• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.108-115
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• 1999

Since grinding is a more complicated process than any other machining process, it is hard for operators to setup a grinding machine properly and to find out correctly abnormal grinding states resulting in damages to products. Abnormalities would be caused by improper setup, improper dressing/grinding conditions which are likely to be occurred without skilled operators' attention. In this study, an AE monitoring unit is developed to help operators conduct with ease setup, and set properly dressing/grinding conditions. AErms(root-mean-square) signal being monitored, on-going process states during grinding and dressing is visualized for machine operators to judge whether the processes are in good condition. Evaluation tests are carried out on centerless grinding machines-both cylindrical and internal. The developed AE monitoring system is verified to be useful to check grinding/dressing states in process even in the centerless grinding of which process is most unknown among various grinding methods because of the complex structure.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.162-167
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• 2005

Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.453-458
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• 2016

CFRP (Carbon Fiber Reinforced Plastic) and CFRP-metal stacks have recently been widely used in the aerospace and automobile industries. When CFRP is machined by a brittle fracture mechanism, defect generation behaviors are different from those associated with metal cutting. The machining quality is strongly dependent on the properties of CFRP materials. Therefore, process control for CFRP machining is necessary to minimize the defects of differently manufactured CFRPs. In this study, defects in drilling of CFRP substrates with a variety of fiber directions and resin types are compared with respect to thrust force. An experimental study on material interface detection is carried out to investigate its benefits in process control.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.140-145
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• 2007

To improve productivity of a metal cutting process, it is required to monitor machining stability in real time. Since cutting environment is harsh against sensing conditions due to vibration, chip, and cutting fluid, etc., it is necessary to develop a robust and reliable sensing system for the practical application. In this work, a chatter monitoring system was developed and its effectiveness was proved. Spindle displacement caused by cutting was selected as a main monitoring parameter. A cylindrical capacitive displacement sensor was adopted. Chatter frequencies were identified through modal analysis. To quantify chatter vibrations, chatter correlation coefficient was introduced. The identification of the monitoring system showed a good agreement with the result of experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.690-694
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• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes, a feedrate override Adaptive Control Constant system was developed. This paper presents an explicit pole-assignment PI-control law through spindle motor current monitoring and its application to cutting force regulation for feedrate optimization. An experimental set-up is constructed for the commercial CNC machining center without any major changes of the structure. A data transfer system is constructed with standard interface between an IBM compatible PC and a CNC of the machining center. Experimental results show the validity of the system.

• IE interfaces
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• v.7 no.3
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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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.2
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• pp.91-99
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• 1998

This paper presents a methodology for identifying the cutter runout geometry in end milling process. Cutter runout is common but undesirable phenomenon in multi-tooth machining because it introduces variable chip loading to insert which results in a accelerated tool wear. amplification of force variation and hence enlargement vibration amplitude From understanding of chip load change kinematics, the analytical cutting force convolution model was formulated as the angular domain convolution model was formulated as the angular domain convolution of three dynamic cutting force component functions. By virtue of the convolution integration property, the frequency domain expression of the local cutting forces and the chip width density of the cutter. Experimental study is presented to validate the analytical model. This study provides the in-process monitoring and compensation of dynamic cutter runout to improve machining tolerance and surface quality for industrial application.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.108-114
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• 2007

A new cutting force estimating approach and machining state monitoring examples are presented which uses a cylindrical displacement sensor built into the spindle. To identify the tool-spindle system dynamics with frequency up to 2 kHz, a home-built electro-magnetic exciter is used. The result is used to build an algorithm to extract the dynamic cutting force signal from the spindle error motion; because the built-in spindle sensor signal contains both spindle-tool dynamics and tool-workpiece interactions. This sensor is very sensitive and can measure broadband signal without affecting the system dynamics. The main characteristic is that it is designed so that the measurement is irrelevant to the geometric errors by covering the entire circumferential area between the target and sensor. It is also very simple to be installed. Usually the spindle front cover part is copied and replaced with a new one with this sensor added. It gives valuable information about the operating condition of the spindle at any time. It can be used to monitor cutting force and chatter vibration, to predict roughness and to compensate the form error by overriding spindle speed or feed rate. This approach is particularly useful in monitoring a high speed machining process.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.34-39
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• 2010

In order to achieve and maintain dimensional accuracy in laser micro-machining, dominant parameters such as laser power and laser focus position need to be monitored and controlled real time. Also, in order to selectively machine multi-layered materials, the material being presently machined need to be recognized. This paper presents an auto-focusing (AF) module to keep laser focus on a large-area surface; a real-time laser power stabilizing module based on optical attenuation; and a laser-induced breakdown spectroscopy (LIBS) module. With these monitoring modules, position error in laser focus on a 4" silicon wafer was kept below $4{\mu}m$, initially $51{\mu}m$, and laser power stability of a UV laser source was improved from 1.6% to 0.3%. Also, the material transition from polyimide to copper in machining of FCCL (flexible copper clad laminate) was successfully observed.