• Food Science and Industry
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• v.49 no.3
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• pp.97-102
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• 2016

It is important to encourage the restoration of the production of traditional Korean liquors, which is being undertaken by individuals, companies, and the government. The flavours of traditional liquors differ and depend on the environment and raw materials. This study on the traditional Gangwondo liquor is based on literature review and oral tradition. The history of and the scientific rationale behind the use of malt, which is a characteristic feature of the traditional Gangwondo liquor manufacturing process, must be systematically researched. It is important that independent two-step fermentation is used in Gangwondo, while in other regions simultaneous two-step fermentation is used. We expect that the current research on fermentation will be useful for the production of various traditional liquors. The total production of traditional liquors will need to be increased to meet the needs of the world festival, 2018 Olympic Winter Games in Pyeongchang.

• International Journal of Korean Welding Society
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• v.3 no.1
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• pp.45-50
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• 2003

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time monitoring system of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensors. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding.

• International Journal of Aerospace System Engineering
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• v.10 no.2
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• pp.1-4
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• 2023

Even though the recent development trend of wind turbine systems has been focused on larger MW Classes, the small-scale wind turbine system has been continuously developed because it has some advantages due to easy personnel establishment and use with low cost and energy saving effect. This work is to propose a specific structural design and analysis procedure for development of a low noise 500W class small wind turbine system which will be applicable to relatively low wind speed region like Korea. The proposed structural feature has a skin-spar-foam sandwich composite structure with the E-glass/Epoxy face sheets and the Urethane foam core for lightness, structural stability, low manufacturing cost and easy manufacturing process. Moreover this type of structure has good behaviors for reduction of vibration and noise. Structural analysis including load cases, stress, deformation, buckling and vibration was performed using the Finite Element Method. In order to evaluate the designed blade structure the structural tests were done, and their test results were compared with the estimated results.

• Journal of Korea Technology Innovation Society
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• v.13 no.1
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• pp.124-139
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• 2010

This study analyzes determinants of innovation in Korea manufacturing industries from 2005 to 2007. In order to do this, we use raw data from 'Korea Innovation Survey 2008: Manufacturing Sector' conducted by STEPI, and also collect financial statement data from Korea Investors Service. As an analytical method for the empirical test, we utilize Probit model. Empirical results show that firm size and market concentration have positive relationship with firm's innovation activities. These support the ‘Schumpeterian hypothesis’. This would be the most distinguished feature of this study compared to previous literatures.Our study also shows that R&D personnel ratio, R&D intensity, and advertising intensity have positive effects on firms' innovation. Thus, we can say that R&D activities and consumer orientation are the main determinants of innovation. However, profit ratio and growth rate do not have any statistically significant effect on firms' innovation.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.77-95
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• 2004

This paper deals with the process planning of flexible manufacturing systems (FMS) with various flexibilities and multiple objectives. The consideration of the manufacturing flexibility is crucial for the efficient utilization of FMS. The machine, tool, sequence, and process flexibilities are considered In this research. The flexibilities cause to increase the Problem complexity. To solve the process planning problem, an this paper an evolutionary algorithm is used as a methodology. The algorithm is named multiobjective competitive evolutionary algorithm (MOCEA), which is developed in this research. The feature of MOCEA is the incorporation of competitive coevolution in the existing multiobjective evolutionary algorithm. In MOCEA competitive coevolution plays a role to encourage population diversity. This results in the improvement of solution quality and, that is, leads to find diverse and good solutions. Good solutions means near or true Pareto optimal solutions. To verify the Performance of MOCEA, the extensive experiments are performed with various test-bed problems that have distinct levels of variations in the four kinds of flexibilities. The experiments reveal that MOCEA is a promising approach to the multiobjective process planning of FMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.305-307
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• 2021

In this paper, we propose a study related to the development of a Digital-Twin platform using a smart factory based CPPS (Cyber Pysical Production System) using ICT (Information Communication Technology) technology. The platform developed through this study performs a 3D model simulation function in conjunction with P3R (Product, Process, Plant, Resource) including BOP (Bill of Process) management function from the preceding manufacturing process planning stage. In addition, we propose a digital twin platform that can predict production processes, equipment, layout, and production. The platform proposed through this paper proposes a feature that can manage the entire smart factory manufacturing process from the initial planning design stage to the manufacturing, production, operation, and maintenance stages.

• Smart Structures and Systems
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• v.33 no.5
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• pp.333-347
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• 2024

There has been an increasing interest in the construction of smart buildings that can actively monitor and react to their surroundings. The capacity of these intelligent structures to precisely predict and respond to deflection is a crucial feature that guarantees both their structural soundness and efficiency. Conventional techniques for determining deflection often depend on intricate mathematical models and computational simulations, which may be time- and resource-consuming. Artificial intelligence (AI) algorithms have become a potent tool for anticipating and controlling deflection in intelligent structures in response to these difficulties. The term "deflection-aware smart structures" in this sense refers to constructions that have AI algorithms installed that continually monitor and analyses deflection data in order to proactively detect any problems and take appropriate action. These structures anticipate deflection across a range of operating circumstances and environmental factors by using cutting-edge AI approaches including deep learning, reinforcement learning, and neural networks. AI systems are able to predict real-time deflection with high accuracy by using data from embedded sensors and actuators. This capability enables the systems to identify intricate patterns and linkages. Intelligent buildings have the potential to self-correct in order to reduce deflection and maximize performance. In conclusion, the development of deflection-aware smart structures is a major stride forward for structural engineering and has enormous potential to enhance the performance, safety, and dependability of designed systems in a variety of industries.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.287-292
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we confirmed advantages/disadvantages of four algorithms and identified application methods of few algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.42-47
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• 2004

Formed insert type tool satisfy both the surface roughness and geometric accuracy, so that cutting edge of formed tool can duplicate final feature. For experiment the formed tools with various clearance angles are machined. And the tools are evaluated with respect cutting force, flank rear and surface roughness to optimistic condition.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.707-712
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• 1991

In machining a part in CAD/CAM system, it is required that the drawing information should be automatically generated, modified, deleted, and thus be used as an general information throughout the entire manufacturing process. This research addresses basic entities(point, line, circle, arc) for design feature and combination of this features, based on GT concepts, with minimum user's manual input. This paper deals with the generalization of operating system which can cover the s parts which appears in mechanical part handbook and the basic constitutional part of sold base. The system developed shows a strong application impact on automatic process planning system of medium - size injection sold companies.