• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.2
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• pp.118-123
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• 2010

The eco-friendly technologies have been extended as matter of international concern due to various diseases and syndromes according to an environmental pollution. In this study, we have manufactured a ceramic cluster with thick film type for anion generation equipment which is maximized anion but minimized ozone contents generated. To develop the formulation of ceramic cluster, we conducted the $Mg_2SiO_4$ powders doped with 10 vol% glass frits as Na-Zn-B-O system and sintered at $1050^{\circ}C$ for 2 hours in air for starting materials and investigated the matching properties between the Ag-Pd electrode and the starting materials. The sintered sample for the composition of cluster has 6.7 of dielectric constant and 32 kV/mm of withstand voltage. The yield of anions was measured according to an electrode pattering, discharge gap between electrode, and thickness of electrode protective layer in the cluster of thick film type. We have manufactured the ceramic clusters with optimized thick film structure that have an anion over a hundred particles and the ozone of 0.6 ppb generated.

• The Journal of shipping and logistics
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• v.34 no.4
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• pp.695-710
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• 2018

Following the collapse of Hanjin Shipping, building a strong maritime cluster is one of the policy measures for the re-construction of the Korean shipping and shipbuilding industries. Thus, the purpose of this study is to develop a policy alternative for building a maritime cluster. Using Porter's diamond models, we analyzed the Imabari maritime cluster of Japan, which is characterized by cooperation between key industries, such as shipping, shipbuilding, shipbuilding equipment, and finance. The Imabari Maritime Cluster is equipped with complete domestic demand conditions and related supporting industry conditions. Although the strengths of the production conditions include excellent family-based management and strong support from regional administration and banks which develops independency among cluster members, the weak points include the absense of robust port services and difficulty in recruiting young talent in small and medium-sized cities. We can confirm that the company's strategy is focused on stable management, rather than a short-term view.

• Journal of Distribution Science
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• v.11 no.4
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• pp.5-11
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• 2013

Purpose - The aim of this work is to study the reorientation that the export industrial sectors in Costa Rica have experienced during the last 20 years. Research design, data, methodology - The study employs the Cluster Analysis with the export data (20 years of cut-off period) from Costa Rica to the U.S-market. To make the predictions, the technique of the time series was used, with official data (from 2001 to 2010) from the U.S. Department of Commerce and the U.S. International Trade Commission. Results - The Cluster Analysis, show how the economic sectors of traditional products exports of Costa Rica have progressively become in exporters of non-traditional products, meanwhile,the time series confirms that this trend will continue, at least during the next five years. Conclusions - The industry of traditional products exports of Costa Rica (dressmaking, vegetables, coffee, mate, species, etc.) will progressively become in exporters of non- traditional products with a high-tech component (i.e., mechanical equipment and devices, electronic devices and medical equipment),as a consequence of the Chinese (Costa Rica's main competitor) economy's presence in the Organization for Economic Co-operation and Development (OCDE). This fact has enabled the potential improvement of Costa Rica's international competitiveness in the U.S. market.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.472-480
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• 2023

This paper describes the development of a test-equipment for the pre-verification of navigation performance in cluster-based AUVs (Autonomous Underwater Vehicle). In the development of an AUV, conducting hardware and software development sequentially is not efficient due to the limited research and development period. Therefore, in order to reduce the overall development time and achieve successful development results, it is essential to pre-validate the navigation system and navigation algorithms. Accordingly, this paper explains the test-equipment for pre-verification of navigation performance, and ultimately confirms the stability of the navigation system and the performance of the navigation algorithms through the analysis of five types of navigation sensor data stored during real-sea experiments. The results demonstrate that through the development and verification of the test-equipment, it is possible to shorten the overall development period and improvement of product quality in the process of developing multiple AUVs.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.957-969
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• 2020

The primary objective of this study is to develop a determination system for an optimal combination of earthwork equipment that improves the traditional way in convenience, prediction accuracy, and productivity. For this, the following research works are conducted sequentially; 1)literature review, 2)technology development trend analysis, 3)develop a determination system for the optimal combination of earthwork equipment, 4)simulation of a developed system. As a result, core considerations are deducted for the development of a determination system. Furthermore, site simulation is performed using a developed system. Site simulation result, Cluster 1(R1200LC 7㎥, CAT 775G 65ton×2) was selected from 6 clusters because of its production cost (￦491/㎥). It is expected that the application range and impact on the construction industry will be enormous due to the availability of the developed system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.573-586
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• 2016

In construction jobs, a combination of various kinds of machinery is used to perform earthworks at a large-scale site. Individual equipments essentially cooperate with each other on task such as excavation, load, transfer and compaction. While other area have studied cooperation system, related study in domestic construction is in poor condition. In this study, construction equipment fleet management system is developed for solving this problem and find way to improving efficiency in earthworks site. The entire concept of the fleet management system, including its components and process, has been systematically outlined in this paper. An operational methodology has also been suggested, where a number of machines, such as the excavators, trucks and compactors, are chosen and further grouped into a cluster. A case study verify fleet management system's effectiveness on performing task package by comparing existing work method with methodology in this study. Fleet management system in this study is expected to curtail fuel consumption by the reduction of working time and moving distance. Furthermore, it can be anticipated to declining carbon emission effect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.11-16
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• 2020

As a plan for oil spill accidents, research to collect and analyze optimal equipment assignments is essential. However, studies that have diversified and analyzed the optimal equipment assignments for responding to oil spill accidents have not been preceded. In response to the need for analyzing optimal equipment assignments study, we devised a genetic algorithm for optimal equipment assignments. The designed genetic algorithm yielded 10,000 optimal equipment assignments. We clustered using the k-means algorithm. As a result, the two clusters of Yeosu, Daesan, and Ulsan, which are expected to be the largest spills, were clearly identified. We also projected 16-dimensional data in two dimensions via Sammon's mapping. The projected data were analyzed for distribution. We confirmed that results of the simulation were better than those of optimal equipment assignments included in the cluster.In the future, it will be possible to implement an approximate model with excellent performance based on this study.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.550-569
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• 2012

This paper studies the R&D network of the Zhongguancun Cluster, the most representative innovative cluster of the high-tech industry in China at present. For this study, Zhongguancun Cluster was the first high-tech cluster to have been created in China, the current Zhongguancun Cluster has played a leading role in the development of the high-tech industry in China. In addition, the Zhongguancun Cluster has at helped elevate China as a key region in terms of research development in relation to the high-tech industry. In particular, companies evaluate the research development network culture of Zhongguancun cluster positively and this increases their tendency to approach the research development network with an open mind. The main contents in research development network are as follows; (1) joint or consigned research development and technology transfer in the case of research development network between companies, (2) joint or consigned research development, human resource support and employment, technical advice and consultant and technology transfer in the case of industrial-educational relationships (3) joint or consigned research development, technical advice and consultant and technology transfer in the case of industrial-research relationships, (4) financial support and participation in joint research development project held by government in the case of industrial and governmental relationships (5) financing for research development, utilization of research human resources, purchase of research development and use of research development equipment for mediators. The main difficulties in creating a research development network are 'lack of mutual trust', 'financial problems of companies' and 'lack of information'. Especially, the main key obstacles for the most important research development network between industry and government in the case of the Zhongguancun Cluster are 'complicated and strict procedures. Therefore, more accurate and detailed understanding of the conditions and the following institutional measures from government are required for research development among companies.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.