• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.610-619
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• 2016

Digital manufacturing (DM) technology helps engineers design products promptly and reliably at low production cost by simulating a manufacturing process and the material behavior of a product in use, based on three-dimensional digital modeling. The computing infrastructure for digital manufacturing, however, is usually expensive and, at present, the number of professional design engineers who can take advantage of this technology to a product design accurately is insufficient, particularly in small and medium manufacturing companies. Considering this, the Korea Institute of Science and Technology Information (KISTI) and H University is operating a DM track in the form of Industry-University-Research Institute collaboration to train high-performance-computing-based DM professionals. In this paper, a series of courses to train students to work directly into DM practice in industry after graduation is reported. The operating cases of the DM track for two years since 2013 are presented by focusing on the progress in establishment, lecture and practice contents, evaluation of students, and course quality improvement. Overall, the track management, curriculum management, learning achievement of students have been successful. By expediting more active participation of the students in the track and providing more internship and job offers in the participating companies in addition to collaborative capstone design projects, the track can be expanded by fostering a nationwide training network.

• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.138-147
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• 2014

In manufacturing companies, different types of production have been developed based on diverse production strategies and differentiated technologies. The production systems have become smart, factories are filled with unmanned manufacturing lines, and sustainable manufacturing technologies are under development. Nowadays, the digital manufacturing technology is being adopted and used in manufacturing industries. When this technology is applied, a lot of efforts, time and cost are required and training professionals in-house is limited. In this paper, we introduce e-FEED system (electronic based Front End Engineering and Design) that is the integrated design and analysis system for optimized manufacturing line development on virtual environment. This system provides the functions that can be designed easily using library and template based on standardized modules and analyzed automatically the logistic and capacity simulation by one-click and verified the result using visual reports. Also, we can review the factory layout using automatically created 3D virtual factory and increase the knowledge reuse by e-FEED system.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.71-80
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• 2011

Gyeongnam province is well known for its high concentration on machinery manufacturing industry. However, this province is losing competitive advantage due to the lack of IT S/W industry. In this paper, we propose a way for adoption of u-Manufacturing technology to promote IT S/W industry in Gyeongnam. At first, we identified the needs of manufacturing companies and the capabilities of the IT S/W companies with survey. Based on the survey analysis, then we set up the u-Manufacturing concept and proposed Manufacturing IT middleware to support it. Finally, we proposed a strategy to promote smoothly the adoption of u-Manufacturing technology in this area.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.69-70
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• 2007

• Journal of Digital Convergence
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• v.12 no.1
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• pp.305-311
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• 2014

The manufacturing industry early have been introducing automation and information systems of the engineering and production process for getting competitive advantage. one of the typical information systems is MES(Manufacturing Execution System) and it keeps evolving. As Big Data showed up nowadays, application method of Big Data to MES is also being sought. First, this study will do preceding research and cases study on the application of Big Data in the manufacturing industry. Then, it will suggest application Plan of Big Data to MES.

• IE interfaces
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• v.23 no.2
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• pp.182-192
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• 2010

Customer needs for final products are very unpredictable because product specifications and technologies are being improved very quickly thereby their requirement level is also elevated correspondingly. In order to survive and to enhance competitiveness in the global market, many manufacturing companies are trying to find a breakthrough from collaborization. Even though they want to collaborate with others, however, they do not exactly know what kind of system they have to develop or which technology they have to use. In this paper, therefore, we first investigate status and trend of information systems and infrastructure that are essential for collaboration. We then clearly describe definition and classification of collaboration with various point of views considering collaboration pattern, timing condition of collaborative activities, organizational structure, etc. With web-based collaboration systems already developed by i-Manufacturing (Korean-style Manufacturing Innovation) project, led by Korean government from 2004, we introduce main functions and analyze collaboration types of each system. Strategically important technologies for supporting collaboration will also be illustrated by reorganizing collaborization technologies after evaluating them with respect to emergency and importance of each technology. We hope this research will provide a guideline on collaboration especially for small and medium sized manufacturing companies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.235-247
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• 2021

The objective of this paper is to clarify the relationship between ICT application and labor productivity in Vietnamese manufacturing firms and connect it with the context of economic restructuring in Vietnam. The study uses data of 3,428 manufacturing firms from the General Statistics Office of Vietnam and regression models. In addition to the general model, the study also runs the models for sub-samples of firms of different production technology levels. Research results show two main points. First, information technology can enhance the labor productivity of Vietnamese manufacturing firms. This is true for both ICT hardware applications, ICT services, ICT software solutions, and employees' ICT skills in firms. Second, manufacturing firms with higher levels of production technology use ICT more effectively and achieve a higher impact on labor productivity. The results confirm that the Vietnamese government can stimulate ICT application and digital transformation in firms, thereby increasing labor productivity and promoting economic restructuring in the direction of shifting from agriculture to industry and from low-tech industries to high-tech ones. The results also provide implications for business managers and policymakers in other developing countries who are adopting the digital economy as a development strategy.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.245-250
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• 2023

Digital twin technology, which copies information from real space into virtual space, is being used in a variety of fields.Interest in digital twins is increasing, especially in advanced manufacturing fields such as Industry 4.0-based smart manufacturing. Operating a digital twin system generates a large amount of data, and the data generated has different characteristics depending on the technology field, so it is necessary to efficiently manage resources and use an optimized digital twin platform technology. Research on digital twin pipelines has continued, mainly in the advanced manufacturing field, but research on high-speed pipelines suitable for data in the plant field is still lacking. Therefore, in this paper, we propose a pipeline design method that is specialized for digital twin data in the plant field that is rapidly poured through Apache Kafka. The proposed model applies plant information on a Revit basis. and collect plant-specific data through Apache Kafka. Equipped with a lightweight CFD engine, it is possible to create a digital twin model that is more suitable for the plant field than existing digital twin technology for the manufacturing field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.spc
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• pp.9-18
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• 2023

In the global manufacturing industry, digital transformation is emerging as an important issue for companies to improve productivity and strengthen industrial competitiveness. The government and shipbuilding companies drive research and development to attain advanced technologies through digital transformation for shipbuilding & offshore plants, one of Korea's representative manufacturing industries. Therefore, the digital transformation of the shipbuilding & offshore plant industry was defined using an input-output analysis model, and the economic interrelationships of industries linked to the digital transformation of the shipbuilding & offshore plant industry were analyzed. According to the analysis, the shipbuilding & offshore plant industry ranks second among all 34 industries regarding the forward linkage effect. The backward linkage effect was ranked 27th, making it a mid-demand industry with a robust forward linkage effect. In addition, the production-induced effect was 0.455, the value-added-induced effect was 0.174, and the employment-induced effect was 1.779 people per billion won. The contribution of this study is that it will provide the basis for establishing policies necessary to strengthen the competitiveness of the shipbuilding & offshore plant industry. Also, it will help analyze the economic effects of digital transformation in other manufacturing industries.