• Journal of Korean Society for Quality Management
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• v.26 no.2
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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 Korean Society for Quality Management
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• v.29 no.4
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• pp.82-91
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• 2001

Taguchi robust design is widely used to quality improve methods. Especially, interest of dynamic characteristics parameter design is getting grow. In this paper, we have a comparative analyzed three Signal-to-Noise Ratios which are used in American Supplier Institute(ASI), MINITAB and Taguchi series published by Japanese Standard Institute with numerical examples.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.180-185
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• 1988

This paper considers the problem of the optimal input design for parameter estimtion in the ARMAX model in which the system and noise transfer function have the common denominator polynomial. Deriving the information matrix, in detail, for the assumed model structure and using the autocorrelation functin of the filtered input as design variables, it is shown that D-optimal input signal can be realized as an autoregressive moving average process. Computer simulations are carried out to show the standard-deviation reduction in the parameter estimtes using the optimal input signal.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.11-18
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• 2001

Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used signal-to-noise(SN) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many statisticians criticize the Taguchi techniques of analysis, particularly those based on SN ratio. In this paper we propose a substantially simpler optimization procedure for parameter design without resorting to SN ratio.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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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.

• Journal of Integrative Natural Science
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• v.13 no.3
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.243-254
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• 1996

In this study, a model and an analysis method for parameter design is presented a linear relation between the input signal and the ideal value of a performance characteristic. Furthermore, There presented a new performance measure, expected quality loss after adjustment, which is proved to be equivalent to Taguchi's SN ratio approximately. On the basis of this, a two-step optimization procedure is proposed for parameter design considering the signal factor and the quality characteristics with continuous variable. Proposed procedure and Taguchi two-stage procedure are compared.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1263-1272
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• 2016

Product array approach which is used in the Taguchi parameter design has a number of advantages by considering the noise factor. However, a disadvantage of this method is that it requires an excessively large number of experiments. So combined array approach have been proposed to reduce the number of experiments. Taguchi has used the signal-to-noise ratio to find the optimum conditions in the Taguchi parameter design. In analyzing the data from the parameter design various problems tends occur by using an SN. In this paper, we propose an alternative solution for reducing the number of experiments without depending on the signal-to-noise ratio to overcome the shortcomings of the parameter design. Two examples illustrate this procedure in the two different experimental design (product array, combined array) approaches.

• Journal of Integrative Natural Science
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• v.12 no.3
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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.