• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.211-221
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• 2006

Manufacturing Execution System(MES) immediately enables users to share the information of systems industrywide, efficiently manages synthetic information with data collection through treating the data in a fast way, and helps their decision-making. MES for real-time information processing requires certain conditions such as data modeling of RFID, which has recently attracted attentions, and monitoring of each product unit from manufacture to sales. However, in the middle of processing the unit with a RFID tag, transponders(readers) can't often read the tag due to reader's malfunctions, intentional damages, loss and the circumstantial effects; for that reason, users are unable to confirm the location of the product unit. In this case, users cannot avoid tracing the path of units with uncertain clues. In this paper we suggest that the unique MES based on RFID and Bayesian Network can immediately track the product unit, and show how to evaluate it.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.17-18
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.489-490
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• 2010

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.22-33
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• 2018

Recently domestic manufacturing companies have been experiencing worsening profitability and stunted growth due to the long-term economic recession and the rapid rise of developing countries such as China and Southeast Asia. These difficulties force many companies to concentrate their core competencies on new value creation and innovation in order to gain momentum for new growth. Enterprise Resource Planning (ERP) has been considered as one of viable solutions. Among the various modules in ERP, shop floor control function in the production management module is rather limited. In order to overcome this problem, Manufacturing Execution System (MES) has been used as a subsystem which has a strong information gathering power and flexibility. Both systems interact closely with each other. In particular, ERP requires fast, accurate shop floor information at MES. This paper describes how to synchronize relevant information between ERP and MES with theory of constraints (TOC). The processing time information transmitted from the MES workplace is received at the ERP workplace. In the process, the received processing time is causing information distortion in ERP, when the information gathering standard of MES is different from the ERP information interpretation standard. The Drum-Buffer-Rope theory of TOC was applied to resolve this problem, therefore, information synchronization between both systems was made. As a precondition, the standard time of the upper ERP system was rearranged according to the capacity constraints resource. As a result, standard time restructuring has affected changes in labor costs. Standard labor costs have come close to actual ones, and information synchronization of MES transmission data has improved the reliability of standard product costs, such that it enabled various company-wide restructuring actions to be much more effective.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.295-300
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• 2014

In information society, Convergence was combined with a word 'digital'. Digital convergence means a service or new product which appeared through fusion of unit technologies in information and communication regions. The effects of convergence technologies and social phenomenons are visualized in overall regions of society such as economy, society, culture, etc. Nowadays, manufacturing field are facing new challenges, through digital information and global integration, toward sophisticated production. This paper presents the system configuration and issues of current manufacturing execution system(MES), and describes major issues and solving elements to establish a MES system for cloud services. Also, we propose a method for building a manufacturing information system to have the optimized production flow and to respond appropriately to consumer market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4618-4625
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• 2011

This paper suggests a specific model that could efficiently improve the interaction and the interface between MES(Manufacturing Execution System) server and POP(Point Of Production) Terminal through RFID(Radio Frequency Identification) system in Automative Module Assembly Line. The proposed model shows that the new method by RFID can more efficiently perform to receive work order informations and transmit work performances, compared with the current approach by proximity sensor. As a result of the certain test among the MES server, RFID system, PLC(Programmable Logic controller) and POP terminal, it is noted in case of the automatic control by RFID that the effects of proposed model are as follows; (a) While the processing time per truck for carrying by the current method was 10 minutes, the processing time by the new method was 1 minutes. (b) While the error rate by the current method was 20 %, the error rate by the new method was 1 %.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.1017-1022
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• 2002

국내외 여러 지역에 공장을 가동하고 있는 제조업체의 경우, 단위 공장의 가동 상황을 통합하여 전체적으로 모니터링하고 관리해야 할 필요성이 증대되고 있으나, 기존 제조실행시스템은 이러한 요구를 반영하지 못하고 있어, 이를 극복하기 위한 방안으로 개별 공장의 각 제조실행 시스템과 연동하면서 전체 공장의 가동 현황을 통합하여 인터넷/웹 기반에서 실시간으로 모니터링할 수 있는 시스템을 제시하였다. 본 논문에서 제시된 시스템 구조, 수행 기능과 관리해야 할 DATA는 상당한 표준화과정을 거쳤으며, 타 제조업체에서도 활용이 가능할 것이다.

• Journal of the Korea Safety Management & Science
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• v.18 no.3
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• pp.147-154
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• 2016

This paper suggests a specific model that could efficiently improve the interaction and the interface between MES(Manufacturing Execution System) server and PDA terminal through RFID(Radio Frequency Identification) system and bar-code system in automative transmission shipment place of the finished assembly parts. The proposed model shows that the new method by RF-Tag system can more efficiently perform to reduce processing time and loading time for shipment, compared with the current approach by bar-code system. It is noted in case of the method by RF-Tag that the effects of proposed model are as follows; (a) While the shipping lead time per truck for carrying by the current method was 35 minutes, the shipping lead time by the new method was 15 minutes. (b) While the accuracy for carrying by the current method was 50%, the accuracy by the new method was 99%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Design & Manufacturing
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• v.15 no.2
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• pp.42-48
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• 2021

In this paper, when manufacturing large/multi-mold parts (more than 30 core parts),A mold manufacturing (tolerance) management system was established through design-processing linkage.The mold manufacturing (tolerance) management system is a design-based measurement shape/measurement position determination system, M/C processing-linked measurement drive system,It is composed of four parts: CAD-linked measurement result analysis system and manager mold part quality management system.In addition, the constructed system was applied to the field and the effect of system construction was evaluated by comparing it with the existing process.As a result of the evaluation, the measurement precision is within 0.02mm, and the time it takes to measure after the end of processing is shorter than that of the existing process.(12 hours → 2 hours) It was shortened to 16.7%.In addition, it was confirmed that the time required for reprocessing after measurement was reduced by 25% (4 hours → 1 hour) compared to the existing process.