• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.227-234
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• 2020

This paper introduces the state definition and diagnostic algorithm for autonomic control of manufacturing facilities. Smart factory systems through cyber-physical systems and digital twin technology are increasing the productivity and stability of existing manufacturing plants, which has become an issue recently. A Smart factory system is one of the key technologies that make up a smart factory system, to improve productivity, enable workers to make better decisions, and to control abnormal process flows. However, performing an autonomic control process based on large number of integrated plat data requires significant advance work. Therefore, in this paper, we define an abstracted facility state for manufacturing facility autonomic control and propose an algorithm to diagnose the current state. This makes the autonomic control process simpler by autonomic control based on the facility status rather then integrated facility data.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.19-25
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• 2021

This study proposes a digital twin implementation method through simulation so that the manufacturing process can be optimized in a manual manufacturing site. The scope of the proposal is a knowledge management mechanism that collects manual motion with a sensor and optimizes the manufacturing process with repetitive experimental data for motion recognition. In order to achieve the research purpose, a simulation of the distribution site was conducted, and a plan to create an optimized digital twin was prepared by repeatedly experiencing the work simulation based on the basic knowledge expressed by the worker's experience. As a result of the experiment, it was found that it is possible to continuously improve the manufacturing process by transmitting the result of configuring the optimized resources to the physical system by generating the characteristics of the work space configuration and working step within a faster time with the simulation that creates the digital twin.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1467-1482
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• 2017

Recently, Interests on The Fourth Industrial Revolution has been increased. In the manufacturing sector, the introduction of Smart Factory, which automates and intelligent all stages of manufacturing based on Cyber Physical System (CPS) technology, is spreading. The complexity and uncertainty of smart factories are likely to cause unexpected problems, which can lead to manufacturing process interruptions, malfunctions, and leakage of important information to the enterprise. It is emphasized that there is a need to perform systematic management by analyzing the threats to the Smart Factory. Therefore, this paper systematically identifies the threats using the STRIDE threat modeling technique using the data flow diagram of the overall production process procedure of Smart Factory. Then, using the Attack Tree, we analyze the risks and ultimately derive a checklist. The checklist provides quantitative data that can be used for future safety verification and security guideline production of Smart Factory.

• The Journal of Information Systems
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• v.26 no.2
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• pp.105-121
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• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.59-69
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• 2018

This study deals with the case study on the pallet quantity determination problem for the flexible manufacturing system producing 32 different types of aircraft wing ribs which are major structures of an aircraft wings. A Korean company has constructed the WFMS (wing rib flexible manufacturing system) that is composed of several automated equipments such as the 5-axis machining centers, the RGV (rail guided vehicles)s, the AS/RS (automated storage and retrieval system), the loading/unloading stations, and so on. Pallets play a critical role in the WFMS to maintain high system utilization and continuous work flow between 5-axis machining machines and automated material handling devices. The discrete event simulation method is used to evaluate the performance of the WFMS under various pallet mix alternatives for wing rib manufacturing processes. Four performance measures including system utilization, throughput, lead-time and work in process inventory level are investigated to determine the best pallet mix alternative. The best pallet mix identified by the simulation study is adopted in setting up and operating a real Korean aircraft parts manufacturing shop. By comparing the real WFMS's performances with those of the simulation study, we discussed the cause of performance difference observed and the necessity of developing the CPS (cyber physical system).

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.29-34
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• 2017

The operating environments of factories and manufacturing units have changed dramatically due to globalization, population, and customization. The existing factories are converted into smart units using information and communications technology (ICT). These smart factories can produce, control, repair, and manage themselves. The manufacturing processes are efficiently optimized using the monitoring and analysis methods of ICT. In this experimental study, we carried out a survey on the system solution providers and consumer companies to determine the field conditions and requirements necessary for assembling a smart factory. Using the results of this survey, we effectively devised smart factory solutions and implemented them on the existing conditions in various factories.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2491-2502
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• 2015

Main issue for embodiment of smart factory in small-medium manufacturing business(SMMB) is to whether might be successful or not in achieving a goal, exact materializing for smart factory related technology, and in seeking possible solutions for limited capacity to invest and develop technology. It is required for effective driving of manufacturing innovation 3.0 paradigm that ensures expertise to push forward technology policy based on value chain level of SMMB, and ensures detailed action plans by investment priority and development of core technology against global trend. This paper focuses to suggest countermeasure strategy and task through analysis of advanced technology and patent trend about industrial IoT(IIoT) and cyber physical system(CPS), and support embodiment of smart factory in underlying manufacturing innovation 3.0 scheme.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.1-10
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• 2016

In this paper, we consider the algorithms and numerical analysis for real-time integrated control system and resource management of large-scale manufacturing smart factory system. There various data transmitted on Cyber-Physical-System (CPS) is necessary to control in real time, as well as the terminal and the platform with respective system service. This will be a true smart manufacturing which consisting of existing research results, and a numerical analysis by the parameter-specific information. In this paper, Jacoby calculation to reflect the optimization algorithms that are newly proposed. It also presents a behavior that optimal operational algorithm on CPS which is adapted to the sensing data. In addition, we also verify the excellence of the real-time integrated control system through experimentation, by comparison with the existing research results.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.11-20
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• 2020

As the manufacturing environment becomes more complex, traditional simulation models alone are having a lot of difficulties in reflecting real-time manufacturing situations. Although the Digital Twin concept is actively discussed as an alternative to overcome theses issues, many studies are being carried out only in the product design phase. This research presents a Digital Twin-based manufacturing environment framework for applying the Digital Twin concept to the manufacturing process. Twin model that is operated in virtual space, physical system and databases describing the actual manufacturing environment, are proposed as detailed components that make up the framework. To check the applicability of proposed framework, a simple Digital Twin-based manufacturing system was simulated in a conveyor system using Arena software and Excel VBA. Experiment results have shown that the twin model is transmitted real time data from the physical system via DB and were operating in the same time unit. The Excel VBA fitted parameters defined by cycle time based on historical data that real-time and training data are being accumulated together. This study proposes operating method of digital twin model through the simple experiment examples. The results lead to the applicability of Digital twin model.

• 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.