• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.168-173
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• 2022

As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.153-156
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• 2005

Real-time monitoring and controlling manufacturing process is important because of the unexpected events. When unexpected event like mechanical trouble occurs, prior plan becomes unacceptable and a new schedule must be generated though manufacturing schedule is already decided for order. Regenerating the whole schedule, however, spends much time and cost. Thus automated system which monitors and controls manufacturing process is required. In this paper, we present a system which uses radio-frequency identification and computer vision system. The system collect real-time information about manufacturing conditions and generates new schedule quickly with those information.

• Korean Management Science Review
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• v.10 no.2
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• pp.121-143
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• 1993

Traditional Manufacturing method is push system by plan made in advance and Japanese manufacturing method represented by JUST-IN-TIME is pull system which respond's to the demand flexibly. Both have their pros and cons. In general, it is well understood that push system is faster than pull system in the sense of manufacturing speed. However, pull system such as JIT excelles dramatically in the sense of work in process. Therefore, this paper is trying to put together to get alternative which has the advantage of both system. The objective of the paper is to enhance the effect of built-in manufacturing system without paying extra cost by way of introducing the alternative of the pull-push manufacturing strategic operational method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.269-272
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• 2004

The target of this paper is the development of Web-based monitoring & control system which is for effective and economic management of mold manufacturing process. This system has three module; G-code Control, Monitoring Module and Result analysis module. Also, as the environment of development is based on internet, this system which is possible to the remote site management of manufacturing process works on Web. To be possible to control the manufacturing monitoring by client, each module is made ActiveX control and is based on socket communication. This system makes the foundation which is possible to manage the mold manufacturing process efficiently from remote site by matching real-time monitoring with manufacturing process in factory using G-code control and displaying the result of manufacturing using Ch-CGI.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.17-27
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• 2014

The number of manufacturing companies that demand the ability to assess sustainability in their manufacturing system is rapidly increasing. However, there are still difficulties in assessing their sustainability in manufacturing for decision-making since it is not easy to determine a single index of sustainability in an operational way. To address these difficulties, this paper proposes an operational guidance and system to assess sustainability of production plan as a single index. The IDEF0 model was defined to explain processes and their input, output, control, and mechanism for sustainability assessment. A prototype system was developed based on the concepts presented in the IDEF0 model, and applied to a case study. To conclude, the prototype system proposed in this paper can help manufacturing companies assess sustainability of their production plans and make a decision using a single value resulted from that assessment.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.201-210
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• 2007

The purpose of this study is to investigate the status of manufacturing information system (MIS) which has been introduced to enhance the manufacturing competitiveness in Korea and to enable statistical comparison of whether there are significant differences in implementing manufacturing information system between large companies and small and medium enterprises (SMEs). The result of the empirical test of 105 manufacturing companies in Korea showed that the utilization and satisfaction of MIS in large companies are significantly greater than those in SMEs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.267-284
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• 2008

Consider a supply chain where products are produced at a manufacturing system, shipped to a distribution center, and then supplied to customers. The distribution center controls inventory based on a base-stock policy, and whenever a unit of product is demanded by a customer, an order is released to the production system. Unsatisfied demand is backordered, and the inventory and backordered units are a function of the base-stock level. The manufacturing system is modeled as an M/M/s/c queueing system, and orders exceeding the limited buffer capacity are blocked and lost. The throughput of the manufacturing system and the steady state distribution of the outstanding orders are functions of number of servers and buffers of the manufacturing system. There is a profit obtained from throughput and costs due to servers and buffers of the manufacturing system, and also costs due to inventory positions of the distribution center, and we want to maximize the total production profit minus the total cost of the supply chain by simultaneously determining the optimal number of servers and buffers of the manufacturing system and the optimal base-stock level of the distribution center. We develope two algorithms, one analytical but without guarantee of the optimal solution and one optimal but without complete analytical proofs. The problem integrates strategic problem of the manufacturing system with tactical problem of the distribution center in a supply chain.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.27-31
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• 2003

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.311-317
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• 2014

As products have been more complex and customer's demands of personalized products are increasing, manufacturing system has been changed from mass production to mass customization production that makes small quantity but different kinds of product. In addition, it becomes important that manufacturers quickly respond to variable customer's demands and characteristic regulations in each country. Therefore, three prerequisites are essential for manufacturers to response agilely. First, manufacturing data should be monitored in real time, second, information is extracted from the data, and finally, the information is used to make manufacturing strategy. In this paper, the mobile dashboard system is presented. It visualizes manufacturing data on mobile devices, and measures performance of the shop floor through the information. The proposed system is composed of server and client, and is running on the R - the open source software for statistics. Four kinds of template are given for easy visualization through the system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1001-1005
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• 2004

The objective of this paper is to develop the flexible manufacturing system (FMS), which is cooperated with the automatic warehouse and inventory control under holonic manufacturing system (HMS). The HMS is a next wave of manufacturing revolution to deal with dynamic changing. The architecture of HMS is developed for cooperation system between the automatic warehouse agents and the manufacturing agents. This research applies the concept of HMS to develop a distributed control system for automatic warehouse and FMS by industrial network. The parts of prototype manufacturing agents consist of the conveyer system and 3-axises robot that provide the variety patterns in order to work as punch process. Each order of productions depends on the reorder points(RP) of inventory levels. The computation results indicate an improvement by comparing with traditional centralized control.