• 한국CDE학회논문집
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• 제4권4호
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• pp.285-294
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• 1999

This paper presents a content-search system built on distributed environments using the open product model of STEP, The content-search system searches design data for given product descriptions such as part name and features. Distribute object interfaces has been defined by IDL and distributed product data are searched through CORBA protocols. Web interfaces are also provided for interactive user interfaces. Given a user request, a mediator interacts with distributed search servers and sends collected results back to the user. The mediator has such metadata as location, program name, and other information about product data stored on distributed system. The search servers use SDAI interfaces to search STEP files or databases. The content-search system promotes the reuse of previous design within a company and the outsourcing of part designs.

• Journal of Information Technology Applications and Management
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• 제26권6호
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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.

• 산업경영시스템학회지
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• 제39권3호
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• pp.139-146
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• 2016

This study proposes a methodology to analyse social networks among participating design engineers during product development projects. The proposed methodology enables product development managers or the participating design engineers to make a proper decision on product development considering the performance of participating design engineers. It considers a product development environment where an integrated product data management (PDM) system manages the product development data and associated product development processes consistently in its database, and all the design engineers share the product development data in the PDM database for their activities in the product development project. It provides a novel approach to build social networks among design engineers from an operational product development data in the PDM database without surveys or monitoring participating engineers. It automatically generates social networks among the design engineers from the product data and relationships specified by the participants during the design activities. It allows analysts to gather operational data for their analysis without additional efforts for understanding complex and unstructured product development processes. This study also provides a set of measures to evaluate the social networks. It will show the role and efficiency of each design engineers in the social network. To show the feasibility of the approach, it suggests an architecture of social network analysis (SNA) system and implemented it with a research-purpose PDM system and R, a statistical software system. A product configuration management process with synthetical example data is applied to the SNA system and it shows that the approach enables analysts to evaluate current position of design engineers in their social networks.

• 한국컴퓨터그래픽스학회논문지
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• 제2권2호
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• pp.69-74
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• 1996

최근 점점 통합되는 세계시장과 증가하는 경쟁에서 살아남기 위해 시간과 공간의 제약을 받지 않고 제품정보를 공유할 수 있는 기술의 확보가 요구되고 있다. 제품정보의 공유를 위한 방안으로 제품정보를 중립형태의 표준으로 표현해 네트워크를 통해 전송하는 방법이 있다. 본 논문에서는 인터넷상에서 STEP 물리적 파일의 3차원 형상정보를 가시화하는 방법을 소개한다. 제품정보의 국제표준으로 새롭게 제시되는 STEP에서 형상정보가 어떻게 표현되는지 알아보고, 인터넷 환경에서의 프로그래밍 언어인 자바와 3차원 데이터 포맷인 VRML을 이용하여 형상정보를 가시화한 후 각각의 장단점을 파악하여, STEP 모델 가시화 기술을 자동차 PDM에 적용해 본다.

• International Journal of CAD/CAM
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• 제7권1호
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• pp.1-10
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• 2007

The compression of CAD models is a key technology for realizing Internet-based collaborative product development because big model sizes often prohibit us to achieve a rapid product information transmission. Although there exist some algorithms for compressing discrete CAD models, original precise CAD models are focused on in this paper. Here, the characteristics of hierarchical structures in CAD models and the distribution of their redundant data are exploited for developing a novel data encoding method. In the method, different encoding rules are applied to different types of data. Geometric data is a major concern for reducing model sizes. For geometric data, the control points of B-spline curves and surfaces are compressed with the second-order predictions in a local coordinate system. Based on analysis to the distortion induced by quantization, an efficient method for computation of the distortion is provided. The results indicate that the data size of CAD models can be decreased efficiently after compressed with the proposed method.

• 한국의류학회지
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• 제44권3호
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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 Information Technology Applications and Management
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• 제30권2호
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• pp.1-18
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• 2023

Recently, as technology development has accelerated and product life cycles have been shortened, it is necessary to derive key product features from customers in the R&D planning and evaluation stage. More companies want differentiated competitiveness by providing consumer-tailored products based on big data and artificial intelligence technology. To achieve this, the need to correctly grasp the required quality, which is a requirement of consumers, is increasing. However, the existing methods are centered on suppliers or domain experts, so there is a gap from the actual perspective of consumers. In other words, product attributes were defined by suppliers or field experts, but this may not consider consumers' actual perspective. Accordingly, the demand for deriving the product's main attributes through reviews containing consumers' perspectives has recently increased. Therefore, we propose a review data analysis-based required quality methodology containing customer requirements. Specifically, a pre-training language model with a good understanding of Korean reviews was established, consumer intent was correctly identified, and key contents were extracted from the review through a combination of KeyBERT and topic modeling to derive the required quality for each product. RevBERT, a Korean review domain-specific pre-training language model, was established through further pre-training. By comparing the existing pre-training language model KcBERT, we confirmed that RevBERT had a deeper understanding of customer reviews. In addition, all processes other than that of selecting the required quality were linked to the automation process, resulting in the automation of deriving the required quality based on data.

• 한국전자거래학회지
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• 제11권3호
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• pp.53-71
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• 2006

오늘날의 제품개발환경은 다양한 역량을 가진 참여자들의 가상조직 구성을 통한 협업을 요구하고 있으며, 참여자들 사이의 협업은 제품 개발 관련 정보들의 교환을 바탕으로 이루어진다. 제품정보의 효율적인 교환을 지원하기 위하여 본 논문에서는 제품정보에 대한 시맨틱스를 기반으로 가상조직 내 모든 애플리케이션 도메인들이 서로의 제품정보모델을 이해하고 이를 바탕으로 제품정보모델 사이의 상호운용성을 확보할 수 있도록 참조 온톨로지인 Reference Domain Ontology(RDO)를 제안하고 이를 이용한 방법론을 제시한다. RDO는 가상조직에 참여하는 모든 애플리케이션 도메인의 제품정보모델과 메타모델에 대한 시맨틱스를 포함함으로써 협업에서 발생 가능한 제품정보모델 교환의 지연요소를 제거한다. RDO는 가상조직이 형성될 때 생성되며 가상조직의 변화에 능동적으로 대응하고 가상조직이 소멸되면 함께 사라지는 등 민첩하고 일시적인 특성을 지닌다. 이를 위하여 RDO는 상위 온톨로지를 이용한 top-down과 가상 조직 내 애플리케이션 도메인 온톨로지의 병합을 기반으로 하는 bottom-up의 복합적 접근법으로 구축된다.

• 한국항만학회지
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• 제14권1호
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• pp.77-86
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• 2000

The planning process of complex projects in oceanic architectural engineering is characterized by the cooperation of many involved specialists and by a high degree of information exchange. In order to improve the quality of the structural design of oceanic buildings, information of different involved partners in the planning process has to be integrated. This paper aims to introduce a concept of the integrated structural design for the floating-type oceanic building using STEP(Standard for the Exchange of Product Model Data). STEP(ISO 10303) is an international standard for the computer-interpretable representation and exchange of product data and it provides a consistent data exchange format and application interfaces between different application systems. In this paper, the structural design process and information of oceanic buildings is analyzed and product models are preposed fir the exchange of the structural design information between superstructure and floating structure. The entities for calculating wind loads, metacenter and restoring forces are represented by Express. As a case study a floating hotel is applicated to describe the STEP physical file.

• 산업공학
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• 제24권1호
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• pp.58-70
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• 2011

As more individuals and organizations participate in the complex design process of manufacturing industry, collaborative product development and management of the global supply chain have become more popular. Although the product quality concerns once focused on the manufacturing process, they are now directed at earlier stages of the design cycle where the engineering product is created as a 3D CAD model. In this paper, we describe the current state of product data quality activities in the manufacturing industry and the yardstick to measure 3D CAD data quality. Moreover we introduce a quality assurance method through the result of statistical analysis of 3D CAD models and suggest a six sigma level of CAD data quality by analyzing 76 samples provided from three Korean automotive companies.