• 한국정밀공학회지
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• 제15권11호
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• pp.32-38
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• 1998

For the purpose of monitoring the abnormal state in proportion to cutting in automatic production process, the 3 kinds of specimens different from mechanical properties by austempering through temperature variation were manufactured, and the effects of tool wear on thrust and AE RMS was analyzed with sequential drilling in in-process. When the ADI specimens were drilled, the relationship of thrust and AE RMS with flank wear was studied through experiments, and it is confirmed that the reliable wear state is able to be monitored by using these signals. It was shown that thrust and AE RMS increased slowly till flank wear reached to V$_{B}$ = 0.25mm, and they increased steeply over the value. The effective tool exchange time was able to be pre-estimated by using this fact. It was validated that the tool breakage was able to be detected on the real time by monitoring in in-process.s.

• 한국기계가공학회지
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• 제16권4호
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• pp.83-88
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• 2017

Recently, the use of advanced materials with light weight significantly increases because of global regulation on CO2 emission. Especially, CFRP (carbon fiber reinforced plastics) one of the most promising advanced materials. Since CFRP has pretty higher strength per unit weight than steel, it is one of most popular materials in aviation industry and its application to automobile rises sharply. Especially, one of the frequent machining processes for CFRP is drilling to make a hole, however, CFRP drilling has troublesome limitations in hole quality and productivity induced due to delamination, splintering and severe tool wear. Particularly, cutting loads increase caused by tool wear makes delamination and splintering even severer. Therefore, tool wear monitoring or reduction in CFRP drilling must be considered seriously. In this study, we measured thrust force, flank wear, and tool surface temperature in drilling using various tools with different sizes and materials. Consequently, it was presented the effects of tool properties on drilled hole quality, thrust force and tool surface temperature.

• 산업공학
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• 제7권3호
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• pp.155-168
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• 1994

In computer integrated manufacturing environment, tool management plays an important role in controlling tool performance for machining operations. Knowledge of tool behavior during the cutting process and effective tool-behavior prediction contribute to controlling machine costs by avioding production delays and off-target parts due to tool failure. The purpose of this paper is to review and develop the tool condition monitoring scheme for drilling operation to assure a fast corrective response to minimize the damage if tool failures occur. If one desires to maximize system through-put and product quality as well as tooling resources, within an economic environment, real-time tool sensing system and information processing system can be coupled to provide the necessary information for the effective tool management. The example is demonstrated as to drilling operation when the aluminum composites are drilled with carbide-tipped HSS drill bits. The example above is limited to the situation that the tool failure mode of drill bits is wear.

• Smart Structures and Systems
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• 제13권6호
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• pp.959-974
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• 2014

Hand-Arm Vibration Syndrome (HAVS) is a group of diseases caused by exposure of the hands to vibration while operating the hand held power tools such as road breaker, drilling machine, demolition hammer in construction works. In this paper, area-changed capacitive micro-accelerometer is designed to measure the vibration exposure on worker's hand when operating a drilling machine on various blocks such as clay block, paver block and solid cement block. The design process includes mathematical modelling of micro-accelerometer and simulations are done using INTELLISUITE 8.6. Experimental results are taken for various blocks surfaces using conventional and micro-accelerometer. Comparisons show that usage of area-changed micro-accelerometer for Hand-arm vibration monitoring provides better sensitivity, which in turn reduces the risk of HAVS in workers.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.275-280
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• 2001

Recently, the trends of industrial products grow more miniaturization, variety and mass production. Micro drilling which take high precision in cutting work is requested more micro hole and high speed working. Especially, Micro deep hole drilling is becoming more important in a wide spectrum of precision production industries, ranging from the production of automotive fuel injection nozzle, watch and camera parts, medical needles, and thick multi-layered Printed Circuit Boards(PCB) that are demanded for very high density electric circuitry. This paper shows the tool monitoring results of micro drill with tool dynamometer. And additionally, microscope with built-in monitor inspection show the relationship between burr in workpiece and chip form of micro drill machining.

• 대한기계학회논문집
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• 제19권5호
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• pp.1176-1181
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• 1995

Microdrilling is one of the most difficult operations because of the poor chip discharge and the weakness of tool. This study is concerned about the development of a microdrilling monitoring system that is useful for minimizing the tool breakage and enhancing the machinability in the air spindle based microdrilling. The system is composed of a drilling state detection unit and an adaptive step-feed control unit that controls the micro-stepping motor driven spindle axis. Drilling states such as overload, tood breakage are recognized by the change of the air spindle speed which is measured via the reflective photo sensor. Based on the monitoring results, the adaptive step-feed control algorithm adjusts the step increment to keep the decrease of spindle speed within a specified range. The results of evaluation tests have shown that the developed system is very effective to prevent the breakage of microdrill and improves the productivity in comparison with the conventional microdrilling.

• 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.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• 한국정밀공학회지
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• 제10권4호
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• 한국생산제조학회지
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• 제7권6호
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• pp.90-96
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• 1998

The ductile cast iron is austempered at 300, 350 and 40$0^{\circ}C$ temperature in order to investigate the basic factors for monitoring drill wear in automatic production process, and cutting force and AE RMS signals are measured with changing cutting condition for ADI(Austempered Ductile Cast Iron) with different mechanical properties. The signals of cutting force were influenced by cutting speed and feedrate greatly. On the other hand AE RMS signals are influenced by cutting speed where as it is not related with feedrate. As the depth of drilling increases, cutting force shows a slow increase and the value of AE RMS increases until the range of h/d=4. But over the range it increases greatly due to an amount of chip discharge and friction with inner wall of drilling hole, etc. As the drill diameter increases at a constant depth of drilling. Cutting force increases linearly, but the level of AE RMS does not increases linearly due to circumferential velocity and great influence of h/d.