• 한국주조공학회지
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• 제42권3호
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• pp.191-197
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• 2022

This study aims to improve the machinability of gray cast irons in high speed cutting by using nonmetallic inclusions. In this research, small quantities of AL and Mg were added to conventional gray cast irons without influencing their mechanical characteristics and castability to investigate the effects of these nonmetallic inclusions in the gray cast irons on tool wear in high speed cutting. During the high speed turning of gray cast iron containing Al and Mg using a cermet tool, protective layers consisting of Al, Mg, Si, Mn, S and O were detected on the flank face and rake face of the tool, and flank and crater wear were significantly reduced compared to the turning of conventional gray cast iron and gray cast iron added with Al. The effect of inclusions on tool wear increased with increasing cutting speed, and flank and crater wear was the smallest at the cutting speed of 700m/min. Moreover, in face milling, the addition of Al and Mg drastically decreased the wear rate, and wear hardly progressed even in prolonged cutting length after initial wear. The amount of adhesion on tool faces increased as the cutting speed increased. This increase in cutting speed resulted in the formation of a thick protective layer and the reduction of tool wear. Furthermore, the addition of small amounts of Al and Mg prevented thermal cracks in the face milling of gray cast irons.

• 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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• 제13권12호
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• pp.151-157
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• 1996

The tool condition monitoring is one of the most important aspects to improve productivity and quality of workpiece. In this study, the wear of ceramic tool (A1$_{2}$0$_{3}$-TiC Series) cutting the hardened die material(SKD11) was investigated. Flank wear was more dominant than crater wear. Therefore the modeling of cutting force related to flank wear has been performed. The cutting force model was construct- ed by an assumption that the stress distribution on the tool face is affected by tool wear. The relationship between characteristics as cutting force and tool wear can be suggested by machining parameters depending on cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions on the flank wear are approximately in good agreement with experimental results.

• 한국정밀공학회지
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• 제2권1호
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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*$10^{-2}$

• 대한기계학회논문집
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• 제17권9호
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• pp.2214-2222
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• 1993

With the use of the NC machine tool, the unmanned production system has been growing recently in the manufacturing field. This there are problems with monitoring adequate tool fracture during the cutting process efficiently. This study was planned and carried out to discover a way of monitoring tool condition in NO-LINE systems during the cutting process. The acquisition of data in cutting force and tool wear has been made in the section examined, to extract the RMS value of the cutting force as specific factors in the cutting process. The fluctuation of the RMS characteristics. From the results, it has been shown that the fluctuation of the RMS values for the cutting force has a close relation to flank wear.

• 한국생산제조학회지
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• 제6권4호
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• pp.124-129
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• 1997

The experimental investigation is mainly focused to detect tool wear by cutting signal measurements in multi-insert face milling SS 41 and STS 304. This research have investigated the effects on the insert number, which has relationship with mean-cutting force. AE(acoustic emission) signal, tool life and surface roughness in machining SS41 and STS 304. The cutting force and AE signal are monitored to analyse the cutting process, The surface roughness of the specimens machined by TiN coated tool with the various insert numbers measured at various cutting speeds, feed rates and depths of cut, The width of flank wear is also observed.

• 한국정밀공학회지
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• 제17권12호
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• pp.54-60
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• 2000

Research about tool condition monitoring has been done until now for product automation and unmaned system. But it is hard to apply it to the industrial field due to its cost and reliability. This paper presents the new method of tool wear measurement using Marpos gauge. This is a kind of touch sensor, so its cost is lower than vision system. And it is not affected by dust and illumination, which are important in vision system. This proposed method use tool clearance angle to measure flank wear. Experimental results compared with vision system shows that this method is available for tool condition monitoring system.

• 한국공작기계학회논문집
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• 제11권2호
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• 한국정밀공학회지
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• 제20권1호
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• pp.222-228
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• 2003

A reliable tool wear monitoring technique is the one of important aspects for achieving an integrated and self-adjusting manufacturing system. In this paper, a tool wear estimation approach for turning is proposed. This approach uses the model of cutting force, spindle displacement and their relation. A series of experiments were conducted by designing experimental techniques to determine the relationship between flank wear and cutting force coefficient as well as cutting parameters such as cutting speed, depth of cut and feed. The proposed model performance has shown that the spindle displacement model predicts tool wear with high accuracy and spindle displacement signal is possible to replace cutting force signal.

• 한국공작기계학회논문집
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• 제13권4호
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• pp.79-86
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• 2004

Tooth errors inevitable in the manufacturing process have large effect on the strength/durability and vibration performances of gear drives. We show that the manufacturing errors affect the overall gear performances, especially vibration performance, and propose a robust optimal design method for gear dimension and its tooth flank form that guarantees reliable performances to the variation of manufacturing errors. This method begins with a search of optimal design candidates by using the previously developed gear optimal design method for the strength/durability and vibration performances. Then, the statistical analysis method is applied to find a robust design solution for the vibration performance which is generally very sensitive to the manufacturing variations.