• 품질경영학회지
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• 제22권1호
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• pp.122-132
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• 1994

So far, the Taguchi Method has dealt with multiple quality characteristics under the assumption that they are independent. Since the relationships between quality characteristics are practically important, this study proposes a new performance measure considering the correlation among characteristics. In this paper, we impose weight on each characteristic and correlation among characteristics. The loss function of multiple characteristics is defined in accordance with combination of simple characteristic types, and it is divided into terms of loss that characteristic itself and the correlation among characteristics cause. And the proposed method uses the expected loss of multiple characteristics as the new performance measure. The data in literature are used to compare with the existing performance measures.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 추계학술대회
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• pp.69-79
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• 2004

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index $MC_{pm}^{++}$ using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other.

• 대한안전경영과학회지
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• 제2권1호
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• pp.161-170
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• 2000

When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in consideration of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics.

• 품질경영학회지
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• 제48권4호
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• pp.535-552
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• 2020

Purpose: The main theme of this study is to derive a specific quality loss function with multiple characteristics according to the same analytical structure as the single characteristic quality loss function of Taguchi. In other words, it presents an analytical framework for measuring quality costs that can be controlled in practice. Methods: This study followed the analytical methodology through geometric, linear algebraic, and statistical approaches Results: The function suggested by this study is as follows; $$L(x_1,x_2,{\cdots},x_t)={\sum\limits_{i=1}^{t}}k_i\{x_i+{\sum\limits_{j=1}^{t}}\({\rho}_{ij}{\frac{d_i}{d_j}}\)x_j\}x_i$$ Conclusion: This paper derived the quality loss function with multiple quality characteristics to expand the usefulness of the Taguchi quality loss function. The function derived in this paper would be more meaningful to estimate quality costs under the practical situation and general structure with multiple quality characteristics than the function by linear algebraic approach in response surface analysis.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.545-551
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 춘계학술대회
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• pp.131-139
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• 2004

Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

• International Journal of Precision Engineering and Manufacturing
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• 제8권4호
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• pp.10-15
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• 2007

Taguchi methods have been used for a long time to improve the product quality and process performance of a manufacturing system, Few researchers have applied this methodology in laser beam cutting (LBC) of sheet metals and found the considerable improvement in cut qualities. In all experimental investigations of LBC so far, the objective was to optimize the single quality characteristic at a time. In this paper the simultaneous optimization of multiple quality characteristics such as Kerf width and material removal rate (MRR) during pulsed Nd:YAG LBC of thin sheet of magnetic material (high Silicon-steel) has been presented using Taguchi's quality loss function. The results show the considerable improvement in multiple S/N ratio as compared to initial cutting condition. Also, the comparison of results from single and multi-objective optimization have been presented and it was found that the loss in quality is always possible shifting from single quality to multiple quality optimization.

• 품질경영학회지
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• 제21권2호
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• pp.71-84
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• 1993

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the vehicle emissions audit procedure and technical innovation constraining the motor vehicle emission. The Korean Environmental Protection Agency currently audits automobiles for emissions compliance at assembly plants with multiple attribute multiple staged sampling plans. In order to establish the more reasonable audit procedure, the multiple staged sampling plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This paper summarizes the auditing procedure and develops methods for determining its statistical characteristics. Specifically, we consider how to evaluate a multiple staged sampling plan, give a procedure that efficiently estimates attribute-type probabilities from multivariate variables-type data, and quantify the effect of tightening the acceptable quality level of the sampling plan. As a result it can be proved that this audit procedure is the reasonable plan minimizing the AQL (Acceptable Quality Level) and is to be used effectively for the auditing procedure constraining the injurious gasses of the motor vehicles.

• 대한산업공학회지
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• 제24권2호
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• pp.287-296
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• 1998

We often have multiple quality characteristics to develop, improve and optimize industrial processes and products. It is not easy to find optimal control factor setting when there are multiple quality characteristics, since there will be conflict among the selected levels of the control factors for each individual quality characteristic. In this paper we propose a desirability function approach and devise a scheme which gives a systematic way of solving multiple quality characteristic problems. A numerical example is provided.

• Fibers and Polymers
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• 제7권4호
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• pp.404-413
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• 2006

This study examines multiple quality optimization of the injection molding for Polyether Ether Ketone (PEEK). It also looks into the dimensional deviation and strength of screws that are reduced and improved for the molding quality, respectively. This study applies the Taguchi method to cut down on the number of experiments and combines grey relational analysis to determine the optimal processing parameters for multiple quality characteristics. The quality characteristics of this experiment are the screws' outer diameter, tensile strength and twisting strength. First, one should determine the processing parameters that may affect the injection molding with the $L_{18}(2^1{\times}3^7)$ orthogonal, including mold temperature, pre-plasticity amount, injection pressure, injection speed, screw speed, packing pressure, packing time and cooling time. Then, the grey relational analysis, whose response table and response graph indicate the optimum processing parameters for multiple quality characteristics, is applied to resolve this drawback. The Taguchi method only takes a single quality characteristic into consideration. Finally, a processing parameter prediction system is established by using the back-propagation neural network. The percentage errors all fall within 2%, between the predicted values and the target values. This reveals that the prediction system established in this study produces excellent results.