• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.238-246
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• 1999

The modeling method to support product development processes (PDP) must have certain characteristics including the ability to represent multiple viewpoints of the product development and integrate with currently available analysis and design methods based on CE concept. This paper describes the reference model to support multiple viewpoints (PPO: Products, Processes, and Organizations/Resources viewpoints) of the product development processes, from which each model (Products model, Processes model, and Organizations/Resources model) can be extracted, as well as produces PPO data schema. This reference model has associative relationships among the products, processes, and organizations/resources. To allow the extensibility to support design evolution, we propose structured dat representation methods using semantic network, which can be constructed through first-order logic. The product development processes is so represented by specifying entities and semantic relationships among them hat he appropriate information can be accessed and all of the relevant attributes about the entities can be retrieved simultaneously.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.55-62
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• 2003

This paper deals with the difficulties involved in analyzing and designing a management system to reduce the risks and improve the productivity of new product development. In this paper, a method is described to analyze user information and determine product specifications based on a stimulus-response model, the conjoint measurement of users needs, and product characteristics deployment. The proposed method can analyze the effect of a partial price on the contribution ratio based on the order of preference of product profiles through a smaller number of product profiles. The strengths and weaknesses of this method are examined as the method is applied to the case study of a mobile computer intended for personal use.

• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• The Research Journal of the Costume Culture
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• v.24 no.4
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• pp.417-430
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• 2016

This study had two aims. First, the study intended to identify the influences of product benefits and product identification on consumers' purchase intention, Second, it wanted to assess the moderating effects of consumers' aesthetic seeking tendency on their decision-making process. Based on the stimulus-organism-response (S-O-R) paradigm and the product personality-brand identification-purchase intention model, this study proposed a research model, the benefits-product identification-purchase intention model. To test the model, a survey was conducted of female college students; a total of 298 questionnaires were analyzed. The stimulus used was a popular model of Nike running footwear: the Luna Eclipse+2. Factor analysis and structural equation analysis were conducted to analyze the research model. The results indicate : (1) The aesthetic benefit influenced product identification positively. The aesthetic benefit, functional benefit and product identification were all positively related to purchase intention. (2) The aesthetic seeking tendency mediated the influences of product benefits on consumers' purchase intention in the decision-making process. For consumers in the 'high' level group of aesthetic seeking tendency, aesthetic benefit and social benefit affected purchase intention and for consumers in the 'low' level group of aesthetic seeking tendency, the functional benefit only affected purchase intention. Based on this study, we find evidence that product benefits and aesthetic seeking tendency play important roles in consumers' decision-making process in product purchase.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.556-571
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• 2020

This study predicts consumer preference for social clothing at work, excluding uniforms using the self-product congruence theory that also establishes a model to predict the preference for recommended products that match the consumer's own image. A total of 490 Korean male office workers participated in this study. Participants' self-image and the product images of 20 apparel items were measured using nine adjective semantic scales (namely elegant, stable, sincere, refined, intense, luxury, bold, conspicuous, and polite). A model was then constructed to predict the consumer preferences using a neural network with Python and TensorFlow. The resulting Predict Preference Model using Product Image (PPMPI) was trained using product image and the preference of each product. Current research confirms that product preference can be predicted by the self-image instead of by entering the product image. The prediction accuracy rate of the PPMPI was over 80%. We used 490 items of test data consisting of self-images to predict the consumer preferences for using the PPMPI. The test of the PPMPI showed that the prediction rate differed depending on product attributes. The prediction rate of work apparel with normative images was over 70% and higher than for other forms of apparel.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.50-56
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• 2016

Social media (SM) for expressing thoughts and opinions of people in network communities can support collaboration among stakeholders in business activities. To enhance collaboration for product design, this study integrates SM with a product data management (PDM) system that manages main product development processes and data in manufacturing companies. This study proposes a text messaging SM model that shares core components of PDM systems and uses product structures in PDM systems as networks for SM broadcasting. The SM model is implemented with a research purpose PDM system and applied to product design experiments to show feasibility of the proposed SM model in PDM systems.

• Korean Journal of Computational Design and Engineering
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• v.11 no.1
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• pp.57-66
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• 2006

Modeling product configurations needs large amounts of knowledge about technical and marketing restrictions on the product. Previous attempts to automate product configurations concentrate on representations and management of the knowledge for specific domains in fixed and isolated computing environments. Since the knowledge about product configurations is subject to continuous change and hard to express, these attempts often failed to efficiently manage and exchange the knowledge in collaborative product development. In this paper, XML Topic Map (XTM) is introduced to represent and exchange the knowledge about product configurations in collaborative product development. A product configuration model based on XTM along with its merger and inference facilities enables configuration engineers In collaborative product development to manage and exchange their knowledge efficiently. An implementation of the proposed product configuration model is presented to demonstrate that the proposed approach enables enterprises to exchange the knowledge about product configurations during their collaborative product development.

• Journal of Navigation and Port Research
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• v.27 no.3
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• pp.307-313
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• 2003

Off-line ship chartering is done nearly through the brokers. Because of the international scale of chartering market, brokers spend too much times and costs on searching the most appropriate product which the consumers want. In this research, we propose the on-line Charter Product Categorization Model to search the products efficiently in the Cyber Chartering System. This Model will make concerned parties of the ship chartering to get unified product information efficiently, and the select the most appropriate product. In this research, we classified the ship chartering products into categories of cargo, ship type, and sea routes, and defined mutual relation of each products, and we verified that this classification is necessary to search the products through the product searching experiment.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.89-101
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• 2019

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.4
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• pp.45-57
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• 1992

In this paper, the trends for the standardization of the product model was surveyed, and the product model can be used as concrete means to realize the communication of information between the CAD/CAM softwares, which are used for the design and manufacturing of the complex products such as ships. We have proposed the newly developed methodology for the representation and definition of the ship model on a basis of the product model. And also we have studied the product modeling technology for the aspect of an application, and the object-oriented system technology have been surveyed for the system implementation issues. We would like to verify the consistency and correctness of our proposed representation methodology by using the prototype application model, which is applied to design work of ship compartmentation model. For this purpose we have developed the "OO_COMDEF"(which means the Object-Oriented System for the Compartmentation Definition of ship) program that is applied to the compartmentation model which can be considered as a submodel of the general ship models. The results of research work have been proved that the representation methodology for the ship model based on the product model is an efficient and appropriate scheme for the ship model definitions. Consequently, this methodology can be proposed as a fundamental framework for the development of the shipbuilding CAD/CAM system.