• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.261-269
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• 2009

Micro end-milling process is applied to fabricate precision mechanical parts cost-effectively. It is a complex and time-consuming job to select optimal process conditions with high productivity and quality. To improve the productivity and quality of precision mechanical parts, micro end-mill wear and cutting force characteristics should be studied carefully. In this paper, high speed machining experiments are studied to construct the optimum process design as well as the mathematical modeling of tool wear and cutting force related to cutting parameters in micro ball end-milling processes. Cutting force and wear characteristics under various cutting conditions are investigated through the condition monitoring system and the design of experiment. In order to construct the cutting database, mathematical models for the flank wear and cutting force gradient are derived from the response surface method. Optimal milling conditions are extracted from the developed experimental models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.452-455
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• 2005

The cutting characteristics of hardened steel by a PCBN tool is investigated with respect to workpiece surface roughness, cutting force and tool flank wear of the vision system. Backpropagation neural networks (BPNs) were used for detection of tool wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, and thrust force signals. The output was the tool wear state which was either usable or failure. Hard turning experiments with various spindle rotational speed and feed rates were carried out. The learning process was performed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.1
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• pp.85-91
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• 2003

The experimental study for turning circular free fanned surface with TiN coated insert tool was conducted for different cutting conditions such as cutting speed, feed rate and depth-of-cut. For the fluctuation of 1.0mm depth-of-cut, the characteristics for machined surface and tool wear were less influenced by the feed rate and cutting speed than those of higher depth of cut. The higher surface roughness and surface precision were obtained in lower cutting speed. For the fluctuation of 1.5mm depth-of-cut, the higher surface roughness was obtained for the case of the lower feed rate of 0.05-10mm/rev and the higher cutting speed of 80m/min. For the fluctuation of 2.0mm depth-of-cut, the surface roughness and surface precision were too worse to machine the specimen And the flank wear on the tool was increased rapidly rather than the crater wear.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1035-1042
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• 1988

The acoustic emission(AE) signal is monitored in milling operation in order to investigate the relationship between the progressive tool wear and the AE signals. A signal processing technique so called time domain averaging(TDA) is presented for the elimination of the influences of the noise imbedded in the periodic signals. The relationship between the progressive tool wear and the AE signals is investigated by varying the cutting speed, feed, depth of cut and the number of insert. From the measured data, it is observed that the averaged level of the AE signal increases at first with the increase of flank wear to a certain critical value, and then stays almost constant or fluctuates with further increase of the flank wear.

• Korean Journal of Materials Research
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• v.18 no.12
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• pp.635-639
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• 2008

In this paper, experimental studies of the regrinding of tungsten carbide (WC-Co) tools for high-speed machining were conducted. Regrinding and a subsequent evaluation test were carried out for a flat endmill tool with diameters of 10 mm and 3 mm using a CNC five-axis tool grinder and a CNC three-axis machining center. Tool wear on the two types of endmill tools increased as the cutting length increased, and the tool wear was not influenced by the regrinding state. In case of the micro endmill with a tool diameter of 3 mm, the effective regrinding time was determined for a flank wear threshold of 0.3 mm considering the tool life according to cutting length. The tool lives of the 10 mm and 3 mm endmill tools were increased by 80% and 72%, respectively. This conclusion proves the Feasibility of the recycling of tungsten carbide materials in the high-speed machining of high-hardened materials for industrial applications.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.281-286
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• 2004

The wear process of end mill is a so complicated process that a more reliable technique is required for the monitoring and controling the tool life and its performance. This research presents a new tool wear monitoring method based on the sound signal generated on the machining. The experiment carried out continuous-side-milling for using the high-speed steel end mill under wet condition. The sound pressure was measured at 0.5m from the cutting zone by a dynamic microphone, and was analyzed at frequency domain. The tooth passing frequency appears as a harmonics form, and end mill wear is related with the first harmonic. It can be concluded from the result that the tool wear is correlate with the intensity of the measured sound at tooth passing frequency estimation of end mill wear using sound is possible through frequency analysis at tooth passing frequency under the given circumstances.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1783-1793
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• 1993

Pattern recognition technique using fuzzy c-means algorithm and multilayer perceptron was applied to classify tool wear states in turning. The tool wear states were categorized into the three regions 'Initial', 'Normal', 'Severe' wear. The root mean square(RMS) value of acoustic emission(AE) and current signal was used for the classification of tool wear states. The simulation results showed that a fuzzy c-means algorithm was better than the conventional pattern recognition techniques for classifying ambiguous informations. And normalized RMS signal can provide good results for classifying tool wear. In addition, a fuzzy c-means algorithm(success rate for tool wear classification : 87%) is more efficient than the multilayer perceptron(success rate for tool wear classification : 70%).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.58-62
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• 1996

In case of hard turning, tool wear is acclerated by heat. So we intend to decrease tool wear by using an air-jet cooling system. Before constructing the air-jet cooling system, no chipping conditions were selected through a statistical method, so called 'Taguchi method', and then the air-jet cooling system was developed by synthesizing and analyzing the results of experimental data through Taguchi method. The air-jet cooling system actually reduced flank wear of TiN coated tool by 25%.

• Journal of the Korean Society for Precision Engineering
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• v.2 no.1
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• pp.62-71
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• 1985

This is a study on the monitoring technique in tool failure and tool life by AE method. The relation between amplitude level of AE signal and flank wear width was studied by experiments. The relation between amplitude level of AE signal and tool life was also studied. As the result, it was observed that amplitude level of AE signal was only affected by cutting velocity. Amplitude level of AE signal was directly proportional to flank wear width and the increasing rate was related to cutting velocity. So, the relation between amplitude level of AE signal and tool life was represented as follow: $CT^n$ = $AE_{rms}$ where, n=0.35 C=9.5*$10^{-2}$

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.131-134
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• 1995

The high efficiency and accuracy in machining the die material can be abtained in high speed machining, so it is necessary to analyze the mechanism of high speed cutting process : cutting force, flank wear. The tool dynomometer with high natural frequency is newly developed. With this device, the mechanism of high speed cutting process is investigated according to speed and feedate.