• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.51-57
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• 2017

The Taguchi parameter design in industry is an approach to reducing performance variation of quality characteristic in products and processes. In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. It often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was studied. In these studies, only single response was considered. In this paper we propose how to simultaneously optimize multiresponse for the robust design using the combined array approach.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.685-696
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• 2001

Robust design is an approach to reducing performance variation of response values in products and processes. In the Taguchl 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 there are correlations among responses, and when we use the combined-array approach to assign control and noise factors. An example is illustrated to show the difference between the Taguchi's product-array approach and the combined-array approach.

• 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 Korean Society for Quality Management
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• v.24 no.2
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• pp.142-157
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• 1996

Robust design in industry is an approach to reducing performance variation of quality characteristic values in products and processes. In the Taguchi type robust design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. In this paper, for the combined array approach to assign control and noise factors, we propose how to simultaneously optimize multiple quality characteristics. Two examples are illustrated to show the difference between the product-array approach and the combined-array approach.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.126-142
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• 1999

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. Taguchi parameter design has a great deal of advantages but it also has some disadvantages. The various research efforts aimed at developing alternative methods. 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 quality characteristic was considered. In this paper we propose how to simultaneously optimize multiple quality characteristics using desirability function when we used the combined-array approach to assign control and noise factors. An example is illustrated to show the difference between the Taguchi's product-array approach and the combined-array approach.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.65-72
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• 2000

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi parameter design has a great deal of advantages but it also has some disadvantages. The various research efforts aimed at developing alternative methods. 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 this paper we make a comparative study on optimization procedures to robust design in the two different experimental design(product array, combined array) approaches the Mough the Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.325-335
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to to changes in the noise factors that represent the source of variation. 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.

• 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.

• 한국데이터정보과학회:학술대회논문집
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• 2002.06a
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• pp.97-106
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• 2002

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. and studied by others. In these studies, only single quality characteristic was considered. We propose how to simultaneously optimize multiple quality characteristics using desirability function when we used the combined-array approach to assign control and noise factors. An example is illustrated to the combined-array approach.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.204-216
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• 1999

Failure physics and statistical lifetime analysis constitute the two extreme ends of the reliability engineering spectrum, and studies that relate failure mechanisms to failure distributions have been near non-existent. This paper is an attempt to stimulate interest to fill the gap between the two extremes and proposes an approach of combining them through i) developing a failure mechanism model, ii) generating failure times by Monte Carlo simulation with the model, iii) deriving the failure time distribution and evaluating the product reliability, and iv) improving the product reliability by the sensitivity analysis. An application of the proposed approach to the BGA(Ball Grid Array) surface mount package is also provided.