• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.311-319
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• 2015

In this paper, in order to increase the production efficiency of the industrial plant, and predicts the resources of the manufacturing process, we have proposed a decision-making system for resource implementing the risk management effectively forecasting and risk management. A variety of information that occurs at each step efficiently difficult the creation of detailed process steps in the scenario you want to manage, is a frequent condition change of manufacturing facilities for the production of various products even within the same process. The data that is not contiguous products production cycle also not constant occurs, there is a problem that needs to check the variation in the small amount of data. In order to solve these problems, data centralized manufacturing processes, process resource prediction, risk prediction, through a process current status monitoring, must allow action immediately when a problem occurs. In this paper, the range of change in the design drawing, resource prediction, a process completion date using a regression algorithm to derive the formula, classification tree technique was proposed decision system in three stages through the boundary value analysis.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.191-204
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• 2024

This study analyzes the effects of manufacturing firms' R&D investment on sales according to global political economic uncertainty. The variables in this research include the firm's R&D investment, sales, which serves as an indicator of the firm's performance, and the Global Economic Policy Uncertainty (GEPU) index, which reflects situations of global political economic uncertainty. Panel data analysis is conducted by using a total of 96 quarters of data spanning 24 years from 2000 to 2023 based on manufacturing firms in the Wharton Research Data Services' Compustat Database. We study the impact of firm's R&D investment on sales by considering the Global Economic Policy Uncertainty index, which was relatively underestimated in previous research, as moderating variable, and present a new direction for research by analyzing the time lag effect. We suggest effective R&D investment strategy for firms.

• Information Systems Review
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• v.20 no.1
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• pp.81-98
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• 2018

ERP supports the automation and integration of business processes of enterprises and records voluminous data about the business activities of enterprises. The academe and business enterprises are focusing on process mining, which improves the performance of business processes and strengthens compliance. However, these studies focused on analysis of the business process of large companies, which adopts foreign ERP, such as SAP ERP or Oracle ERP. In comparison with foreign ERP, domestic ERP lags behind in terms of logging and managing of event data. Therefore, the application of process mining to domestic ERP is a challenging task. The present study aims to analyze domestic ERP based on process mining to overcome this challenge. This study discusses the lessons learned from a case study in a Korean cosmetics manufacturing company. Our results are expected to strengthen the competitiveness of Korean small and medium-sized enterprises that adopt domestic ERP and realize the outcomes of the large investment of the Korean government on the ERP implementation of enterprises.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.264-267
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• 2008

본 논문에서는 TFT-LCD 생산 라인에서의 시스템 통합에 필요한 데이터 프레임 포맷 표준화 방안을 연구하였다. 이를 위해 TFT-LCD 생산 라인을 구축 하는데 있어서 Glass 반송 작업에 필요한 데이터 프레임 구조 및 32개의 Word로 구성된 데이터 필드를 정의하였다. 시스템 통합에 필요한 표준화된 Glass 데이터 프레임 포맷을 사용함에 따라, 각 장비 제조사의 시스템 설계 기간 단축, 비용 절감, 셋업 기간 단축 등의 효과를 기대할 수 있다고 본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1177-1180
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• 2014

본 논문은 생산설비 PLC(Programmable logic Controller) 데이터의 실시간 공유 플랫폼을 설계한다. 이 플랫폼은 자동화 설비를 보유하고 운영 중인 수출집약 중소기업에서 FTA(Free Trade Agreement) 체결 수입 상대국의 원산지 증명을 위한 생산 시험성적서 제출에 활용할 수 있고, 생산설비의 OPC 서버가 갖는 실시간 데이터를 수집하는 라이브러리를 활용하여 MES(Manufacturing Execution System)에서 생성되는 다양한 실시간 데이터를 활용하여 그래프, 생산관리 모니터링 및 설비 관리를 가능케한다. 따라서 중소기업이 생산관리, 공정관리, PLC 데이터공유 등에 필요한 수준별 분야별로 실시간 제조운영관리 시스템의 확대 보급이 가능하고, 생산설비의 실시간 제어가 가능하도록 설계한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.958-961
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• 2015

코팅제는 다양한 산업 분야에서 중요성이 더욱 커지고 있으나 실제 제조업체에서는 여전히 작업자의 경영에 의존하여 배합공정을 수행하는 실정이다. 본 논문에서는 R과 실험계획법을 이용하여 코팅제 배합 공정을 분석하기 위한 프레임워크를 제안한다. 제안된 프레임워크를 통한 분석 결과는 보다 정량적인 작업 기준 데이터를 확보하고 작업 현장에 제공함으로써 코팅제 배합 공정을 개선시킬 수 있다. 특히 정확한 배합 기준이 되는 표준 데이터의 부재로 인한 품질 저하와 원가 손실을 감소시키고, 배합 공정에서 발생한 오차 데이터에 대하여 R과 실험 계획법을 이용한 분석을 통하여 표준 보정 관계식을 도출함으로써 차후 발생 가능한 오차에 대한 대응 방안을 제시할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.507-509
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• 2022

In order to collect vehicle internal diagnostic data, it is necessary to collect diagnostic data of ECU (Electronic Control Unit) included in various automotive parts. Diagnostic communication can be used to collect diagnostic data of ECU. In this paper, the method of collecting diagnostic data according to ECU function through standard diagnostic communication and the diagnostic communication module were analyzed. Among the standard modules of AUTOSAR, a standard for automotive electronics used by many automobile manufacturers, the diagnostic communication module was studied, and the process of diagnostic data processing through ECU was studied.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.113-117
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• 2022

Additive manufacturing (AM, also known as 3D printing) technology is digitalized technology, making it easy to predict and manage quality and also, have design freedom ability. With these advantages, AM technology is applied to various industries. In particular, a method of manufacturing buildings and infrastructure with AM technology is being proposed to the construction industry. However, the application of AM technology is restricted due to problems such as insufficient history and quality of technology, lack of construction management methods, and certification of manufacturing products. Therefore, the manufacture of architectural products is implemented with indirect AM technology. In particular, it manufactures formwork using AM and injecting building materials to implement the architectural product. In this study, hybrid type material extrusion AM is used to manufacture large-sized formwork and implement building products. Moreover, we identify factors that can predict productivity and economic feasibility in the additive manufacturing process. As a result, design optimization results are proposed to reduce the production cost and time of architecture buildings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.237-244
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• 2018

The Smart Factory level of manufacturing factories of SMEs now lacks a system for grasping the accurate inventory amount associated with inventory movements in managing warehouses at the basic level. Also, it is difficult to manage accurate materials for loss of data due to worker manual work and production method due to experience. In order to solve this problem, in this paper, automatic acquisition of inventory to minimize manual work to grasp workers' Inventory and improve automation is done. In the smart warehouse management system using the IoT-based autonomous mobile module, the autonomous mobile module acquires the data of the inventory storage while moving through the line. In order to grasp the material of the Inventory storage, The Camera module recognizes the name of the inventory storage. And Then, If output matches, the data measured by the sensor is transferred to the server. This data can be processed, saved in a database, and real-time inventory quantity and location can be grasped in a web-based monitoring environment for administrators. The Real-time Automatic Inventory (RAIC) systems is reduce manual tasks and expect the effects of automated inventory management systems.