• Industrial Engineering and Management Systems
• /
• v.9 no.3
• /
• pp.242-250
• /
• 2010

For economical and environmental reasons, the aim of this research is hence to monitor the cutting conditions with the dry cutting, the wet cutting, and the mist cutting to obtain the proper cutting condition for the plain carbon steel with the ball end milling based on the consideration of the surface roughness of the machined parts, the life of the cutting tools, the use of the cutting fluids, the density of the particles of cutting fluids dispersed in the working area, and the cost of cutting. The experimentally obtained results of the relation between tool wear and surface roughness, the relation between tool wear and cutting force, and the relation between cutting force and surface roughness are correspondent with the same trend. The phenomena of surface roughness and tool wear can be explained by the in-process cutting forces. The models of the tool wear with the cutting conditions and the cutting times are proposed to estimate the tool cost for the different cooling strategies based on the experimental data using the multiple regression technique. The cutting cost is calculated from the costs of cutting tool and cutting fluid. The mist cutting gives the lowest cutting cost as compared to others. The experimentally obtained proper cutting condition is determined based on the experimental results referring to the criteria.

• Journal of the Korean Society for Precision Engineering
• /
• v.7 no.2
• /
• pp.47-57
• /
• 1990

In-process recognition of the cutting states is one of the very important technologies to increase the reliability of mordern machining process. In this study, practical methods which use the dynamic component of the cutting force are proposed to recognize cutting states (i.e. chip formation, tool wear, surface roughness) in turning process. The signal processing method developed in this study is efficient to measure the maximum amplitude of the dynamic component of cutting force which is closely related to the chip breaking (cut-off frequency : 80-500 Hz) and the approximately natural frequency of cutting tool (5, 000-8, 000 Hz). It can be clarified that the monitoring of the maximum apmlitude in the dynamic component of the cutting force enables the state of chip formation which chips can be easily hancled and the inferiority state of the machined surface to be recognized. The microcomputer in-process tool wear monitor- ing system introduced in this paper can detect the determination of the time to change cutting tool.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.16 no.1
• /
• pp.156-161
• /
• 1992

In this research a monitoring system for turning using NC information and the current of feed motor as a monitoring signal was developed. The overall system consists of modules such as learning process, NC data transmission, generation of forecast information, signal acquisition, monitoring and post process. In the learning process, the reference data and the cutting force equation necessary for monitoring are obtained from the accumulated monitoring results. In the generation of forecast information, the information of forecasted cutting forces is acquired from the cutting force equation and NC program and appended to each NC block as a monitor code. Reliability of monitoring is improved by using the monitor code in the real-time monitoring. Monitoring module is divided into two parts : the off-line monitoring where errors of NC program are checked and the on-line monitoring where the level of motor current is monitored during cutting operations. If the actual current level exceeds the limit value provided by the monitor code in the level monitoring, it is recognized as abnormal. In the event of abnormal status, the post processor sends the emergency stop signal to NC controller to stop the operation. Actual experiments have shown that the developed monitoring system works well.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.9 no.3
• /
• pp.150-159
• /
• 2000

In-process diagnosis of the cutting state is essential for the automation of manufacturing systems. Especially when the cutting process becomes unstable it induces self-exited vibrations a frequent case of poor tool life rough surface finish damage to the workpiece and the machine tool itself and excessive down time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time monitoring and controlling chatter. This paper describes the detection method of chatter vibration using cutting force in turning process. In order to detect a chatter vibra-tion the dynamic fluctuation of radial force is analyzed since this components is sensitive to the chatter. The envelope sig-nal of radial force has been calculated by the use of FIR Hilbert transformer and it was useful to classify the chatter signal from the dynamically unstable circumstances. It was found that the mode and the mode width were closely correlated with the chatter amplitude was well. Finally back propagation(BP) neural network have been applied to the pattern recognition for the classification of chatter signal in various cutting conditions. The validity of this systed was confirmed by the experiments under the various cutting conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1992.04a
• /
• pp.89-93
• /
• 1992

We experimented cutting characteristics-cutting force, behavior of chip, surface roughness-under low temperature, which generated by liquid nitrogen(77K). The results obtained are as follows; 1) The workpice is became to-195 .deg. C in 5, minutes, and in cooled cutting, cutting force bycooled workpices is stronger than normal temperature condition. Chip thickness is decreasing comparative toN.C and shear angle in shear plane is in creasing. 2) Chip formation becomes long or short tubular chips in turning SXM440, SNCM21 steel, when cutting speed is low and cutting temperatre is cooled condition, but in the STS304 steel the variation of c formations isn't known to. 3) In C.C, surface roughness of workpices is better than N.C and found to make more the crat wearthan N.C 4) It is possible to detect the behavior of chip by monitoring the maximum amplitude of gai value of cutting force.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.4
• /
• pp.72-77
• /
• 2001

Monitoring of the chatter vibration is necessarily required to do automatic manufacturing system. Therefore, we constructed a sensing system using tool dynamometer in order to monitor of chatter vibration on cutting process. Furthemore, an application of neural network using behavior of principal cutting force signals Is attempted. With the error back propagation trining process, the neural network memorized and classified the feature of principal cutting force signals. From obtained result, it is shown that the chatter vibration can be monitored effectively by neural network.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.10a
• /
• pp.30-35
• /
• 2003

Recently, with the rapid growth of information technology, many studies have been performed to implement web-based manufacturing system. Such technologies are expected to meet the need of many manufacturing industries those want to adopt E-manufacturing system for the construction of globalization, agility, digitalization to cope with the rapid changing market requirements. In this research, areal-time web-based machine tool and machining process monitoring system is developed as a first step fur implementing I-manufacturing system. In this system, main spindle motor current and feed current are measured using hall sensors. And the relationship between the cutting force and the spindle motor RMS current at various spindle rotational speed is obtained. Also, a rule-based expert system is developed in order to monitor the machining process effectively. Finally, developed system is applied to real machining process to verify the effectiveness.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.28-33
• /
• 2000

The monitoring of the chatter vibration is necessarily required to do automatic manufacturing system. To this study, we constructed a sensing system using tool dynamometer in order to the chatter vibration on cutting process. And a approach to a neural network using the feature of principal cutting force signals is proposed. with the error back propagation training process, the neural network memorized and classified the feature of principal cutting force signals. As a result, it is shown by neural network that the chatter vibration can be monitored effectively.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.8 no.1
• /
• pp.31-36
• /
• 2009

Micro-machining technology has been adopted for shape accuracy of micrometer and sub-micrometer scale, surface roughness of tens nanometer in industries. In micro-machining process the quality of machined surface is derived from machining condition and tooling. This paper investigates AE(acoustic emission) and cutting force signals according to machined surface quality related to machining condition. Machined surface quality was analyzed by the AE and cutting force parameter which reflect surface morphology. The characteristics of signal were extracted for process optimization by monitoring both the tool condition and the machined surface texture in micro end milling process.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.151-156
• /
• 1995

This paper presents a methodology for real-time detecting and identifying the runout geometry of an end mill. Cutter runout is a common but undesirable phenomenon in multi-tooth machining such as end-milling process because it introduces variable chip loading to insert which results in a accelerated tool wear,amplification of force variation and hence enlargement vibration amplitude. Form understanding of chip load change kinematics, the analytical sutting force 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 total cutting forces can be given as the algebraic multiplication of the Fourier transforms of the local cutting forces and the chip width density of the cutter. Experimental study are presented to validata the analytical model. This study provides the in-process monitoring and compensation of dynamic cutter runout to improve machining tolerance tolerance and surface quality for industriql application.