• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.281-290
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• 2015

The specific goal of the SMS (Ship Management System) is to increate ship safety and decrease maintenance fee. Equipment of ship is managed by PMS (Planned Management System), subsystem of SMS. But hull has not managed by ship manager. So, the Classes have developed the system for hull maintenance. Recently, the ship maintenance system has been developed for satisfying operator's requirements such as managing maintenance data as integrated platform, intuitive manipulation and design for ease of use. To reflect such requirement, 3D Model based maintenance system was introduced for ship in operation stage. Hull items that have to be inspected, repaired, replaced, are stored in integrated data platform with drawing, reports, and etc. and completely linked to 3D product Model. This system is specially developed for measurement and maintenance of hull thickness.

• Korean Journal of Computational Design and Engineering
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• v.11 no.5
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• pp.335-343
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• 2006

Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.107-116
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• 2001

The purpose of this paper is to solve the problem that is occuring in assembly process and to progress the productivity by process analysis methods for manu-open and closed model(DWV-20/25DRG), and auto-open and cloesd model(DWV-20/25/DRA)-ventilation fan. Also, this paper is studied by data of ＇D＇ company's product.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.93-100
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• 2001

The three dimensional(3D) reconstruction from two dimensional(2D) image data is using in many fields such as RPD(Rapid Product Development) and reverse engineering. In this paper, the main step of 3D reconstruction is comprised of two steps : image processing step and B-spline surface approximation step. In the image processing step, feature points of each cross-section are obtained by means of several image processing technologies. In the B-spline surface approximation step, using the data of feature points obtained in the image processing step, the control points of B-spline surface are obtained, which are used for IGES file of 3D CAD model.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.849-860
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• 2021

Recently, it is easy to find cases of 3D printing product, equipment, and materials in the architecture field. However, there is a lack of distribution environment where 3D printing products can be traded on an online platform or to access on-demand services in the architecture field. Therefore, in this study, a distribution platform development plan was proposed in consideration of the maturity level of the 3D printing distribution market in the domestic architecture field. For this purpose, the research was carried out as follows. First, by analyzing the case of the 3D printing distribution platform, the development stage of the distribution platform was set as three stages from the perspective of market maturity, platform development level, and sales/purchase experience level of suppliers and consumers. Second, the market maturity of the current domestic architecture field was evaluated as the first stage, and a distribution platform that could be implemented in the first stage was presented as a pilot. Third, we presented the first stage pilot, collected practical opinions on future construction plans through in-depth interviews, and presented detailed implementation plans for each stage necessary to achieve the second and third stage market maturity goals. Based on the roadmap derived from this study, it is expected that the domestic distribution platform market will grow step by step in the future and be utilized for business model development.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.400-411
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• 2011

Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components-process variables experiments depend on the mixture components-process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. In this paper we propose three starting models for the mixture components-process variables experiments. One of the starting model we are considering is the model which includes product terms up to cubic order interactions between mixture effects and the linear & pure quadratic effect of the process variables from the product model. In this paper, we propose a method for finding robust designs and practical designs with respect to D-, G-, and I-optimality for the various starting combined models and then, we find practically efficient and robust designs for estimating the regression coefficients for those models. We find the prediction capability of those recommended designs in the case of three components and three process variables to be good by checking FDS(Fraction of Design Space) plots.

• Design & Manufacturing
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• v.15 no.3
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• pp.1-6
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• 2021

An artificial neural network model based on a deep learning algorithm is known to be more accurate than humans in image classification, but there is still a limit in the sense that there needs to be a lot of training data that can be called big data. Therefore, various techniques are being studied to build an artificial neural network model with high precision, even with small data. The transfer learning technique is assessed as an excellent alternative. As a result, the purpose of this study is to develop an artificial neural network system that can classify burr images of light guide plate products with 99% accuracy using transfer learning technique. Specifically, for the light guide plate product, 150 images of the normal product and the burr were taken at various angles, heights, positions, etc., respectively. Then, after the preprocessing of images such as thresholding and image augmentation, for a total of 3,300 images were generated. 2,970 images were separated for training, while the remaining 330 images were separated for model accuracy testing. For the transfer learning, a base model was developed using the NASNet-Large model that pre-trained 14 million ImageNet data. According to the final model accuracy test, the 99% accuracy in the image classification for training and test images was confirmed. Consequently, based on the results of this study, it is expected to help develop an integrated AI production management system by training not only the burr but also various defective images.

• Journal of Distribution Science
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• v.18 no.9
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• pp.31-43
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• 2020

Purpose: This study examined a comprehensive model for assessing the success probability of electric vehicle (EV) commercialization in the Korean market. The study identified three risks associated with successful commercialization which were technology, social, policy, environmental, and consumer risk. Research design, methodology: The assessment of the riskiness was represented by a Bayes belief network, where the probability of success at each stage is conditioned on the outcome of the preceding stage. Probability of success in each stage is either dependent on input (i.e., investment) or external factors (i.e., air quality). Initial input stages were defined as the levels of investment in product R&D, battery technology, production facilities and battery charging facilities. Results: Reasonable levels of investment were obtained by expert opinion from industry experts. Also, a survey was carried out with 78 experts consisting of automaker engineers, managers working at EV parts manufacturers, and automobile industry researchers in government think tanks to obtain the conditional probability distributions. Conclusion: The output of the model was the likelihood of success - expressed as the probability of market acceptance - that depended on the various input values. A model is a useful tool for understanding the EV industry as a whole and explaining the likely ramifications of different investment levels.

• International Journal of CAD/CAM
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• v.7 no.1
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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.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.362-374
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• 2010

Product Lifecycle Management (PLM) is an integrated business approach to manage the creation and distribution of product information throughout the product development process. From the product perspective, PLM encompasses a holistic approach to product development and product information management. It supports the integrated product information in conjunction with the efficient product structures and BOM (Bill Of Material), user interfaces, proper functions, design processes and enterprise integration. Therefore, PLM should not only satisfy required functions as an enterprise software but also offer a systematic method for the efficient application from the initial stage of its development. Recently, many shipyards have been considering the PLM as a strategic solution to get the efficient management of product information such as 3-D models, BOM, drawings, documents, and the other product data. Though many studies on PLM are performed, most of them are performed in a function-based approach adequate for mass productive assembly industries. It could not help having limitations on applying the proper PLM system to the shipbuilding business since the requirements of shipbuilding PLM are too diverse and huge to design the architecture. This study presents the PLM framework which effectively reflects the diverse requirements of shipbuilding PLM. In order to get the macroscopic architecture of shipbuilding PLM, authors suggest the four-tier architecture model which considers the various requirements collected from shipyards. Entities of ship design data are modeled BOM in terms of product structure and hierarchical class diagram. Applicable functions of shipbuilding PLM are also investigated by analysis of issues of ship design. Finally, by reflecting the design process of shipbuilding, To-Be ship design procedure cooperated with the suggested PLM framework has been summarized.