• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1103-1110
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• 2022

The old machine tools that have been used for a long time cause both increase in defective rate and decrease in productivity compared to new machines due to wear and failure of their components. In order to improve productivity and quality of machined components through remanufacturing, it is necessary to analyze the wear and failure of major components of old machine tools. In this study, the process for reverse engineering is designed for the remanufacture of planner millers, which belong to a very large machine tool. Also, the suitability of the designed process is verified through the analysis of the selected remanufactured components. In the first step of the process, some major components of the aging planner miller are scanned using a 3D laser scanner. In the next step, reverse engineering is performed using the data obtained through 3D scanning. Finally, wear and failure analysis is performed by comparing the reverse engineering data with the scan data. As a result, this reverse design and wear analysis can complement the insufficient design database and reduce costs in the maintenance of remanufactured products.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.876-879
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• 1995

Parallel NC machines are a new generation of machine tools aimed at increasing maching accuracy and reducing part cycle time. In addition to their capacity to perform both milling and turning operations, these machine tools can perform multiple machining operations simultaneously,involving one or more parts at a time, and can completely finish a part in a single setup. Due to the lack of a computer-aided process planning system, these machines are used in industry today as dedicated, mass-production machines. This pape presents methodology for generating optimal process plan for each parallel machine tool using a genetic algorithm.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.926-931
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• 2001

In this paper a CAD-based optimal design system is introduced and applied to optimal design of machine tool structures. The system is designed to reduce manual interfacing effort. All the design activities such as selecting design variables, making FE meshes and FE analysis are integrated on a parametric CAD program. A user can easily select design variables by clicking a CAD model. To enhance the robustness and versatility, this system uses the finite difference method for the design sensitivity analysis. By taking a practical example of the design of the column of a horizontal machining center, it is shown that the software system is efficiently usable in industry establishing the goal of minimizing user intervention between various analysis and optimization activities.

• Journal of the Korean Society of Industry Convergence
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• v.12 no.2
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• pp.91-97
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• 2009

The productivity and the precision machining are the major concerns of the machine tools, and the importance of those features will be even more emphasized with the needs of the modern industries. In this paper the dynamic properties of a lathe have been investigated through the frequency analysis test and the computer simulation to minimize the transmission of vibration generated during the machining process. The modifications have been applied to the original structure to suppress the vibration transmission and further for the structure to achieve less vibrations and higher precision machining. The result shows that the machine can have much less vibrations with simple design alterations for minor expenses, the result can also be readily applied to many similar machines for improved stability.

• Proceedings of the Technology Innovation Conference
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• 2001.06a
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• pp.71-95
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• 2001

This study reveals that the user industry has a limited role as a source of technological capability in the case of the machine tools in Korea where the user industry is relatively mope advanced than other capital goods industry. The study examined the sources of technological capability in terms of migration of workforce and flow of product design information. Although the capital goods sector is generally regarded as being the sector where the user producer interaction is important the user industry failed to be the seed-bed of technological capability to develop machines. This study argues that this finding could have implications to the specificity of capital goods in a developing country.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.16-22
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• 2005

It is difficult to separate those of NC controller from the error of machine tools because the conventional testing methods to inspect the performance are including the errors of moving system, therefore it has been used as the methods that compare the other controllers. Also, it is hard to predict the machine itself errors with the methods assembling the NC controller and moving system on machine because of the variable load conditions. In this study, the performance inspecting system was developed by analyse the $axis\_rotating$ properties of servo system finally outputting from NC controller. The axis torque was controlled by motor dynamometer and the rotating position accuracy was measured by this developed system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1097-1102
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• 2022

With the continuous development of the current industry, the current global environment is in a very serious situation, with resource supply and demand dependent on imports and huge costs for waste disposal due to the depletion of resources and mass generation of industrial waste. Its limitations have already been revealed in many fields, and the importance of re-manufacturing is drawing attention as a countermeasure to these problems. Re-manufacturing aims to recover products that are in the aging and disposal stages, recover to performance close to new products, and re-commercialize them. Among them, most of the machine tools are made of materials such as steel and cast iron with large structures, and raw materials are widely used when producing new products. In addition, since a lot of carbon is generated due to production, it is an object that can obtain a great re-manufacturing effect. Planner millers belonging to large machine tools are one of the machine tool equipment that can greatly reduce resources and energy through re-manufacturing because the structure is very large and the casting is several to tens of tons. Through this machine tool, performance tests and results are derived on the development of re-manufacturing source technology and domestic servo motor and CNC control device.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.58-63
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• 2007

A compact gun drill machine was developed to improve productivity and economical efficiency for small and medium enterprise tool makers. Gun drilling works are mainly using at molding, automobile, aircraft industry and special tool makers to make deep holes. As gun drill machines are very expensive and big burden for small tool makers, so that works used to execute through outside orders but it was required lot of cost too. Most of gun drill machines are providing for high volume and large capacity enterprises. In order to use for small and medium enterprises that compact gun drill machine was designed and developed. It could be improved product quality, productivity and manufacturing cost for small and medium enterprises by using this machine.

• Journal of Ocean Engineering and Technology
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• v.36 no.3
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• pp.194-210
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• 2022

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.