• 한국공작기계학회논문집
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• 제17권1호
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.1021-1024
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• 2001

Out of all metal-cutting processes, 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. In this paper, the vision system of the sensing methods of drill flank wear on the basis of image processing is used to detect the wear pattern by non-contact and direct method and get the reliable wear information about drill. In image processing of acquired image, median filter is applied for noise removal. The vision flank wear area of the drill was measured. Backpropagation neural networks (BPns) were used for no-line detection of drill wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, thrust and torque signals. The output was the drill wear state which was either usable or failure. Drilling experiments with various spindle rotational speed and feed rates were carried out. The learning process was peformed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• 한국공작기계학회논문집
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• 제12권5호
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• pp.46-52
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• 2003

End-milling have been used widely in industrial system because it is effective to a material manufacturing with various shape. Recently the end-milling processing is needed the high-precise technique with good surface roughness and rapid time in precision machine part and electronic part. The optimum surface roughness has an effect on end-milling condition such as, cutting direction spindle speed, feed rate and depth of cut, etc. Therefore this study was carried out to presume for mutual relation of end-milling condition to get the optimum surface roughness by regression analysis. The results shown that coefficient of determination($\textrm{R}^2$) of regression equation has a fine reliability of 87.5% and regression equation of surface rough is made by regression analysis.

• 한국기계가공학회지
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• 제20권6호
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• pp.10-16
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• 2021

Drilling is a crucial process that takes up a significant amount of weight during machining operations. In addition, drill tip-type tools and related operations have been developed for manufacturing industries to achieve economic efficiency. In this study, SM45C carbon steel, widely used for machine structures, was utilized as the working material after quenching and tempering. Insert-tip types of carbide tools, such as TiN and TiAlN, were used as tool materials. Drilling conditions such as the spindle revolution, feed rate, step of cut, and tool diameter were used to measure roughness, roundness, and straightness using the orthogonal array table statistical method. The surface roughness, roundness, and straightness characteristics based on the conditions were analyzed using ANOVA. The results showed that the spindle speed and feed rate were the main factors influencing carbide insert-tip drilling under the same conditions as the experimental conditions.

• 한국CDE학회논문집
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• 제18권2호
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• pp.148-154
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• 2013

Han-ok (the Korean traditional house) is famous for its beauty and healthful aspects. However, its construction cost is too high because of the manual process of parts such as rafter, timber, etc. These days, many people want to build a modernized Korean traditional house at a low cost. In order to do so, the rafter machining process is required to be automatized using a CNC machine. It is also observed that, generally the timber does not have a uniform shape. Therefore, it is also needed to examine the timber shape before starting its processing. This paper presents the concept design of the rafter processing CNC machine, and a 3D laser scanning system. The laser scanner is developed to acquire 3D details of the timber shape. Furthermore, the results of simulated experiments are presented to investigate surface roughness during the machining process of the timber. Since cutting parameters largely influence on surface roughness and cusps formation, it is needed to achieve optimal machining parameters. Several experiments were carried out changing cutting parameters such as cutting tool diameter, feed-rate, and spindle speed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1995년도 춘계학술대회 논문집
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• pp.1-8
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• 1995

This paper proposed a simple method for measuring surface roughness of ground surface. utilizing non-contact in-process measuring system using the diode laser. The measurement system is consisted of a laser unit with a diode laser and a cylindrical lens a detecting unit with polygon mirror and CCD array sensor. and a signal processing unit with a computer and device. During operation, this measuring system can provide information on surface roughness in the measuring distance with a single sampling and simultanilusly monitor the state of the grind wheel. The experimental results, showed that the increase of the feed rate and the dressing speed an caused increase in the surface roughness and when the surface roughness is 4Rmax-10Rmax, the cutting speed is 1653m/min-1665m/min. the feed rate is 0.2m/min-0.9m/min, the dressing speed is 0.2mm/rev-0.4mm/rev, the stylus method and the in-process method can be obtained the same results. thus under limited working conditions. using the proposed system. the surface roughness of the ground surface during cylindrical grinding can be obtained through the in-process measurement method using the diode laser.

• 한국기계가공학회지
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• 제13권1호
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• pp.92-99
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• 2014

An aspherical lens, which resolves several problems with a spherical lens,typically serves asa key part of an optical system. Generally, an aspherical lens is fabricated using a diamond turning machine or by mean of injection molding. However, residual stress and/or tool marks can arise when using a commercial fabricating method such as DTM or injection molding. A polishing process, thus, is commonly used to obtain a high-precision aspherical lens. In this study, a polishing method using MR fluid was applied to minimize several problems, in this case residual stress and the creation of tool marks, during the cutting process. The MR polishing system was developed to polish aspherical lenses. A series of experiments were performed to obtain a very fine surface roughness. PMMA (the lens material for molding) was used as a workpiece, and the gap size, magnetic field intensity, wheel speed and feed rate were selected as the parameters in this study. Finally, a very fine surface roughness of Ra=2.12nm was obtained after MR polishing.

• 대한산업공학회지
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• 제29권1호
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• pp.21-31
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• 2003

Determination of operational dimensions and tolerances is complex if there exist inconsistencies between operational and design specifications. Dimension and tolerance charts (D&T charts) have been used to establish the relationships among operational dimensions in complex machining. This chart proves that individual operations can be harmonized when they are interconnected. However, it is hard to generate the chart manually. Because operational dimensions and tolerances must meet the design specifications, the dimensions and tolerances of interconnected operations have to be verified serially for economical operations. In this paper, the chart is automatically generated from the interconnected operations. More importantly, all operational dimensions and tolerances displayed in the chart have been verified by using LP to meet the design specifications. Finally, the chart is converted to an operational routing sheet that contains a detailed process plan along with cutting speed, feed rate, and operational references based on material hardness, surface finish, and tool nose radius.

• International journal of advanced smart convergence
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• 제4권1호
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.