• International journal of advanced smart convergence
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• v.13 no.2
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• pp.265-275
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• 2024

Smart factory is a remarkable development from traditional manufacturing systems to data-based smart manufacturing systems that can connect and process data continuously, collected from machines, production equipment to production and business processes, capable of supporting workers in making decisions or performing work automatically. Smart factory is the key and center of the fourth industrial revolution, combining improvements in traditional manufacturing activities with digital technology to help factories achieve greater efficiency, contributing to increased revenue and reduce operating costs for businesses. Besides, the importance of smart factories is to make production more quality, efficient, competitive and sustainable. Businesses in Vietnam are in the process of learning and applying smart factory models. However, the number of businesses applying the pine factory model is still limited due to many barriers and difficulties. Therefore, in this paper we conduct a survey to assess the needs and current situation of businesses in applying smart factories and propose some specific solutions to develop and promote application of smart factory model in Vietnamese businesses.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.165-177
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• 2018

Smart technology has been utilized in various fields of all kinds of industries. Manufacturing industry has built its smart technology environment appropriate for its manufacturing fields in order to strengthen its manufacturing performance and competitiveness. The advance of smart technology for manufacturing industry needs to efficiently produce products, and response customer's demands and services in a global industrial environment. The smart technology capability of manufacturing fields is very crucial for the innovative production and efficient operation activities, and for efficient advancement of the manufacturing performance. We have necessitated a scientific and objective method that can gauge a smart technology ability in order to manage and strengthen the smart technology ability of manufacturing fields. This research provides a comprehensive framework that can rationally gauge the smart technology capability of manufacturing fields for effectively managing and advancing their smart technology capabilities. In this research, we especially develop a structural framework that can gauge the smart technology capability for a smart factory of manufacturing fields, with verifying by reliability analysis and factor analysis based on previous literature. This study presents a 13-item framework that can measure the smart technology capability for a smart factory of manufacturing fields in a smart technology perspective.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.982-986
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• 2005

Digital Manufacturing is a technology to facilitate effective product developments and agile productions by digital environments representing the physical and logical schema and the behavior of real manufacturing system including manufacturing resources, processes and products. A digital virtual factory as a well-designed and integrated environment is essential for successful applications of this technology. In this research, we constructed a sophisticated digital virtual factory by measuring and 3-D CAD modeling using parametric methods. Specific parameters of each objects were decided by object-oriented schema of the digital factory. It is expected that this method is very useful for constructions of a digital factory, and helps to manage diverse information and re-use 3D models.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.78-83
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• 2007

In this paper, the digital model of the micro-factory has been established, inspected and evaluated by progress of assembly, manipulation and examination. The new paradigm of the system analysis is realized by digital simulation of the factory. The digital manufacturing system of the micro-factory was simulated through UML(Unified Modeling Language) with the object-oriented logical model analysis method and then the micro lens module assembly system was simulated with MST(Micro System Technology) Application Module.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.252-261
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• 2019

In this study, we analyzed the factors affecting the introduction of Smart Factory by domestic SMEs through AHP analysis and tried to provide implications for the introduction of Smart Factory. It was confirmed that the manufacturing and introduction group, the non-manufacturing introduction group, and the already introduced group had the highest weight in the cost reduction in the first hierarchy standard. At this time, it can be seen that the weight for cost reduction is relatively high in the manufacturing introduction group and the introduction group, and the weight for the productivity improvement is relatively high in the non-manufacturing introduction group. It can also be seen that the portion of marketing enhancement does not have a significant impact on smart factory choices. It was confirmed that image enhancement is the highest in the manufacturing introduction group and the non-manufacturing introduction group in the first hierarchy standard, and the marketing has the highest weight in the introduction group. In the two - tiered standard, customer - friendly and proper inventory maintenance weights were relatively high in all the introduced groups, except for the high rankings.

• IE interfaces
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• v.18 no.1
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• pp.94-103
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• 2005

Digital Manufacturing is a technology to facilitate effective product developments and agile productions by digital environments representing the physical and logical schema and the behavior of real manufacturing system including manufacturing resources, processes and products. A digital factory as a well-designed and integrated environment is essential for successful applications of this technology. In this research, we constructed a sophisticated digital factory of an automotive company’ general assembly shop by measuring and 3-D CAD modeling using parametric methods. Specific parameters of each objects were decided by object-oriented schema of the general assembly shop. It is expected that this method is very useful for constructions of a digital factory, and helps to manage diverse information and re-use 3D models.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.135-142
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• 2022

The smart factory is an important system that can reduce defects, maximize productivity, and respond to customer needs, from the labor-intensive era of traditional small and medium-sized manufacturing companies through the automation era to CPS using ICT. However, small and medium-sized manufacturers often fall short of the basic stage due to economic and environmental constraints, and there are many companies that do not even recognize the concept of a smart factory. In this situation, to expand the smart factory of small and medium-sized enterprises, the project to support the establishment of a smart factory for the win-win between large and small enterprises. The win-win smart factory construction support project provides a customized differentiation program support project according to the size and level of the company for all domestic manufacturing SMEs regardless of whether or not they are dealing with Samsung. In this study, we analyze the construction status and introduction performance of companies participating in the win-win smart factory support project to find out whether they have been helpful in management and to find efficient ways to improve support policies, and to suggest the direction of continuous support projects to improve the manufacturing competitiveness of SMEs in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.204-206
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• 2022

Digital twin, which is evaluated as the core of smart factory advancement, is a technology that implements a digital replica in the virtual world with the same properties and functions of assets in the real world. Since the smart factory to which digital twin is applied can support services such as real-time production process monitoring, production process simulation, and predictive maintenance of facilities, it is expected to contribute to reducing production costs and improving productivity. AAS (Asset Administration Shell) is an essential technology for implementing digital twin and supports a method to digitally represent physical assets in real world. In this paper, we design AAS for manufacturing data gathering to be used in real-time CNC (Computer Numerical Control) monitoring system in operation by considering manufacturing facility in smart factory as assets.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.189-196
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• 2016

The ultimate goal of this study is to investigate the cases with respect to smart factory that has been introduced by German government. To do this, the study suggest implications for manufacturing version 3.0 that is one of manufacturing revolution agendas in Korea. The main point of smart factory is the convergence between manufacturing and information and communications technologies such as CPS(Cyber-Physical Systems), MES(Manufacturing Execution Systems), 3D Printer, AI(Artificial Intelligence), and so forth. It is hard to accomplish a complete manufacturing automation. In fact, German government had experienced the failure in pursuing the smart factory agenda. But now the agenda is gradually realized by a variety of success stories from German. Thus, this study is to investigate the well-known success stories that came from German.