• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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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.

• 품질경영학회지
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• 제26권2호
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• pp.17-26
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• 1998

Taguchi's parameter design is a method for quality improvement by making the performance fo a system robust to noise. Parameter design with dynamic characteristics has been recently the subject of much interest. This paper is concerned with a review and a generalization of the Signal-to-Noise (SN) ratio, a quality measure for parameter design with dynamic characteristics, proposed by Taguchi. We present a method for determination and analysis of the generalized SN ratio and illustrate its implementation by example.

• Journal of the Korean Data and Information Science Society
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• 제12권1호
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• pp.11-18
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• 2001

다구찌가 제안한 파라미터 설계는 제품설계나 공정설계 단계에서 품질특성치의 수행변동(performance variation)을 줄이는데 있다. 파라미터 설계에서 품질평균 근처에서 품질의 변동을 줄일 수 있는 최적조건을 찾는데 있어서 신호대 잡음비(Signal-to-noise ratio; SN비)라는 수행측도(performance measure)를 사용하였다. 그러나 많은 통계학자들은 SN비를 이용한 다구찌 분석 기법을 비판한다. 본 논문에서는 파라미터 설계를 위한 최적조건을 찾는데 있어서 SN비를 사용하지 않는 보다 실질적인 최적방안을 제안한다.

• 통합자연과학논문집
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• 제13권3호
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• pp.92-96
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• 2020

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

• 대한안전경영과학회지
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• 제16권4호
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• pp.397-403
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• 2014

The objective of this study is to provide improved methodology based on the IPA method. One case studies are solved by the proposed method. this study present the method that give value to use SN(Signal-to-Noise) ratio in IPA. A case study of lecture satisfaction are solved by the proposed method and the existing method. Also, the result is compared with the existing method using Mean and the proposed method using SN ratio.

• 대한기계학회논문집
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• 제18권4호
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• pp.1050-1056
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• 1994

When a vibration data for a rotating machine such as a pump or a compressor is concerned, the frequency fluctuation of the energy contents at an instant time may provide useful information on understanding the vibration characteristics of the rotating machinery, rather than the averaged energy distribution along the frequency axis. Especially, when a periodic signal has different spectral contents, the approach to use the averaged frequency distribution, called the normal frequency analysis, may not be appropriate to extract vibration source characteristics of the structure. This paper introduces a way to analyze the signal based on an instant time. In order to evaluate the performance of the various approach, the investigatation compares three different algorithms which are frequently implemented in the instantaneous frequency analysis. Also for the noise effect embodied in the true signal, various cases for different SN ratio have been examined. The result shows that the noise level is crucial to evalute the instantaneous frequency analysis. In order to implement the instantaneous frequency analysis, the extraction of the relevant information from the measured signal should have the high S/N ratio, i, e., 40 dB or above.

• 품질경영학회지
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• 제21권1호
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• pp.96-107
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• 1993

In parameter design Taguchi analyzed a statistic which he called signal-to-noise(SN) ratio by using the experimental design technique. However he gave no justification for using SN ratios in the optimization procedure of parameter design. In this paper we discuss the validity of such SN ratios as proper statistics to be analyzed in parameter design. Moreover, using the real empirical data we examine the appropriateness of SN ratios, and we explain how transformation technique can be applied in parameter design as an alternative method of analysis.

• 품질경영학회지
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• 제22권4호
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• pp.1-12
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• 1994

각각의 설계인자들의 실험조건에서 얻어지는 특성치들의 분산은 평균에 영향을 받는다. 많은 경우에 평균이 커짐에 따라서 분산이 커지는 경향이 있다. 다구찌가 산포제어인자를 찾기 위해서 제시한 SN 비인 $(SN)_i$ = 10 log ($\bar{y}_{i}^{2}/s_{i}^{2}$) 은 분산이 평균의 제곱에 비례하여 커지는 경우이다. 그런데 분산이 평균의 제곱보다 더 느리게 또는 더 빠르게 커질 수도 있기 때문에 이 논문에서는 간단한 자료분석적 기법에 의해서 그 관계를 추측하여, 합당한 SN 비를 사용할 것을 제시하였고, 평균조정인자를 찾기위한 통계량인 감도 $(S)_i$ 의 통계적 성질들을 논의하였다.

• 통합자연과학논문집
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• 제12권3호
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• pp.69-73
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• 2019

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

• 품질경영학회지
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• 제23권2호
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• pp.28-42
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• 1995

For quality improvement, Taguchi emphasizes the reduction of variation of the quality characteristic, Taguchi has used the signal-to-noise ratios for achieving minimum dispersion of the quality characteristic with its location adjusted to some desired target value ${\tau}$ Lim(1994) proposes a reasonable SN ratio based on a linking relationship of the variance and mean through simple data analysis technique. In this paper we investigate the efficiency of those two SN ratios and variance stabilizing transformations through Monte Carlo Simulations.