• Title/Summary/Keyword: Material Classification

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Classification System of material and Component Technology and Industry (부품ㆍ소재 정보를 위한 분류 체계 설계)

  • 이희상;유재영;정의섭
    • Journal of Korea Technology Innovation Society
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    • v.6 no.1
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    • pp.110-124
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    • 2003
  • In this study, we establish technology classification system for twelve material and component(MC) areas to sup-port systematic information services for MCT-20l0 which is supported by Korean government. We propose some design principles for MC technology classification system. The principles are suggested by considering of the characteristics of MC classification, regarding with scope, originality, hierarchy, relationship between technology classification and product classification, duplication and complex structure, use of information system, and life cycle of the classification system.

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A Comparative Study on the Classification System of Material Library (소재도서관 분류체계에 대한 비교 연구)

  • Chung, Ok-Kyung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.4
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    • pp.297-317
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    • 2018
  • The purpose of this study is to propose a classification system that can classify various industrial and craft materials consistently and systematically by comparing and analyzing the classification system of materials libraries in domestic and foreign. For this study, it was investigated the operation cases and classification system of domestic and foreign material libraries, and then proposed a method to classify consistently and systematically by comparing and analyzing the classification items of KDC and DDC. The classification system of material library was not classified by subject, but classified into the name of material and type, or the classification system of a material library was divided by Arabic numeral as a general classification system. It is difficult to access and share information because most of material libraries use the classification system developed by the library itself. Therefore, it is necessary to develop a standard classification system to share the information stored in the material libraries.

Improvement of the Code Classification Structure in Piping Material Management for Petrochemical Plant Projects (석유화학 플랜트의 효율적 배관자재 관리를 위한 코드분류체계 개선)

  • Lee, Jong-Pill;Moon, Yoon-Jae;Lee, Jae-Heon
    • Plant Journal
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    • v.11 no.1
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    • pp.39-49
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    • 2015
  • The objective of this study is to improve the classification structure of commodity code for piping material management which is considered as the fundamental of commodity code and piping material management system. It enhances the efficiency of piping material management directly or indirectly affecting the engineering, procurement and construction in a petrochemical plant projects. To establish an improved code classification structure, this study identifies the problems of former code classification structure in details, as well as the characteristics of other domestic and global EPC company's code classification structures and presents the improved direction considering the recently mega-sized and specialized projects. Accordingly, to efficiently enhance piping material management, the improved code classification structures have been derived from defining suitable code classification structure for specific piping component, adding more standard attribute, expanding the number of code digits and classifying code hierarchy. The results of applying the improved classification structure of commodity code to on-going project have led to reduce the rate of rework from 4.98% to 2.48% for developing purchase description and also have saved working time for executing piping design by 3D modeling from 6 months by two persons to 4 months by a person which is decreased 67% consequently. In addition, the structures of pyramid code management have resulted to accumulation and analysis of the various piping data for other disciplines such as procurement and estimation team which require commodity code information through the company's material control system.

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Comparison of Classification rate of PD Sources (부분방전원 분류기법의 패턴분류율 비교)

  • Park, Seong-Hee;Lim, Kee-Joe;Kang, Seong-Hwa
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2005.07a
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    • pp.566-567
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    • 2005
  • Until now variable pattern classification methods have been introduced. So, variable methods in PD source classification were applied. NN(neural network) the most used scheme as a PD(partial discharge) source classification. But in recent year another method were developed. These methods is present superior to NN in the field of image and signal process function of classification. In this paper, it is show classification result in PD source using three methods; that is, BP(back-propagation), ANFIS(adaptive neuro-fuzzy inference system), PCA-LDA(principle component analysis-linear discriminant analysis).

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Material Classification Using Reflected Signal of Ultrasonic Sensor (초음파의 반사 신호를 이용한 실내환경의 재질 인식)

  • Kim Dal-Ho;Lee Sang-Ryong;Lee Choon-Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.6
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    • pp.580-584
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    • 2006
  • Material information for environment may be useful to accomplish mobile robot localization. A procedure to classify a set of indoor materials (glass, steel, wood, aluminum and concrete) with the reflected signal of ultrasonic sensor is proposed in this paper. The main idea is to use material-specific reflection characteristics for the recognition of material type. To achieve the classification task, we modeled reflected signal as a maximum amplitude with respect to distance. In this way, we can generate echo signal models for the given materials and these models are used to compare with the current sensor reading. The experimental results show that the proposed method may give material information during map building task of mobile robot.

The development of web based power plant maintenance management system (Web기반 발전설비 정비관리시스템 개발)

  • Kim, Bum-Shin;Kim, Eui-Hyun;Jang, Don-Sik;Cho, Jae-Min;Chae, Gil-Seok;Jung, Gyu-Chol
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.2059-2063
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    • 2004
  • Most power plants have operated many independent computerize systems for maintenance. Independence of systems have caused complexity of business process and inconvenience of computer system management. Because the equipment and material master data is not standardize and structurize, it is difficult to manage equipment maintenance history and material delivery. Especially equipment classification criterion is important for standardization of every maintenance information. It is necessary to integrate function of independent systems for business process simplification and rapid work flow. this paper provides equipment classification criterion design and system integration method with the case of live system development.

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Comparison with Finger Print Method and NN as PD Classification (PD 분류에 있어서 핑거프린트법과 신경망의 비교)

  • Park, Sung-Hee;Park, Jae-Yeol;Lee, Kang-Won;Kang, Seong-Hwa;Lim, Kee-Joe
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.07b
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    • pp.1163-1167
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    • 2003
  • As a PD classification method, statistical distribution parameters have been used during several ten years. And this parameters are recently finger print method, NN(Neural Network) and etc. So in this paper we studied finger print method and NN with BP(Back propagation) learning algorithm using the statistical distribution parameter, and compared with two method as classification method. As a result of comparison, classification of NN is more good result than Finger print method in respect to calculation speed, visible effect and simplicity. So, NN has more advantage as a tool for PD classification.

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Material Maintenance Information System for Electric Multiple Unit (도시철도 차량 유지보수를 위한 자재시스템 정보화에 대한 연구)

  • Ahn, Tae-Ki
    • Proceedings of the KIEE Conference
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    • 2006.10d
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    • pp.241-243
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    • 2006
  • To supply the materials the right time, and the right place, it is required some information maintenance system to manage this procedure effectively. In this paper, we represent the standard products classification for EMU and the materials maintenance information system to manage the parts used EMU maintenance efficiently. The standard material classification is matched to G2B code made by the Supply Administration. The implemented material information system can perform various functions such as the inquiry of the number of stocks, the demand of the materials, and etc.

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Study on the Linking Method of Information Factors in order to use in wide of Standard Material into Apartment Housing Construction (공동주택의 표준자재 범용화를 위한 정보요소의 연계 및 개발방안 연구)

  • Park, Geun-Soo;Lim, Seok-Ho
    • Proceeding of Spring/Autumn Annual Conference of KHA
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    • 2008.11a
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    • pp.448-451
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    • 2008
  • This study is under doing to suggest application manual using assembling reference plane design & standard finish material basis upon material classification code as a tool of a linkage between building design and construction standarization in order to enlarge the applicability of house building material that is produced by the module plant. We can say the goal of building standardization intend not only the improvement of construction productibility but also guarantee of subsequent performance through automatization basis upon informationalization of building design. For a etabilishing of this condition, it is neccessary to link the standardization's result of material--design--construction field. According to this neccessity, we are going to suggest information factor that can make relative business manager easily approach to the standardization practical task.

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Material Image Classification using Normal Map Generation (Normal map 생성을 이용한 물질 이미지 분류)

  • Nam, Hyeongil;Kim, Tae Hyun;Park, Jong-Il
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.69-79
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    • 2022
  • In this study, a method of generating and utilizing a normal map image used to represent the characteristics of the surface of an image material to improve the classification accuracy of the original material image is proposed. First of all, (1) to generate a normal map that reflects the surface properties of a material in an image, a U-Net with attention-R2 gate as a generator was used, and a Pix2Pix-based method using the generated normal map and the similarity with the original normal map as a reconstruction loss was used. Next, (2) we propose a network that can improve the accuracy of classification of the original material image by applying the previously created normal map image to the attention gate of the classification network. For normal maps generated using Pixar Dataset, the similarity between normal maps corresponding to ground truth is evaluated. In this case, the results of reconstruction loss function applied differently according to the similarity metrics are compared. In addition, for evaluation of material image classification, it was confirmed that the proposed method based on MINC-2500 and FMD datasets and comparative experiments in previous studies could be more accurately distinguished. The method proposed in this paper is expected to be the basis for various image processing and network construction that can identify substances within an image.