• Journal of the Society of Naval Architects of Korea
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• v.54 no.1
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• pp.57-62
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• 2017

These days, shipbuilding companies are making an effort to adopt the IT technology in order to improve the production efficiency. One such effort is to utilize a planning and scheduling system to predict the production cost in advance. In this system, assessing the welding material quantity is an important factor. Unfortunately, obtaining the welding material quantity in the early design stage is extremely difficult because the detailed production information, which is essential in deriving the cost associated with welding, is normally available at a later stage. This paper aims at developing a computerized program that produces an index to estimate the welding material quantity in the early design stage. By using only three-dimensional geometric information, the program analyzes the production process and estimates the welding material quantity at any design or production stage when no production information is available. The results can be used for the planning and scheduling system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.6
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• pp.964-978
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• 2015

Numerous experiments with a scaled pilot facility were carried out to compare the relative bulk transfer performance of three special devices for applications to drilling systems. The pipe diameter for bulk transportation was 3 in., which corresponds to around half of the actual system dimensions. Two different pressures, 3 and 4 bar, were considered to check the relative performance under different pressure conditions at a bulk storage tank. And to make a practical estimation method of the bulk transfer rate at the early design stages of the bulk handling system, a series of experiments were conducted for real scaled bulk handing systems of two drilling vessels. The pressure drops at each pipe element as well as the bulk transfer rates were measured under different operating conditions. Using the measured results, the friction factor for each pipe element was calculated and a procedure for transfer rate estimation was developed. Compared to the measured transfer rate results for other drilling vessels, the estimated transfer rates were within a maximum 15% error bound.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.856-866
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• 2021

The increasing international awareness regarding air pollutant reduction has resulted in increasing demand for eco-friendly ships; hence, electric ships are being actively developed by various countries. Presently, studies on electric ships are mainly focused on electric propulsion systems and electric motors. However, from the ship perspective, there are no studies on conceptual designs for coastal car ferries powered by removable power supply systems. In the present study, the main research consideration is regarding the conceptual design of a fully electrified car ferry using a battery-based removable system as the main power source. By analyzing the dimensions of more than 100 domestic coastal car ferries, the main criteria satisfying the requirements for developing a suitable vessel were derived, and a study on intact/damage stability was conducted considering the application of a removable battery truck. Further analyses of the problems concerning the conceptual design were also performed to derive solutions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.589-591
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• 2021

In the offshore plant industry, the Access service basket for aerial work is used of for various business purposes. However, various types of safety accidents continue to occur in operating these system. In the case of high-capacity workstations currently in use, workers are exposed to various risks in determining and operating the load capacity, proximity distance, and direction of operation. In this paper, to solve this problem, we develop a device that incorporates IoT-based monitoring and crash alarm systems into aerial work systems. The developed device was tested in the presence of experts to ensure reliability of the device, which allows workers and managers to easily check the operation status and thereby prevent safety accidents in advance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.153-160
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• 2022

This study presents the bogie arrangement of the load-out system for on-ground shipbuilding. The load-out system is one of the most important systems to perform the bogie arrangement of the on-ground shipbuilding technique without dry dock facilities, and this system is composed of four pieces of equipment: bogies, driving bogie with motors, trestles, and power packs. Also, the bogie arrangement analysis (BAA) is employed to simply calculate the reaction forces at the trestle for structural safety. In this context, the purpose of this study is to propose an optimal design method to perform the bogie arrangement satisfying structural safety requirements with minimal cost. It is expected that the proposed methodology will contribute to the effective practice as well as to the improvement of competitive capability for shipbuilding companies at the on-ground shipbuilding stage. Furthermore, we describe some problems and their solutions of the deformation that may occur in the bottom of the hull during the load-out process. As a result, it is shown that we applied it to the 114K crude oil tanker (Minimum bogie 54EA) and the 174K CBM LNG carrier (Minimum bogie 88EA), it can minimize the number of bogie and critical risks (Safety rate 1.61) during the load-out of on-ground shipbuilding. Through this study, the reader will be able to learn successful load-out operation and economic shipbuilding in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4442-4466
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• 2016

This paper proposes a privacy-preserving aggregation scheme based on the designed P-Gene (PAPG) for sensor networks. The P-Gene is constructed using the designed erasable data-hiding technique. In this P-Gene, each sensory data item may be hidden by the collecting sensor node, thereby protecting the privacy of this data item. Thereafter, the hidden data can be directly reported to the cluster head that aggregates the data. The aggregation result can then be recovered from the hidden data in the cluster head. The designed P-Genes can protect the privacy of each data item without additional data exchange or encryption. Given the flexible generation of the P-Genes, the proposed PAPG scheme adapts to dynamically changing reporting nodes. Apart from its favorable resistance to data loss, the extensive analyses and simulations demonstrate how the PAPG scheme efficiently preserves privacy while consuming less communication and computational overheads.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.8
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• pp.1378-1391
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• 2010

This study examines the wearing conditions of working clothes according to the working environment and working processes at machinery, automobile, shipbuilding industry sites. It also investigates the relationship between the wearing sense of working clothes and the overall comfort according to work processes. The hazardous working environment was high in the order of the shipbuilding industry, machinery, and automobiles. The findings on the harmful overall work environmental factors were the noise, heavy dust, and noxious fumes, respectively. In general, the satisfaction with the wearing performance of working clothes was low especially with regard to sweat absorbency, sweat permeability, body protection and covering, and the work motion suitability. In respect of the correlation between the overall comfort and the wearing sense of working clothes, the satisfaction was decreased in the order of movement comfort, sensual comfort, and physiological comfort.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Journal of Advanced Research in Ocean Engineering
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• v.2 no.4
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• pp.179-191
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• 2016

As the demand for renewable energy has increased following the worldwide agreement to act against global climate change and disaster, large-scale floating offshore wind systems have become a more viable solution. However, the cost of the whole system is still too high for practical realization. To make the cost of a floating wind system be more economical, a new concept of tension leg platform (TLP) type ocean floating wind system has been developed. To verify the performance of a 5-MW TLP type ocean floating wind power system designed by the Korea Advanced Institute of Science and Technology, the FAST simulation developed by the National Renewable Energy Laboratory is used. Further, 1/50 scale model tests have been carried out in the ocean engineering tank of the Research Institute of Medium and Small Shipbuilding, Korea. This paper compares the simulation and ocean engineering tank test results on motion prediction and tension assessment of the TLP anchor.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.1
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• pp.32-40
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• 2017

Recently, the amount of data to be processed and the complexity thereof have been increasing due to the development of information and communication technology, and industry's interest in such big data is increasing day by day. In the shipbuilding and offshore industry also, there is growing interest in the effective utilization of data, since various and vast amounts of data are being generated in the process of design, production, and operation. In order to effectively utilize big data in the shipbuilding and offshore industry, it is necessary to store and process large amounts of data. In this study, it was considered efficient to apply Hadoop and R, which are mostly used in big data related research. Hadoop is a framework for storing and processing big data. It provides the Hadoop Distributed File System (HDFS) for storing big data, and the MapReduce function for processing. Meanwhile, R provides various data analysis techniques through the language and environment for statistical calculation and graphics. While Hadoop makes it is easy to handle big data, it is difficult to finely process data; and although R has advanced analysis capability, it is difficult to use to process large data. This study proposes a big data platform based on Hadoop for applications in the shipbuilding and offshore industry. The proposed platform includes the existing data of the shipyard, and makes it possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weights of offshore structure topsides. In this study, we store data of existing FPSOs in Hadoop-based Hortonworks Data Platform (HDP), and perform regression analysis using RHadoop. We evaluate the effectiveness of large data processing by RHadoop by comparing the results of regression analysis and the processing time, with the results of using the conventional weight estimation program.