• 한국기계가공학회지
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• 제12권1호
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• pp.9-14
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• 2013

In recent years, high hardness steel is used for most of the material in many areas including aircraft, nuclear power, space exploration and automotive parts. Low CBN tools are widely used in industrial field which can effectively process high hardness steel of HRC 45 or harder. The results of this study demonstrated, when high hardness steel, SCM440 is turned with Low CBN tools coated with TiN and TiAlN coatings respectively, that both the thrust force and cutting force tends to increase with more increase in cutting force than thrust force, as the feed rate increases at constant cutting speed. In addition, the size of the cutting force and thrust force does not change with the increased cutting speed at the same feed rate, but the tool life is reduced if the cutting speed is increased to shorten the machining time. Therefore, it is recommended to limit the cutting speed at 250 m/min maximum or less. Furthermore, comparing the cutting force of the three tools at the same cutting condition, Tin coating tool showed the smallest cutting force and Low CBN was the next, and the TiAlN coating tools showed the largest cutting force.

• 한국정밀공학회지
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• 제21권4호
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• pp.64-71
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• 2004

The growing need for higher precision and productivity in manufacturing industry has lead to an increased interest in computer numerical control (CNC) systems. It is well known fact that the cross-coupling controller (CCC) is an effective method for contouring applications. In this paper, a multi-axis contour error controller (CEC) based on a contour error vector using parametric curve interpolator is introduced. The contour error vector is a vector from the actual tool position to the nearest point on the desired path. The contour error vector is the closest error model to the contour error. The simulation results show that the CEC is more accurate than the conventional CCC for a biaxial motion system. In addition, the experimental results on 3-axis motion system show that the CEC is simply applied to 3-axis motions and contouring accuracy is significantly improved.

• 한국공작기계학회논문집
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• 제15권3호
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• pp.1-7
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• 2006

By the reason of increased demand of high productivity, the researches on manufacturing process and equipments for reducing cycle time have been made in many directions of a machine tool industries. Especially high productivity is very important to machining center with high-speed spindle. This paper proposed method of reducing T-T(tool to tool) time which results in shorter unclamping time. T-T time varies as factors such as a hydraulic system, a drawbar mass, a flow meter, a disc spring, piston and pipe diameters. In this paper We could find design factors has much influence on decreasing the unclamping time using DOE(Design of Experiment) and optimized the level of the factors using AMESim $4.0^{(R)}$ and visualNastran $4D^{(R)}$ Finally, we have verified improved result of the optimized factors with initial design.

• 한국정밀공학회지
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• 제19권4호
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• pp.147-153
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• 2002

In the preceding research, the active balancing device, which is an electro-magnetic type, has been developed and active balancing method using influence coefficient method is also proposed. The stability of active balancing control is studied in this paper. A stable condition for active balancing control is derived by estimating errors of influence coefficients. A gain scheduling control using influence coefficients of the reference model is proposed when dynamic characteristic of rotor system is changed. The stability of the balancing method is verified by experiments.

• 한국기계가공학회지
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• 제18권9호
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1996년도 제23회 학술대회
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• pp.53-59
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• 1996

The new trends in main spindle design of Machining Center are focused on high-speed, high-precision and high-stiffness. As a main spindle bearing, the angular-contact ball bearing is well used. A rolling bearing is usually only a small part of a larger mechanical system, but its performance can have a great influence on the functioning of the whole machine. This work is about fatigue life tester design and monitoring of defected rolling-element bearings. The major work is done via experiments and the vibration signal is analysised by means of frequency spectrum technique. By analyzing the frequency spectrum, it is possible to view the condition of the bearings.

• 한국분말재료학회지
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• 제20권5호
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• pp.355-358
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• 2013

Micro trench structures are applied in gratings, security films, wave guides, and micro fluidics. These micro trench structures have commonly been fabricated by micro electro mechanical system (MEMS) process. However, if the micro trench structures are machined using a diamond tool on large area plate, the resulting process is the most effective manufacturing method for products with high quality surfaces and outstanding optical characteristics. A nonferrous metal has been used as a workpiece; recently, and hybrid materials, including polymer materials, have been applied to mold for display fields. Thus, the machining characteristics of polymer materials should be analyzed. In this study, machining characteristics were compared between nonferrous metals and polymer materials using single crystal diamond (SCD) tools; the use of such materials is increasing in machining applications. The experiment was conducted using a square type diamond tool and a shaper machine tool with cutting depths of 2, 4, 6 and 10 ${\mu}m$ and a cutting speed of 200 mm/s. The machined surfaces, chip, and cutting force were compared through the experiment.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2001년도 추계산학기술 심포지엄 및 학술대회 발표논문집
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• pp.99-103
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• 2001

Though the research and the development in the field of machine tool was focused on high precision and high speed machine these days, traditional gear reduction device has been used to increase the cutting force which was transmitted from power source, motor In this study, analysis of 2 step gear reducer used in machining center spindle was carried out by using APM WinMachine which is commercial software for the analysis of machine element and system. For the analysis of this device, first of all, the analysis of power source and the transmitting of it were carried out. Then, machine elements like gear, shaft, bearing, and the forth, was analyzed in the view point of life time, static strength, stiffness, fatigue failure, etc. Consequently, we can estimate them and introduce new idea of the design modification of reduction device by this study.

• 한국기계가공학회지
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• 제15권5호
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• pp.1-7
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• 2016

In the present study, a plastic surface end-milling was implemented to investigate the effects of processing parameters on surface quality. The end milling can be considered an efficient method for rapid prototyping of thermoplastic bio-systems since it exhibits several beneficial functions including short fabrication time and high dimensional accuracy. In this regard, putative biocompatible thermoplastic materials, such as PMMA, PET, and PC, were chosen as workpiece materials. Among the relevant processing parameters influencing the surface quality of the final product, depth of cut, feed rate, and spindle speed were considered in the present study. The roughness of surfaces machined under various conditions was measured to elucidate the effect of each parameter. We found that the cut depth was the most significant factor. Heat generation during machining also had a remarkable effect. From these investigations, an appropriate combination of processing conditions specific to each type of use and end-product could be found. This optimization can be useful in end-milling of thermoplastic bio-systems.

• 한국기계가공학회지
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• 제20권9호
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.