• Tribology and Lubricants
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• v.23 no.3
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• pp.103-108
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• 2007

In this paper, the optimized design and strength analysis have been presented based on the finite element and Taguchi's experimental methods. The stress, strain and displacement characteristics of OPC drum tubes are affected by rolling contact pressures between an OPC drum tube and a paper, design parameters of an aluminum tube and material properties. The OPC drum tubes with nine different geometrical models are analyzed for design parameters that are related to the outer diameter, the thickness, and the length of an aluminum tube for a toner cartridge. The optimized design parameters for an aluminum tube may be selected as the outer diameter of 28 mm, the thickness of 0.8 mm, and the length of 220 mm. But the currently used aluminum tube for a laser printer is fairly optimized based on the Taguchi's design analysis. The calculated FEM results showed that the affection ratio of the design parameter t, which may control the strength of an aluminum tube, is the most influential parameter among the length and an outer diameter of a tube.

• Tribology and Lubricants
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• v.20 no.5
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• pp.259-265
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• 2004

The sealing performance of O-rings is affected by working conditions such as applied pressure, operation temperature, pre-compressed ratio and material properties. In this paper, a pressurized and compressed elastomeric bi-polymer O-ring in which is inserted into a rectangular groove is analyzed by non-linear MARC finite element program based on the Taguchi experimental method. O-rings with 9 different profile models are analyzed for design parameters that are related to the diameter ratio between outer diameter and inner one of bi-polymer O-ring, compressive ratio, groove angle and groove depth. The calculated FEM results showed that the affection ratio of design parameter dlD, which may control sealing pressure of O-rings, is the most influential parameter among the groove angle, groove depth and compression ratio.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.253-263
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• 1995

In parameter design, Taguchi's stated objective is to find the setting of product or process design parameters that minimize average quadratic loss-that is, the average squared deviation of the response from its target value. Yet in practice to choose the settings of design parameters he maximizeds a set of measures called signal-to-noise(SN) ratios. In general, Taguchi gave no justification for the use the SN ratios and no explanation of why the two-step procedure that he recommened will minimize average loss. The purpose of this study is comparing and analyzing of performance statistics by Leon et al(PerMIA), Box(Transformation theory), Vining & Myers(Dual Response Systems) and Taguchi(Signal-to-Noise ratios).

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.211-218
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• 2010

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. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. Moreover, there are difficulties in practical application, such as complexity and nonlinear relationships among quality characteristics and design (control) factors, and interactions occurred among control factors. Neural networks have a learning capability and model free characteristics. There characteristics support neural networks as a competitive tool in processing multivariable input-output implementation. In this paper we propose a substantially simpler optimization procedure for parameter design using neural network without resorting to SN. An example is illustrated to compare the difference between the Taguchi method and neural network method.

• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.265-273
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• 2000

A study to analyze and solve problems of polyacetal resin cutting 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/H ratio.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.57-64
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• 2001

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 Vining and Myers (1990) and others. In these studies, only single respouse variable was considered. We propose how to simultaneously optimize multiple responses when there are correlations among responses.

• Journal of the Korea Safety Management & Science
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• v.5 no.1
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• pp.103-113
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• 2003

A study to analyze and solve problems of a stone surface 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.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.103-117
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• 1996

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 Vining and Myers(1990), Box and Jones (1992) and others. In these studies, only single response variable was considered. We propose how to simultaneously optimize multiple responses when there are correlations among responses, and when we use the combined-array approach to assign control and noise factors.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.47-53
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• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• Journal of the Semiconductor & Display Technology
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• v.16 no.2
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• pp.79-84
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• 2017

This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining STS304 with TiAlN coated SKH59 tool under up and down end milling conditions. The end milling parameters evaluated are depth of cut, spindle speed and feed rate. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to analyze the effect of these end milling parameters. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. An orthogonal array of $L_9(33)$ was used. The most important input parameter for cutting force, however, is the feed rate, and depending on the cutter rotation direction. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.