• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.158-166
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• 2014

Apparel design is an economic activity to create values for users over the value chain of a product. In this paper, the contribution of apparel design is defined as the enhancement of users' perceived values by improving users' experience of products. In this context, the value of a product corresponds to compensation for experience or a promise for experience of a product. Experience can be sensory or psychological benefits to users. To evaluate the value of apparel design, the researcher identified and analyzed the apparel design parameters affecting users' experience and benefits of products such as macro-, micro-environmental factors, value chain factors, apparel designer factors, and user factors. For an analytical modeling of the values of apparel design, this paper introduces the concept of a utility function from economics. In economics, utility is a measure of desirability or satisfaction that can be correlative to need or desire. The measure of value can be found in the price which a user is willing to pay for the fulfillment or satisfaction of need or desire via the experience of a product.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.83-87
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• 2002

Many industrial products such as paints, ink and adhesives are composed of the ingredients of a mixture. In mixture experiments, the characteristics of quality(response) depends only on the proportions of the ingredients and does not depend on the total amount of the mixture. This article discusses the constrained mixture experimental design, the data analysis, and the optimum formulation of ingredients based on the two quality characteristics - taste and flavor. It IS shown that efficient designs can be constructed from D-optimal criterion. Special cubic models were selected as the final mixture response surfaces for both reponses. The desirability function was used for the optimization of the two responses.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1392-1400
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• 2006

Since the monolithic ceramic substrate was in introduced for automotive catalytic converters, the durability of the substrate has been a continuing requirement to reduce the emission, gas of vehicle. The substrate can occupy a volume as small as 82 $cm^3$ and as large as 8200 $cm^3$ to provide the required substrate for catalytic activity. The long-term durability varies with the size of the substrate from manufacture's point of view. Therefore this study presents that the response surface model using central composite design can explain size effect on the modulus of rupture in a cordierite ceramic monolithic substrate.

• 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.

• Journal of Food Hygiene and Safety
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• v.10 no.1
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• pp.19-22
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• 1995

Sensory characteristics of various milk samples-low-temperature long-time(LTLT) milk, high-temperature short-time (HTST) milk and ultra-high temperature (UHT) milk-were investigated using chemical analysis and sensory evaluation. The chemical composition was not much different among the milk samples. The results of evaluation of preference for color, flavor, taste and overall desirability of the milk samples by scoring and ranking tests indicated that significant difference on the sensory quality was recognized at 0.01 percent level. UHT milk samples (especially sample F and H) had better sensory acceptability than LTLT milk HTST milk samples.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.43-47
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• 1997

Advances in EDM power supplies have made the process competitive in some areas dominated by conventional and numerically controlled machines. This paper will produce more comprehensive data than are presently available and will use this data in applying concepts of optimization based on manufacturer's guide lines utilizing neural networks. A method will be developed for determining the machining parameters of the EDM process considering the conflicting desirability of good surface finish, low tool wear and high rates of metal removal. By the proposed method, one can select machining parameters that can maintain permissible tool wear and obtain maximum machining rates on the system represented by the data.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.377-390
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• 2011

A common problem encountered in product or process design is the selection of optimal parameter levels which involves simultaneous consideration of multiple response variables. This is called a multiresponse problem. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. Up to date, various methods have been proposed for the optimization, including the desirability function approach and loss function approach. In this paper, the existing studies in multiresponse optimization are reviewed and a future research direction is then proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.42 no.3
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• pp.190-196
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• 2009

To optimize the mixing ratio of ingredients for optimal sensory qualities of seasoned tofu, a response surface methodology with a central composite design was performed on tofu containing freshwater crab meat (TCM). Using the desirability function technique, the optimal formulation was determined to be 3.67 g of freeze dried meat, 5.54 g of garlic powder, and 2,120 mL of soymilk. In the texture profile analysis, tofu prepared using the optimal ingredient ratio had a higher hardness, cohesiveness and gumminess than commercial tofu but TCM value for adhesiveness, springiness and chewiness were lower. However, the texture properties of TCM were not significantly different than those of commercial tofu.

• 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.