• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.45-53
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• 2003

This paper addresses the issues related to the development of product model and applications fer nuclear power plants based on STEP and PLIB standards. The ISO standards which can be applied are; STEP(Standard for the Exchange of Product Model Data) AP(application protocol) 221/231, AP 230/225, AP 227, ISO 13584 PLIB, ISO 15926 RDL. The data models of the AP's and ISO 15926 RDL are reviewed and an application system is proposed to exchange and share the design data of the nuclear power plant.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.44-52
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• 1997

A design process is difficult to describe comprehensively because a design problem has a multi-disciplinary nature and the design itself evolves as solutions are attempted by the designer. The process of design has been investigated in this paper with the purpose of characterizing the role that a system of this kind may have. In defining the system, an approach has been used that privileges the relationships with the existing CAD tools based on data exchange standards in course of definition today. Integrated design environment normally consists of a centralized data model a data management system and a set of CAD tools. In this study, all further investigations are directed towards the data management system, as one of the main components of the proposed environment. Moreover, product modeling, as a prerequisite for the data management core, is taken into special consideration.

• IE interfaces
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• v.21 no.1
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• pp.18-32
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• 2008

In recent, a general trend is observed towards more customized products and shorter product life cycles in manufacturing companies. In these companies, customers often wish to influence the product they order and to get a variant of product that meets their requirements. This environment is called as a customer-oriented manufacturing companies. This paper presents a procedure of product specification management for customer-oriented manufacturing companies by using product specification framework. This framework is founded on the product specification based product structure which is made of model, specification, function, and part. Also, a product specification management system(PSMS) is implemented by using the proposed product specification framework and is a core system in product data integration system. To illustrate an utilization of the proposed framework and procedure, a case of a ship engine product is applied. As a result, PSMS reduces delivery time and improves customer relationships. Moreover, the case shows that PSMS can be used as a tool for improving inter-department coordination within a company during product life cycle.

• Information Systems Review
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• v.7 no.2
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• pp.117-128
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• 2005

This study proposes an integrated monitoring system for data reliability improvement in a steel manufacturing industry. The data obtained from existing steel manufacturing process is not micro data which is gathered at the occurring point, but average value (macro data) which is gathered from the occurring point to ending point. This kind of macro data is not only difficult for a detailed analysis for an error causing factor, but it might cause a fatal influence as well on the quality of produced goods even if the error is within an error tolerance. And during the process of steel production, thousands of data is produced in a second, thus requiring database plan to manage abundant amount of data. Therefore, the following proposed system is capable of collecting as well as analyzing all the data generated from the process of product production. And the system was able to raise the efficiency of the database server by planning the database to handle large capacity data. Also, by applying web-based technology, inquiries and analysis of data with no limit on time and space was possible with PC connected to the intranet. Hence, the system was able to work on effective quality improvement of manufactured products, plus able to raise the reliability of the product. Also, accumulated data from long period of time was used for fundamental material for new controlling model, operation technology, and new product development.

• Industry Promotion Research
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• v.2 no.1
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• pp.1-7
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• 2017

In the case of manufacturing companies, various types of data are collected. Many of these data can be used as useful information for product reliability evaluation. In this study, we first look at data that can be collected by a manufacturing company and related to products, technology, finance, and customers. Next, we will look at the company's business management system, scientific journals, test and marketing survey data, etc., as sources of data. Next, look at what kind of data is collected over the product life cycle to evaluate the reliability of the product. In the development stage of the product, reliability test is performed for each component, and reliability data is collected by performing reliability test at the subsystem and system level. On the other hand, at the manufacturing stage, data on the functional test and the design change test of the product are collected, and at the field stage, the problem of the product is detected in the field and collected in the form of data. Finally, let's look at what you need to do to make a reasonable analysis later in your data collection.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.107-126
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• 2021

In e-commerce, rapid and accurate automatic product classification according to product information is important. Recent developments in deep learning technology have been actively applied to automatic product classification. In order to develop a deep learning model with good performance, the quality of training data and data preprocessing suitable for the model are crucial. In this study, when categories are inferred based on text product data using a deep learning model, both effects of the data preprocessing and of the selection of training data are extensively compared and analyzed. We employ our CNN model as an example of deep learning model. In the experimental analysis, we use a real e-commerce data to ensure the verification of the study results. The empirical analysis and results shown in this study may be meaningful as a reference study for improving performance when developing a deep learning product classification model.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.2
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• pp.315-326
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• 2001

This study is to suggest data for setting school uniform size with the size satisfaction degree through finding out the physical body change and uniform size problems following an increase in age during middle school girl days. For this purpose, by analyzing the physical body size data of 13~15 age of girls among $\ulcorner$human body size data of the youth for product design$\lrcorner$publicized under sponsorship of National Technology Quality Institute in 1999 the physical body size change by part following an increase in age during middle school girl days was found out and the most frequent physical body size by grade was suggested. Questionnaire about uniform production status and product size at the object of uniform makers were measured directly, a school uniform wearing status and size satisfaction degree by part were at the abject of middle school girls were examined by means of questionnaire and unsatisfactory factors in uniform size were found out. Based on collected data the most optimum product size in each part by item were suggested. The method of suggesting the most optimum size suitability by item was decided based on the result of survey into corresponding title and product size by maker and that of survey into the size satisfaction degree of middle school girls by maker, and the product size of maker showing the highest size satisfaction degree was selected as the most optimum product size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2194-2210
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• 2018

In the era of big data, consumers capture more and more economic surplus yet the seed of distrust also grows with the fast-spreading of social commerce, this paper began with the idea that product types may determine the degree of consumers' distrust even when identical discounts are offered for those products on Chinese social commerce websites. We also attempted to determine if distrust negatively affected consumers' purchase attitudes. 20 representative products that are commonly sold on social commerce websites in China were chosen to examine the relationships among product types, discount rates, distrust levels, and purchase attitudes. Inductive interview was used to collect the data as well as consumers' perceptions of the relationships. Data analysis results suggested that consumers like deep discounts, but their distrust levels increase along with the discount rates, however, the levels of increasing distrust vary according to product types. High, medium, and low discount rate categorizations were made and three propositions were suggested. This paper will contribute to the body of knowledge on online social commerce market and provide valuable implications for e-retailers and general consumers in online social commerce websites in China.

• Asia pacific journal of information systems
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• v.16 no.3
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• pp.159-176
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• 2006

Collaborative filtering is one of the popular techniques for personalized recommendation in e-commerce. In collaborative filtering, user profiles are usually managed per product category in order to reduce data sparsity. Product diversification of Internet storefronts and multiple product category sales of e-commerce portals require cross-product category usage of user profiles in order to overcome the cold start problem of collaborative filtering. In this paper, we study the feasibility of cross-product category usage of user profiles, and suggest a method to improve recommendation performance of cross-product category user profiling. First, we investigate whether user profiles on a product category can be used to recommend products in other product categories. Furthermore, a way of utilizing user profiles selectively is suggested to increase recommendation performance of cross-product category user profiling. The feasibility of cross-product category user profiling and the usefulness of the proposed method are tested with real click stream data of an Internet storefront which sells multiple product categories including books, music CDs, and DVDs. The experiment results show that user profiles on a product category can be used to recommend products in other product categories. Also, the selective usage of user profiles based on correlations between subcategories of two product categories provides better performance than the whole usage of user profiles.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1318-1323
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• 2009

In recent years, dramatic advances in information technology have motivated the construction industry to improve its productivity. Computer-based information technology includes Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), Computer-Aided Manufacturing (CAM), Enterprise Resource Planning (ERP), Digital Mock-Up (DMU) and Product Data Management (PDM). Most construction industries are trying to apply these technologies for quality improvement, reduction of construction time and cost. PDM is very useful for managing data and process related to product design and manufacturing. PDM system has various functions such as drawing and engineering document management, product structure and structure modification management, part classification management, workflow management, and project management. In this paper, PDM system was applied to the design of steel-concrete composite girder bridge. To make a practical guidance for PDM implementation to bridge design, the procedure for its implementation was presented. Consequently, this paper could be useful to enhance the efficiency of bridge design.