• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1161-1166
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• 2017

Recently, with the development of display technology, AMOLED(Active Matrix OLED) panel production and demand are increasing. Unlike LCD, AMOLED panel basically does not need backlight, so it can output clear images with low power consumption. Therefore, the AMOLED market is growing globally. Accordingly, the demand for inspection devices required for production is also expanding. The inspection device of the AMOLED panel aging system operates in conjunction with MES(Manufacturing Execution System) and MIS(Management Information System), and it is efficient to construct network environment. The inspection device used for panel aging is a pattern generator capable of outputting multiple signals. Efficient design is required to operate multiple signal generators. To solve this problem, the proposed system proposed a method for remotely controlling the signal generator remotely and a method for driving the AMOLED panel. And the timing and power setting results are presented.

• International Journal of Contents
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• v.13 no.2
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.54-61
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• 2009

General manufacturing process of the manufacturing time and manufacturing process problems have a problem. In the past, in the manufacturing process the data by hand has been. Therefore, the production performance management information, and materials input, output information, equipment information of the failure of the management problems emerged. Through this research, improvements in real-time production information to collect distribution and overall productivity will increase the efficiency of the system. the production process to improve the quality of management, efficient production methods are presented. is a stable quality control. POP system The new building should be. This is the executive or administrative decisions support. It increases productivity, efficiency, and reduce production costs, increase product reliability. This will increase the company's reputation. This increases the competitiveness of enterprises. POP system toward the future with the new destroyer to prepare for our company. Collectively POP system build this research improves the reliability of the product. Improves the quality of customer service. The expansion of product sales is. increase the competitiveness of enterprises. companies should prepare for the future of the business.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.80-88
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• 2019

Recently, automobile manufacturing companies, which are major customers of them, are requiring IATF 16949 (ISO/TS 16949) certification as a mandatory requirement to secure product quality. In particular, IATF 16949 : 2016, revised in October 2016, was reinforced product traceability requirements for production information management by lot in the production process. Therefore, small and medium-sized precision parts processing companies in the automobile industry are very difficult to survive due to quality and price competition for customers satisfaction. MES (Manufacturing Execution System) is required to solve this problem. However, small and medium sized precision parts processing enterprises are reluctant to introduce the MES which is not suitable for the manufacturing environment of them such as high cost and low utilization. Even if the system is introduced, it is difficult to operate and maintain the system because the lack of computer manpower. In this paper, we propose a method for building a lot tracking system for small and medium precision parts processing companies by reviewing relevant literature and analyzing cases. In addition, by managing the production history for each lot of the final product in the system, we will grasp the effect of reducing the quality failure cost obtained by minimizing the range of defect selection.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.3 s.147
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• pp.392-398
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• 2006

A prototype of MES(Manufacturing Execution System) applied to panel assembly shop is implemented by using PDA(Personal Digital Assistant) and wireless database web server. The system is developed based on the Dot Net framework. The prototype can exchange the manufacturing execution data between production managers in the control room and workers in the factory through wireless internet communication. Manufacturing model of the panel shop is designed by using IDEF0 and UML method to understand the characteristics of the information and the data entities from the PPR-S view. Several issues in the shop were revealed from the manufacturing model analysis. The most typical problem was the lack of information sharing between the managing workers and the assembly workers. The problem prevents the workers and labors from sharing the process information and continuous workpiece flow In interactive way. To increase the information and data flow, a wireless internet based system is implemented and PDAs are linked together to exchange the process planning data and in-process data between the workers. It is anticipated that PDA and the implemented system can enable the process control at each process stages to obtain the well-organized operation.

• Information Systems Review
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• v.19 no.2
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• pp.95-113
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• 2017

The advent of information communication technology or the Fourth Industrial Revolution facilitated the fusion of equipment and management systems, such as Manufacturing Execution System, Enterprise Resource Planning, and Product Lifecycle Management, in the successful implementation of smart factories. The government supports the early adoption of these systems in small and medium companies to enhance their global competitiveness in producing products that can be recognized in a dramatically changing manufacturing environment. This study introduces smart factories to improve company competitiveness and address influences from the government assistance, CEO leadership, external consultancy, and organizational participation. We analyzed 101 results received from the questionnaires circulated to small- and medium-sized manufacturing companies. Given a successful smart factory implementation, company competitiveness is the factor that mostly influences organizational participation, government assistance, external consultancy, and CEO leadership. This study suggests several perspectives to implement a smart factory, which is the most important aspect of company competitiveness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.463-466
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• 2004

본 연구는 조선 LNG선의 탱크를 제작하는 공장의 관리 및 운영을 지원하는 제조실행 시스템(MES : Manufacturing Execution Sys- tem)의 개발에 대한 내용이다. 본 연구대상 공장에는 가공과 조립라인이 있으며, 가공라인에서는 소재를 가공하고, 조립라인에서는 가공된 소재를 가공하고, 조립라인에서는 가공된 소재를 용접으로 최종 조립한다. 본 연구 대상 공장의 주요 관리 및 운영에 대한 관점은 장비의 고장 방지와 효율극대화, 납기 준수 및 최종 용접 후 결함 최소화 등이다. 이에 본 연구에서는 공장을 체계적으로 관리 운영하기 위해 공정관리와 장비관리 기능을 통합한 제조실행 시스템을 개발하였다. 공정관리는 일정계획 수립, 관리에서부터 작업자 배치 및 입${\cdot}$출고 관리 등의 역할을 수행하고, 장비관리는 장비 모니터링, 장비와 작업 이력 데이터 추출 및 집계, 장비보전 관리, 장비별 작업지시 등의 역할을 수행한다. 본 연구의 개발 시스템은 MSSQL Sever 데이터베이스와 Visual Basic, C++ Builder로 개발되었다.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.4
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• pp.262-271
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• 2013

Owing to the development of mobile communication technology during the last a few years, the number of users of mobile devices such as the smartphone and the tablet PC has increased rapidly. As a result, the range of applications of the mobile devices has also been greatly expanded from an application for the convenience of daily life to an application for assisting the operations of industrial fields. Especially, portability of mobile devices can provide great help in collecting and using information on the production site. In shipbuilding production processes, it is difficult to collect changes of circumstance in the field and reflect the changes to schedule due to the low production automation rate and frequent changes in schedule. In this study, we propose a system to solve the problems of shipbuilding production processes such as the ones described above by using mobile devices. First of all, we organize the production information and production processes of the panel line through the analysis of shipyard panel line operations. Next, we have developed a system that can support the production execution plan of the panel line and monitor the production processes in the field. The system was developed utilizing application virtualization to allow access to the system from various platforms of mobile devices and PC's. The system was implemented using ooCBD methodology considering the future expansion of the system and ease of maintenance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.627-633
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• 2020

Assembly process data can be gathered in real time in a manufacturing execution system (MES) server using proximity sensors, barcodes, RFID, ZigBee, Bluetooth, wireless sensor networks, etc. Although this is suitable for identifying process flow and checking production progress, it is difficult to trace the location of individual workers in real time for missing work or trajectories within the work area. To overcome this, the location and trajectory of the working tool can be analyzed in real time through a position tracking system of an operator's working tool. It can instruct the operator to perform a consistent working process. Productivity and quality improvement can be achieved by an alarming or blocking operator with possible assembly defects during the assembly process in real time. To this end, we developed a real-time tool position-tracking sensor system based on Ultra Wide Band (UWB) trilateration using a Kalman filter to eliminate mechanical vibration and radio communication noise.