• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1033-1034
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• 2011

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.14-18
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• 2001

Rise in cutting force causes tool damage and worsens product quality resulting in machining accuracy deterioration. Especially, fragile material cutting brings about breakage of material and worsens product surface quality. In this study, we trace the locus of cutting force and examine the machined surface corresponding to the cutting force loci. and build up a monitoring system for deciding normal operation or not of cutting process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.3
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• pp.34-40
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• 2003

This paper describes evaluation and monitoring methods of machining characteristics for developed micro grooving machine. Experiments were conducted under various process conditions such as spindle revolution speed, feed rates and depth of groove V and U shape of blade and STD11 were used in this experiment. The status of grooving was evaluated through analysis of the Acoustic emission (AE) signal resulted in each process condition. Based on the analysis, this paper examined the possibility of monitoring adapting fuzzy logic. In conclusion, this paper presented the possibility of monitoring in process adapting AE technology and appropriate micro grooving condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.888-891
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• 2000

Drilling is one of the most important operations in machining industry and usually the most efficient and economical method of cutting a hole in metal. From automobile parts to aircraft components, almost every manufactured product requires that holes are to be drilled for the purpose of assembly, creation of fluid passages, and so on. It is therefore desirable to monitor drill wear and hole quality changes during the hole drilling process. One important aspect in controlling the drilling process is drill wear status monitoring. With the monitoring, we may decide on optimal timing for tool change. The necessity of the detection of tool wear, fracture and the abnormal tool state has been emphasized in the machining process. Accordingly, this paper deals with the cutting characteristics of the hot-rolled high strength steels using common HSS drill. The performance variables include drill wear data obtained from drilling experiments conducted on the workpiece. The results are obtained from monitoring of the cutting force and Acoustic Emission (AE) signals, and from the detection of the abnormal tool state with the computer vision system.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.4
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• pp.45-49
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• 2007

When drilling using electrical-discharge machining (EDM), severe electrode wear makes in-process measurements of the depth of the drilled hole and the volume of material removed impossible. To estimate the volume of material removed a reliable real-time discharge pulse counting method is proposed by assuming that the volume removed in EDM is proportional to the number of discharge pulses from an iso-energy pulse generator. The geometry of machined holes, including depths and cross-sectional profiles, is estimated using geometric analysis. A proportional relationship between the volume of material removed and the number of discharge pulses was developed and verified by experiments.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.133-145
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• 1996

This paper presents an indirect cutting force measuring system, which uses the current signals from the AC servo drive units of the horizontal machining center, with its applications to the adaptive regulation of the cutting forces in various milling processes and to the on-line monitoring of tool breakage. A typical model for the feed-drive control system of a horizontal machining center is developed to analyze cutting force measurement from the drive motor. The pulsating milling forces can be measured indirectly within the bandwidth of the current feedback control loop of the feed-drive system. It is shown that the indirectly measured cutting force signals can be used in the adaptive controller for cutting force regulation. The whole scheme has been embedded in the commercial machining center and a series of cutting experiments on the face cutting processes are performed. The adaptive controller reveals reliable cutting force regulating capability against the various cutting conditions. It is also shown that the tool breakage in milling can be detected within one spindle revolution by adaptively filtering the current signals. The effect of the cutter run-out has been considered for the reliable on-line detection of tool breakage.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.41-46
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• 2017

Productivity improvement and cost reduction in the aircraft industry have become major industrial objectives, and improving productivity by reducing machining time has become a key focus. When numerical cutting code is created by CAM software, such as CATIA or UG-NX, it is impossible to control machining feed speed using cutting force changes depending on the machining tool path. However, machining an aircraft engine part from difficult material, such as Inconel 718, takes a long time, and tool chipping or breakage often occurs from forcing the machining path too quickly. This study investigated and verified the reliability of the AdvantEdge production module (PM)using cutting power tests. In particular, diffuser and diffuser case parts were considered, comparing cutting power and machining time using AdvantEdge PM and CATIA.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.3
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• pp.24-31
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• 2004

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.14-21
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• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.304-309
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• 2011

A monitoring system for magnetic abrasive polishing process is necessary to ensure the polishing products the high quality and integrity. Acoustic emission (AE) signal is known to reflect the material removal phenomena in other machining processes. In a case of the magnetic abrasive polishing of non-magnetic materials, application of AE method is very difficult because of lower machining force on the surface of workpiece and the level of AE signal is extremely lower. In this study, AE sensor-based monitoring system is applied to the magnetic abrasive polishing. The relation between the level of the AE RMS and the surface roughness during the magnetic abrasive polishing of magnesium alloy steel is investigated.