• Journal of Distribution Science
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• v.11 no.3
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• pp.13-22
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• 2013

Purpose - Product purpose for optimal values solution for synthesize evaluative criteria and optimize product design values. In addition, product designer has to consider the product design to conform to project, laws and regulations, authentication, from the product design stage. Research design, data, methodology - How to use an evaluative criteria model's imprecise market data by evaluative criteria research design; product mapping relationships between design parameters and customer requirements using product predicted value method. An evaluative criteria model and their associated criteria status, product evaluative criteria model of results. Results - Therefore, after the enterprise product design project analysis, effectiveness and the customer degree of satisfaction must be appraised to obtain the maximum value for the benefit on behalf of the implementation goals, the promotion product level and market competition strength. Conclusions - In multi criterion decision making (MCDM), using its searching software capacity to obtain the optimal solution.

• Korean Journal of Computational Design and Engineering
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• v.13 no.4
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• pp.314-322
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• 2008

This paper introduces an integration of Product Data Management (PDM) and Software Configuration Management (SCM). PDM and SCM have supported development of mechanical products and software products respectively. The importance of software components in the current products increases rapidly since the software enables the products to satisfy various customer requirements efficiently. Therefore the current product development needs enhanced product data management that can control both the hardware and software data seamlessly. This paper proposes an extended product data model for integrating SCM into PDM. The extension enables PDM document management to support the version control for software development. It also enables engineers to control both the software and hardware parts as integrated data objects during product configuration and engineering change management. The proposed model is implemented by using a commercial Product Lifecycle Management (PLM) system and a development of a network based robot system is tested by the implemented product development environment.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.597-608
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• 1997

Life cycle product data is very important yet difficult to handle for manufacturing companies. Shoring and exchanging product data over world-wide-web is a part of key technology to implement PDM or CALS. STEP is widely accepted as a standard to represent the life-cycle product model data. Described in this paper is a web browser plug-in that can graphically display and explore product data represented by STEP over internet. By the use of the plug-in (named "npSTEP"), a product model data stored in STEP format on a web server can be displayed on a commonly used web client (browser), such as Netscape navigator, without any format conversion process. Furthermore one can explore the components or attributes of the product model data in hierarchical manner.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.1
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• pp.57-68
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• 2009

In automotive industries, reusability of product information is increasing through database construction of previous product data. The product data is stored by data quality management in product information systems. For naval ships, have the functional similarity by the ships of the same classification and class, that are built by series. Information of hull structures as well as embarked equipments are similar. So it would be effective to use database systems that are considered product information quality of previous ships in design and production processes. In this paper we discuss product information quality in database construction of naval ship product models. For this, we propose a basic concept and reference model for data quality verification. Based on this concept, A verification guideline is defined and it is applied for the case study of the digital naval ship which was built to the naval ship product model.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.1
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• pp.43-56
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• 2009

The Korean navy has made many efforts to apply the concepts of PLM (Product Lifecycle Management) and M&S to its naval design and production. However, most of the efforts that have being applied to some acquisition processes, focused only on the element technologies without information models and data frameworks. This study discusses an information model of naval ships for advanced naval acquisitions. We introduce a naval ship product model, and it refers to the DPD (Distributed Product Description) concept of SBA (Simulation-Based Acquisition). To realize the product model concept, we design a data architecture and develop a Product Model Management System (PMMS) based on a PDM System. It is validated through the case study of building the product model of the battle ship that the PMMS has the applicability to effectively manage the naval ship acquisition data on the basis of a 3D product model.

• 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 Korean Society for Quality Management
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• v.41 no.4
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• pp.623-635
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• 2013

Purpose: The recent major recalls of hazardous products caused consumer product safety acts to be strengthen worldwide. Although the recall system of hazardous products in Korea has been operating based on Framework Act on Product Safety since 2011, the evaluation of product risk has been relied on not the results of objective incident data but the results of illegal product investigations. The purpose of this paper is to propose a product risk assessment model for Korea using injury data. Methods: The authors derived Korea's risk assessment method by analysing the advantages and disadvantages of the most widely used models in advanced countries such as EU's RAPEX RAG and Janpan's R-MAP. In this study, the level of relative frequency and severity of injury are determined based on the objective incident data and the length of hospitalization respectively. In addition, the injury data occurred during 2011 is applied to the proposed risk assessment model for case study. Results: The data analysed in this paper can be classified as high risk, medium risk, low risk, acceptable risk, and safe products through the matrix f rom the combination of the relative frequency and the severity derived. Conclusion: The proposed risk assessment model in this study has advantage obtaining reliable objective results because it uses actual injury data and redeems the drawbacks of the existing models used in advanced countries. Furthermore, because the proposed model shows the high risk products among many, it is expected to be useful especially for customs whose main job is inspecting the imported goods and the government when selecting the target product groups for safety investigation.

• 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.

• Journal of Engineering Education Research
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• v.25 no.1
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• pp.46-54
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• 2022

This study attempted non-face-to-face collaborative product development practice that can respond to the spread of COVID-19 by expanding existing product data management system-based product development practice. For the complete non-face-to-face product development practice, it utilized prototype development using a 3D paper model, an online class management system and social media for classes and meetings. As a result of applying the non-face-to-face method, product developments of 26 practice teams have been completed without any failures. Therefore, through this study, the author can confirm that it is possible to provide the complete non-face-to-face collaborative product development practice based on product data management systems.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.55-60
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• 2017

In order to provide intelligent services without human intervention in the Internet of Things environment, it is necessary to analyze the big data generated by the IoT device and learn the normal pattern, and to predict the abnormal symptoms such as faulty or malfunction based on the learned normal pattern. The purpose of this study is to implement a machine learning model that can predict product failure by analyzing big data generated in various devices of product process. The machine learning model uses the big data analysis tool R because it needs to analyze based on existing data with a large volume. The data collected in the product process include the information about product faulty, so supervised learning model is used. As a result of the study, I classify the variables and variable conditions affecting the product failure, and proposed a prediction model for the product failure based on the decision tree. In addition, the predictive power of the model was significantly higher in the conformity and performance evaluation analysis of the model using the ROC curve.