• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.781-785
• /
• 2005

Cutting forces and tool deflection in end milling are represented as the closed form of tool rotational angle and cutting conditions. The discrete cutting forces caused by tool entry and exit are continued using the Fourier series expansion. Tool deflection is predicted by direct integration of the distributed loads on cutting edges. Cutting conditions, tool geometry, run-outs and the stiffness of tool clamping pan are considered for cutting forces and tool deflection estimation. Compared to numerical methods, the presented method has advantages in short prediction time and the effects of feeding and run-outs on cutting forces and tool deflection can be analyzed quantitatively. This research can be effectively used in real time machining error estimation and cutting condition selection for error minimization since the ferm accuracy is easily predicted by tool deflect ion curve.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.485-489
• /
• 2004

Cutting force is important to understand cutting process in milling. To measure cutting force, tool dynamometer is widely used but it is hard to apply in workshop condition. Cutting force measurement which doesn't affect cutting process is needed. Using relations between cutting force and spindle displacement, cutting force can be predicted. Cylindrical capacitive sensor was used to measure spindle displacement during cutting. And signals from tool dynamometer collected to compare with spindle displacement. The result shows spindle displacement has a linear relation with cutting force. Using this result, a simple method to predict cutting force could be applied at workshop condition.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2000.04a
• /
• pp.67-70
• /
• 2000

The tool life is not long enough under sever forming condition in warm forging. The tool life is affected by wear heat fatigue plastic deformation and so on. Especially wear is one of the most serious factors for tool life. To increase tool life we should consider various factors like processing design die design die materials lubrication and cooling system This study design to obtain the steady state temperature of die by FEM analysis under several conditions of cooling. There are four cooling conditions in this study no cooling internal cooling external cooling and both internal and external cooling. With above obtained temperatures tool life is predicted using Archard's model that is considered softening of die. The effect of internal cooling system is better than that of externally cooled die. To predict the die life the steady state temperature is calculated by using mean temperature of die. Considering only wear the die life much longer as the cooling effect is bigger. The more accurate die life will be predicted if we consider heat crack as well as wear.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1998.03a
• /
• pp.172-177
• /
• 1998

An experimental study on the prediction of grinding wheel wear by dual detection methods was conducted by the laser displacement and acoustic emission(AE) system. The laser displacement sensor was located above the head of the grinding wheel and the AE sensor was set under the workpiece, where the wheel were condition can be detected. It was found that the dual detection methods by laser displacement system and AE system made it possible to predict the wheel wear. From the experiments, the root mean square(RMS) values both methods was found to be proportional to the grinding wheel wear.

• International Journal of Air-Conditioning and Refrigeration
• /
• v.15 no.3
• /
• pp.137-146
• /
• 2007

CFD simulation is a very useful tool to predict the concentration of contaminant generated from the building materials in a single room. However, there is a limitation on analyzing air movement and contaminant concentration in a multi-room when the door of each room is closed. In this study, network based simulation was coupled with contaminant simulation for the multi-room condition, using an network simulation tool 'ESP-r'. The coupled simulation was first validated with experimental measurements which performed to define the characteristics of the analyzed space prior to the simulation, and indoor air flow and contaminant concentration between rooms were then analyzed when the door of each room was open and closed in the case of natural and forced ventilation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.61-66
• /
• 1994

Tool condition monitoring is one of the most important aspects to improve productivity and quality and to achieve intelligent machining system. The tool state is classified into three groups as chipping, wear and fracture. In this study, wear of a ceramic cutting tool for hardened die material (SKD11) was investigated. Flank wear was occured more dominant than crarer wear. Therefore, to predict flank wear, the modeling of cutting force has been performed. The modeling of cutting force by an assumption that act the stress distribution on the tool face obtained through a numerical analysis. The relationships between the cutting force and the tool wear can be constructed by machining paraneters with cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions of the flank wear is approximately in good agreement with experimental result.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.5 no.3
• /
• pp.15-21
• /
• 1996

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE(Acoustic Emission) signals, while cutting stainless steel by end mill on the machining center. The results of this study were that RMSAE tends to increase linearly along with the increase of the cutting speed, and it was more sensitive to depth of cut than to the variation of feed rate at the same cutting conditions, and RMSAE increases around 0.21mm flank wear hereby AE-HIT also increases. AE signals depend upon tool wear and fracture from the above results. Therefore, the AE signals can be utilized in order to monitor the tool condition.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.4
• /
• pp.161-167
• /
• 2020

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.6 s.99
• /
• pp.635-644
• /
• 2005

This paper is. a study on relation between road traffic noise(RTN) and sound power level(PWL). At present, many experimental formulae and prediction formulae are used for prediction of RTN. But these formulae are difficult to appiy to the metropolitan area because these formulae are inaccurate in the different condition from reference condition. This paper calculate RTN and PWL of each prediction formula, choose the best one and make a noise map of the subject area. Procedure is as follows. First, calculate $L_{eq}$ of RTN using experimental formulae and prediction formulae. Second, calculate PWL using $L_{eq}$ of RTN and distance attenuation for point source at semi-free field. Third, choose the most accurate formula. And finally, make a noise map of the subject area at present and future. The result using noise map will be able to apply to application field. Noise mapping tool used on this paper is Raynoise program using Ray Tracing Method(RTM), Mirror Image Source Method(MISM) and Hybrid Method(HM).

• Proceedings of the Korean Nuclear Society Conference
• /
• 1997.05a
• /
• pp.356-361
• /
• 1997

To investigate parametric effect on CHF and to get CHF data, experimental study has been performed with vertical round tubes under the condition of low pressure and low flow (LPLF). Test sections are made of Inconel-625 tube and have the geometry of 8 and 10 mm in diameter, and 0.5 and 1.0 m in heated length. All experiments have been conducted at the pressure of under 9 bar, the mass flux of under 250 kg/$m^2$ and the inlet subcooling of 350 and 450 kJ/kg, for stable upward flow with water as a coolant. Flow regime analysis has been performed for obtained CHF data with Mishima's flow regime map, which reveals that most of the CHF occur in the annular-mist flow regime. General parametric trends of the collected CHF data are consistent with those of previous studies. However, for the pressure effect on CHF, two different are observed; For relatively high mass flux, CHF increases with pressure and far lower mass flux, CHF decrease with pressure. Using modern data regression tool, ACE algorithm, two new CHF correlations for LPLF condition are developed based on local condition and inlet condition, respectively. The developed CHF correlations show better prediction accuracy compared with existing CHF prediction methods.