• 대한기계학회논문집
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• 제17권7호
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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%).

• 한국정밀공학회지
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• 제15권8호
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• pp.116-125
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• 1998

In this paper, main target is to select parameters for prediction of tool wear and detection of tool fracture. The research about choosing parameter for prediction of tool wear is done by using force ratios. Also current sensor, tool-dynamometer, and accelerometer are used for researching detection method of tool fracture. Experiment is done using Taguchi's method in medium machining conditions. Parameter which is best for prediction of tool wear and detection of tool fracture by deviation analysis is selected. In this paper, tool wear means flank wear.

• Tribology and Lubricants
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• 제6권1호
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• pp.82-88
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• 1990

마찰학적인 관점에서 피복초경공구의 피복층이 공구마멸에 미치는 영향을 조사하기 위하여 공구표면의 피복층을 선택적으로 제거한 후 마멸시험, 급속정지 실험 및 절삭력 측정 실험을 수행하였다. 실험 결과 피복층은 공구와 피삭재 사이의 점착성을 낮추어 점착마멸을 억제시키는 것으로 나타났으며, 마찰저항을 감소시켜 절삭력을 낮추는 것으로 관찰되었다. 또한 경사면상의 피복층이 플랭크 마멸의 성장을 저지하는 효과가 있는 것으로 나타났으며, 피삭재가 탄소강인 경우 경계마멸까지 고려할 때 다중피복공구가 가장 바람직한 것으로 관찰되었다.

• 한국생산제조학회지
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• 제8권6호
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• pp.71-77
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• 1999

Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.74-79
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• 1996

The wear of partially coated pinion cutters under several cutting conditions was studied. In the realm of this experiment, chipping was a dominant tool wear mechanism and flank wear was much larger than crater wear. Under the condition of relatively low rotary feed and low radial feed rate, the wear due to chipping was concentrated at the nose part of pinion cutter. Increasing of rotary feed and radial feed rate alleviated the concentration of chipping at nose and prolonged tool life.

• 한국공작기계학회논문집
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• 제14권3호
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• pp.1-7
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• 2005

The prediction for tool life is one of the most important factors for increasing reliability, stability, and productivity of manufacturing system. This paper deals with a tool life prediction method in view of reliability assessment for cutting tools. In this study, flank wear was focused among multi-factors deciding the tool wear state. First, tool life was predicted by correlation between flank wear and cutting time, based on the extended Taylor tool life equation of turning, including parameters of cutting speed, feed rate, and cutting depth. Second, each of cutting conditions of end-milling was equivalently converted to apply ball end-mill data to the extended Taylor equation. The web-based prediction program for tool life was developed as one of reliability assessment programs for machine tools.

• 한국정밀공학회지
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• 제12권5호
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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.

• 한국정밀공학회지
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• 제20권1호
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• pp.144-150
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• 2003

When WC and group IV elements are added to Ti(C,N)-Ni substrate, microstructures of the cermet is changed. The microstructure gives direct effect on the property of the material. In this study, the amount of WC and group W elements of Ti(C,N) cermet tool was investigated. The composition of WC was changed from 5 to 20wt% to determine the effect of WC on the cutting performance of cermet tool. The more WC was added, the longer the tool life of the cermet tool was. The cermet with 20wt% WC showed the best fracture toughness. The effect of group W elements; ZrC, ZrN and HfC was also investigated by adding each of them to manufacture the cermet tool with fixed l4wt% WC composition. The cermet with 1wt% ZrC and 14wt% WC showed the best cutting performance among the investigated cermet tools.

• 한국공작기계학회논문집
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• 제12권3호
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• 한국정밀공학회지
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• 제26권5호
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• pp.48-56
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• 2009

In this paper, laser-assisted machining(LAM) has been employed to machine hot isostatically pressed (HIPed) Si3N4 work pieces. Due to little residual flaws and porosity, HIPed $Si_3N_4$ work pieces are more difficult to machine compared to normally sintered $Si_3N_4$ workpieces. In LAM, the intense energy of laser was used to enhance machinability by locally heating the workpiece and thus reducing yield strength. In experiments, the laser power ranges from 200W to 800W and the diameter of work pieces is 16mm. While machining, the surface temperature was kept nearly constant by laser heating except for a short period of rise time of max. 58 seconds. Results showed as feed rate increases the surface temperature of $Si_3N_4$ workpieces decreases slightly, whereas the effect of depth of cut is disregardable. With a laser power of 800W, achievable maximal depth of cut as 0.7mm and feed rate was 0.03mm/rev.