• Design & Manufacturing
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• 제16권4호
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• pp.60-66
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• 2022

Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

• Design & Manufacturing
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• 제17권3호
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• pp.41-47
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• 2023

This paper presents the development of a controller that can control the temperature of an heating system based on a thermoelectric module. Temperature controller using Peltier has various external factors such as external temperature, characteristics of an aluminum plate, installation location of temperature sensors, and combination method between the aluminum plate and heating element. Therefore, it is difficult to apply the simulation and simulation results of heating system using Peltier at control algorithm. In general, almost temperature controller is using PID algorithm that finds control gain value heuristically. In this paper, it is proposed mathematical model that explain correlate between the temperature of the heating system and input voltage. And then, optimal parameter of estimated thermal model of the aluminum plate are searched by using genetic algorithm. In addition, based on this estimated model, the optimal PID control gain are inferred using a genetic algorithm. All of the sequence are simulated and verified with proposed real system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.449-450
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• 2006

Development of a feed drive system with high speed, positioning accuracy and thrust has been an important issue in modern automation systems and machine tools. Linear motors can be used as an efficient system to achieve such technical demands. By eliminating mechanical transmission mechanisms such as ball screw or rack-pinion, much higher speeds and greater acceleration can be achieved without backlash or excessive friction. However, an important disadvantage of linear motor system is its high power loss and heating up of motor and neighboring machine components on operation. For the application of the linear motors to precision machine tools an effective cooling method and thermal optimizing measures are required. In this paper presents an investigation into a thermal behavior of linear motor cooling plate. FVM employed to analyze the thermal behavior of the linear motor cooling plate, using the ANSYS-CFX.

• Transactions of Materials Processing
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• 제20권8호
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• pp.581-587
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• 2011

The production of high-precision micro-sized screws, used to fasten parts of micro devices, generally utilizes a cold thread-rolling process and two flat dies to create the teeth. The process is fairly complex, involving parameters such as die shape, die alignment, and other process variables. Thus, up-front finite-element(FE) simulation is often used in the system design procedure. The final goal of this paper is to produce high-precision screw with a diameter of $800{\mu}m$ and a thread pitch of $200{\mu}m$ (M0.8${\times}$P0.2) by a cold thread rolling process. Part I is a first-stage effort, in which FE simulation is used to establish process parameters for thread rolling to produce micro-sized screws with M1.4${\times}$P0.3, which is larger than the ultimate target screw. The material hardening model was first determined through mechanical testing. Numerical simulations were then performed to find the effects of such process parameters as friction between work piece and dies, alignment between dies and material. The final shape and dimensions predicted by simulation were compared with experimental observation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2001년도 추계학술대회 논문집
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• pp.106-110
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• 2001

The ball-end milling process is widely used in the die/mold industries, and it is very suitable for the machining of free-form surfaces. However, this process is inherently inefficient process to compared with the end-milling or face milling process, since it relays upon the machining at the cutter/surface contact point. The machined part is the result of continuous point-to-point machining on the free-form surface. And cusps (or scallops) remain at the machined part along the cutter paths and they give the geometrical roughness of the workpiece. Thus, for the good geometrical roughness of the workpiece, it is required very tightly spaced cutter paths in this ball-endmilling process. However, with the tight cutter paths, the geometrical roughness of the workpiece is not regular on the workpiece since the cusp height is variable in the previously developed ISO-parametric or Cartesian machining methods. This paper suggests a method of tool path generation which makes the geometrical roughness of workpiece be constant through the machined surface. In this method, Ferguson Surface design Model is used and cusp height is derived from the instantaneous curvatures. And, to have constant cusp height, an increment of parameter u or v is estimated along the reference cutter path. In ball-end milling experiments, the cusp pattern was examined, and it was proved that the geometrical roughness could be regular by suggested tool path generation method.

• Korean Journal of Food Science and Technology
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• 제23권1호
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• pp.88-92
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• 1991

To analyze the effects of the system parameters on the target parameters, which include the amount of water evaporation, water solubility index(WSI) and water absorption index(WAI), test trials of fractional factorial design of the three process variables at three levels were carried out for corn grit with a laboratory twin-screw extruder with three different screw configurations. The system parameters collected from the trials, such as extrusion temperature, specific mechanical energy input(SME) and mean residence time(RT), were showed the ranges of $129{\sim}182^{\circ}C$, $67{\sim}163\;kwh/ton$ and $12{\sim}34\;sec$, respectively. Within these ranges of the system parameters, the target parameters were able to be quantified by using multiple regression equations. The correlation of results with the system parameters blocked by the screw configuration as dependent variables, yield correlation coefficients above 0.90, and the correlation using the system parameters obtained from whole experiment system as the dependent variables yield correlation coefficients around 0.80. The functional relationship, which can be quantified by second order polynomial regression equation with only two system parameters within necessary degree of accuracy, can he graped in three dimensional surface response and contour diagrams.

• Elastomers and Composites
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• 제43권3호
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• pp.173-182
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• 2008

Rubber-pad forming process for materials such as metal in which portions of the die which act upon the material is composed of a natural or synthetic rubber or elastomer material. This makes the rubber pad forming process relatively cheap and flexible, high accuracy for small product series in particular. In this study, we carried out the physical test and finite element analysis of elastomer such as natural rubber and urethane for steel rack rube forming. The non-linear property of elastomer which are described as strain energy function are important parameter to design and evaluate of elastomer component. These are determined by material tests which are uni-axial tension and bi-axial tension. This study is concerned with simulation and investigation of the significant parameters associated with this process.

• Design & Manufacturing
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• 제16권4호
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.