• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.83-91
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• 2020

Environmental conditions are known to impact human health and behavior, emotions such as pleasure, anxiety, and depression, and reduce stress. Interior design that elevates emotional comfort and satisfaction can help improve mental health and well-being. This study is a systematic review that analyzed previous empirical studies that explored the effect of interior design elements on the user's emotional response which is quantitatively evaluated by bio-signal and qualitatively evaluated through self-reported questionnaire surveys. This paper aims to derive the attributes of interior design and biometric indicators that affect the user's positive emotion through the synthesis of previous studies and to confirm the feasibility of measuring bio-signals as an objective evaluation tool for architectural design and as a quantitative research method. As a result of the review, the biometric data from EEG, fMRI, ECG, EMG, GSR, and eye-tracking were used to measure the participants' emotional responses, which were manifested as positive or negative depending on certain attributes of interior design such as the form, color, lighting, material and furniture. The attributes of interior design related to the positive emotional response were the curved shape, high ceiling, openness of space, and subdued tone colors. Standard lighting conditions and wooden spaces were related to stress reduction in terms of comfort and relaxation. The free arrangement of furniture was related to the user's positive emotions. On the other hand, consistent experimental protocols could not be found, and although the sample sizes of the studies were small, the studies have demonstrated the feasibility of the emotional response measurement by using the biometric data. Therefore this method can be a useful objective tool in the measurement of human-centric data in architectural design, and to develop the evidence-based design to induce positive emotions and minimize stress.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Journal of the Korean Society of Industry Convergence
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• v.12 no.1
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• pp.35-42
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• 2009

In Taguchi's quadratic expected loss function used as robustness metric of performance characteristics, the mean and variance contributions are confounded. The consolidation of the mean and variance in the expected loss function may not always be the ideal approach. This paper presents a procedure for multi-attributes design optimization, where the mean and variance of performance characteristics are considered as separate attributes having designer's relative preferences for them and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) is introduced to attain robust optimal design. The effectiveness of proposed approach is shown with an example of a weld line minimization problem in the injection molding process.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.111-126
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• 2021

A Kano model was used to classify the quality attributes of the service robot function for actual deployment that can support and replace bank employees. Quality attributes for a total of 6 dimensions and 23 service elements were divided into bank employees and customer groups, and service priorities were derived after comparative analysis. The Decision tree model was used to supplement the excessive simplification of quality attributes by the modest number of Kano models and to classify and predict by segment market. Of the 23 services, 16 were classified into the same attributes in both groups. 6 services classified as combination attributes used a Decision tree to identify differences in perception of quality attributes among groups. In terms of basic financial services and professional financial services, it was confirmed that bank employees feel financial service robots more attractive than ordinary customers. In the design of IT convergence service, we propose a methodology for deriving quality attributes by combining a Kano model for classifying quality attributes of two groups and a Decision tree for forecasting subdivision markets.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.119-125
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• 2011

The part family (PF) formation in a cellular manufacturing has been a key issue for the successful implementation of Group Technology (GT). Basically, a part has two different attributes; i.e., design and manufacturing. The respective similarity in both attributes is often conflicting each other. However, the two attributes should be taken into account appropriately in order for the PF to maximize the benefits of the GT implementation. This paper proposes a clustering algorithm which considers the two attributes simultaneously based on pareto optimal theory. The similarity in each attribute can be represented as two individual objective functions. Then, the resulting two objective functions are properly combined into a pareto fitness function which assigns a single fitness value to each solution based on the two objective functions. A GA is used to find the pareto optimal set of solutions based on the fitness function. A set of hypothetical parts are grouped using the proposed system. The results show that the proposed system is very promising in clustering with multiple objectives.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.67
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• pp.77-82
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• 2001

A study was conducted to develop a better classification method of Consumer Attributes that can enhance user-centered product design process. A modified QFD(Quality Function Deployment) survey form based upon Fuzzy set theory was proposed which contains 9 steps of importance level, and Certainty and Necessity function to improve the reliability of extracted consumer attributes. To verify the betterment and advantage of proposed classification method, a series of questionnaire survey was performed. Thirty male and 30 female university students were participated in the survey using a VCR as a target product. The result of the study showed that 80% of subjects were preferred the proposed classification over existing method. A cluster analysis was performed to further verify the betterment of the proposed method. The result also supported that the proposed classification method is more reliable and enhanced method in extracting consumer attributes and can be applied in the product design.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.2
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• pp.294-306
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• 2015

This study investigated how the travel motivation of Korean overseas tourists influenced shopping behavior. We first identified factors of the travel motivation and then categorized types and attributes of shopping products and shopping stores. We then examined the relationship between the travel motivation and shopping products and shopping channels. A questionnaire method was applied for this survey, while factor analysis and regression analysis were used to analyze data. The results are listed below. First, nature & leisure, rest, family, pleasure, hobby & fitness, and discovery were identified as 6 factors of travel motivation. Second, shopping products of overseas tourists were categorized into three types: fashion & luxury, daily goods, and memento. There were four attributes of products, namely, design, utility, economy, and prestige. Major types of shopping stores were souvenir shops, fashion channels and local markets; the shopping store attributes identified were location & salesperson, assortment & atmosphere, and display. Third, overseas tourists' motivation was shown to influence the selection of product types and attributes. Those who traveled for rest, family, pleasure, hobby & fitness orientation were inclined to purchase fashion & luxury goods, and daily goods; however, those who traveled for rest and hobby & fitness orientation also tended to buy memento. The effect of the travel motivation was shown to be different according to product attributes. Fourth, tourists' motivation was shown to affect store type selection and attributes. Those whose traveled for rest, family, pleasure, hobby & fitness preferred souvenir shops while those seeking nature & leisure and pleasure tended to visit fashion channels and local markets more often. Travelers seeking nature & leisure and discovery cared for all three store attributes while family oriented and pleasure seeking tourists considered shopping store location, salesperson and display attributes as important.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.41-47
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• 2007

Mahalanobis Taguchi-System (MTS) is a pattern information technology, which has been used in different diagnostic ap plications to make quantitative decisions by constructing a multivariate system using data analytic methods without any as sumption regarding statistical distribution. MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric In this work, MTS used for analyzing automotive brake feeling system, which measured as a brake feel index (BFI) from 9 attributes. The automobile which has a good BFI score treated as a normal group for constructing Mahalanobis space. The results of this research show that two attributes (Pre load & Max deceleration) have a minus gain value and can be removed from further analysis. The difference of MD value between using all 9 attributes and just using significant attribute compared.

• Journal of the Korean Society of Costume
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• v.64 no.1
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• pp.77-88
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• 2014

This study examined the cosmetic store attributes that japanese tourists evaluated when purchasing cosmetics in korean cosmetic stores and the effect of those attributes on satisfaction, repurchase intention and recommendation intention. The subjects of this study were 250 Japanese female tourists who had purchase experiences of Korean cosmetics in the stores. Data analysis was conducted using factor analysis, regression analysis, and ANOVA using SPSS 15.0. The result of this study was as follows: First, cosmetic store attributes for Japanese tourists were composed of four factors such as products, store's atmosphere, salesperson and sales promotion. Second, it was shown that the salesperson and store atmosphere attributes have positive effect on cosmetic store satisfaction. Third, it was shown that store satisfaction had a positive effect on both repurchase intention and recommendation intention. Fourth, Japanese tourists' satisfaction on cosmetic store depends on the frequency of visiting Korea, and preference of the Korean Wave.