of the Korean Professional Engineers Association
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• v.31 no.6
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• pp.114-123
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• 1998

Qualify Engineering(QE) is purposed for company profits. It is difficult to understand the literature of QE which is published in Korean. In this paper, we want to make easy understanding of the QE and to apply it to real fields. Though that Taguchi has contributed to QE is absolute, QE and Taguchi methods are not the same methods. In this paper, we are trying to show differences of those. QE methods also are developed from the design of experience, the design of parameter and the on-line control of production process. Nowadays, the main subject of QE are to determine control variables and noise variables.