• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.607-615
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• 2021

Cytokines are protein mediators that possess the ability to assist cell-to-cell communication in immune system-related activities. In general, pathogen endotoxins activate the release of inflammatory mediators, and with time, there is an increase in the cytokine levels in the body. Interleukin (IL)-6 mediates the acute-phase inflammatory response, and elevated IL-6 levels have been reported in peritoneal fluids of women with pelvic inflammation and endometriosis, thereby associating it with oocyte quality and infertility. To overcome subfertility or infertility in humans and animals, the present study was done to examine the effect of recombinant IL-6 on porcine oocytes matured in vitro and subsequently to determine the fertilization rate and embryo development. Porcine oocytes were incubated with varying concentrations of IL-6 (0 - 2 ㎍·mL^-1) for 44 h followed by in vitro fertilization and culturing of the oocytes. The oocytes or embryos were fixed with 3.7% paraformaldehyde (PFA) and stained with fluorescence dyes, and the meiotic spindle, chromosome organization, fertilization status and embryo development were subsequently assessed under a fluorescence microscope. We observed induction of an abnormal meiotic spindle alignment in the oocytes incubated with IL-6 compared to the control oocytes incubated without IL-6. Moreover, significantly decreased fertilization rates and embryo development were observed for oocytes incubated with IL-6 (p < 0.05). Thus, an increased IL-6 level during oocyte maturation could be associated with fertilization failure due to an aberrant chromosomal alignment and a disruption of the cortical granules. Taken together, our results indicate that successful assisted reproduction can be achieved by controlling the levels of inflammatory cytokines.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.111-117
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• 2000

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models the thermal errors for error analysis and develops an on-the-machine measurement system by which the volumetric errors are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses and a designed spherical ball artifact (SBA). Experiments show that the developed system provides a high measuring accuracy, with repeatability of $\pm$2$\mu\textrm{m}$ in X, Y and Z directions. It is believed that the developed measurement system can be also applied to the machine tools with CNC controller. In addition, machining accuracy and product quality can be also improved by using the developed measurement system when the spherical ball artifact is mounted on a modular fixture.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• IE interfaces
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• v.19 no.1
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• pp.43-52
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• 2006

In order to make best use of NC machine tools with minimal labor costs, they need to be in operation 24 hours a day without being attended by human operators except for setup and tool changes. Thus, unattended machining is becoming a dream of every modern machine shop. However, without a proper mechanism for real-time monitoring of the machining processes, unattended machine could lead to a disaster. Investigated in this paper are ways to using PC camera as a real-time monitoring system for unattended NC milling operations. This study defined five machining states READY, NORMAL MACHINING, ABNORMAL MACHINING, COLLISION and END-OF-MACHINING and modeled them with DEVS (discrete event system) formalism. An image change detection algorithm has been developed to detect the table movements and a flame and smoke detection algorithm to detect unstable cutting process. Spindle on/off and cutting status could be successfully detected from the sound signals. Initial experimentation shows that the PC camera could be used as a reliable monitoring system for unattended NC machining.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.98-107
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• 1995

The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.79-88
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• 2002

High speed machining system have been used in industrial because it is effective to a material manufacturing with various shape. Recently the end-milling processing is needed the high-precise technique with good surface roughness and rapid time in aircraft, automobile part and molding industry. Therefore this study proposed to decide best manufacturing cutting condition for surface roughness and rapid manufacturing tune by using computer Image processing system and 3D modelling. Until the 16,000 rpm, the surface roughness is decreased rapidly, but it is not over that. The 22,000 rpm is the spindle speed with the optimum surface in the high speed end-milling. In the case of the feed rate with 2,000 mm/mm and 8,000 mm/mm, the surface roughness is better than 4,000 mm/min and 6,000 mm/min. By using the 3D modelling, it is effectively represented shape characteristics of working surface m high speed end-milling.

• Tribology and Lubricants
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• v.28 no.3
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• pp.130-135
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• 2012

This study presents a new methodology for realtime tool breakage detection by sensor fusion concept of two hall sensor and an acoustic emission (AE) sensor. Spindle induction motor torque of CNC Lathe during machining is estimated by two hall sensor. Estimated motor torque instead of a tool dynamometer was used to measure the cutting torque and tool breakage detection. A burst of AE signal was used as a triggering signal to inspect the cutting torque. A significant drop of cutting torque was utilized to detect tool breakage. The algorithm was implemented on a NI DAQ (Data Acquisition) board for in-process tool breakage detection. The result of experiment showed an excellent monitoring capability of the proposed tool breakage detection system. This system is available tool breakage monitoring through internet also provides this system's user with current cutting torque of induction motor.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.694-699
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• 2005

This paper deals with a control technique of eliminating the transient vibration of a geared mechanical system. This technique is based on a model-based control with a rotational speed sensor in order to establish the damping effect at the driven machine part. A rotational speed sensor is installed in a driven gear, namely a bull gear. A control model is composed of a reduced-order mechanical part expressed as a transfer function between the rotational speed of the motor and that of the bull gear. This control model estimates a load speed after the rotational speed of the bull gear is acted on the transfer function. The difference between the estimated load speed and the motor speed is calculated dynamically and it is added to the velocity command to suppress the transient vibration generated at the load. This control technique is applied to a dies driving spindle of a form rolling machine. In this paper, the performance of this control method is examined by simulations. The settling time of the residual vibration generated at the loading inertia can be shortened down to about 1/2 of the uncompensated vibration level.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.33-39
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• 2012

The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1166-1171
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• 2001

The method for output disturbance estimation is proposed. In this method, output disturbance is estimated from the closed loop system dynamics using the output and control input signals. In the closed-loop output-disturbance estimator, precise system identification is required to reduce estimation error. The realization of estimator was done by the DSP board (DSPl103), and disturbance estimation in various environments was performed： change of rotation speed, media feature and spindle motor with (or without) auto-ball balancing system (ABS). From these experiments, the disturbance characteristics of ODD under various conditions are analyzed, and the desirable servo loop configuration based these results is proposed.