• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.10
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• pp.60-67
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• 2019

Recently, lightweight materials such as Ti alloys have been used increasingly in the aerospace and high-tech industries for weight loss and fuel efficiency. Because of built-up edges and workpiece deflection due to low stiffness, the Ti alloys have poor machinability. In our study, systematic experiments were conducted to investigate the milling characteristics of the Ti alloy (Ti-6A1-4V) with endmills. The independent variables in the experiment were spindle speed, feed per tooth, and axial depth. Cutting force, acceleration RMS, and surface roughness were measured. Using the response surface method, the optimal cutting conditions were analyzed to improve machining quality and productivity.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.2
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• pp.137-143
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• 2022

Composite materials, being light-weight and of high mechanical strength, are increasingly used in various industries such as the aerospace, automobile, sporting-goods manufacturing, and ship-building industries. Recently, manufacturing of composite materials using 3D printers has increased. 3D-printed composite materials are made in free-form and adapted for end-use by adjusting the fiber content and orientation. However, research on the machining of 3D printed composite materials is limited. The aim of this study is to develop a machine learning method to select machining conditions for machining of 3D-printed composite materials. The composite material was composed of Onyx and carbon fibers and stacked sequentially. The experiments were performed using the following machining conditions: spindle speed, feed rate, depth of cut, and machining direction. Cutting forces of the different machining conditions were measured by milling the composite materials. PCA, a method of machine learning, was developed to select the machining conditions and will be used in subsequent experiments under various machining conditions.

• Journal of the Korean institute of surface engineering
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• v.40 no.4
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• pp.170-174
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• 2007

High Velocity Oxygen Fuel (HVOF) thermal spray coating of nano size WC-Co powder (nWC-Co) has been studied as one of the most promising candidate for the possible replacement of the traditional hard plating in some area which causes environmental and health problems. nWC-Co powder was coated on Inconel 718 substrates by HVOF technique. The optimal coating process obtained from the best surface properties such as hardness and porosity is the process of oxygen flow rate (FR) 38 FMR, hydrogen FR 57 FMR and feed rate 35 g/min at spray distance 6 inch for both surface temperature $25^{\circ}C\;and\;500^{\circ}C$. In coating process a small portion of hard WC decomposes to less hard $W_2C$, W and C at the temperature higher than its decomposition temperature $1,250^{\circ}C$ resulting in hardness decrease and porosity increase. Friction coefficient increases with increasing coating surface temperature from 0.55-0.64 at $25^{\circ}C$ to 0.65-0.76 at $500^{\circ}C$ due to the increase of adhesion between coating and counter sliding surface. Hardness of nWC-Co is higher or comparable to those of other hard coatings, such as $Al_2O_3,\;Cr,\;Cr_2O_3$ and HVOF Tribaloy 400 (T400). This shows that nWC-Co is recommendable for durability improvement coating on machine components such as high speed spindle.

• Journal of the Korean Society for Heat Treatment
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• v.25 no.1
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• pp.6-13
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• 2012

HVOF thermal spray coating of 80%WC-CoFe powder is one of the most promising candidate for the replacement of the traditional hard chrome plating and hard ceramics coating because of the environmental problem of the very toxic $Cr^{6+}$ known as carcinogen by chrome plating and the brittleness of ceramics coatings. 80%WC-CoFe powder was coated by HVOF thermal spraying for the study of durability improvement of the high speed spindle such as air bearing spindle. The coating procedure was designed by the Taguchi program, including 4 parameters of hydrogen and oxygen flow rates, powder feed rate and spray distance. The surface properties of the 80%WC-CoFe powder coating were investigated roughness, hardness and porosity. The optimal condition for thermal spray has been ensured by the relationship between the spary parameters and the hardness of the coatings. The optimal coating process obtained by Taguchi program is the process of oxygen flow rate 34 FRM, hydrogen flow rate 57 FRM, powder feed rate 35 g/min and spray distance 8 inch. The coating cross-sectional structure was observed scanning electron microscope before chemical etching. Estimation of coating porosity was performed using metallugical image analysis. The Friction and wear behaviors of HVOF WC-CoFe coating prepared by OCP are investigated by reciprocating sliding wear test at $25^{\circ}C$ and $450^{\circ}C$. Friction coefficients (FC) of coating decreases as sliding surface temperature increases from $25^{\circ}C$ to $450^{\circ}C$.

• Korean Journal of Materials Research
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• v.20 no.11
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• pp.559-569
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• 2010

The liquid-phase sintering method was used to prepare a glass lens forming core composed of SiC-$Al_2O_3-Y_2O_3$. Spark plasma sintering was used to obtain dense sintered bodies. The sintering characteristics of different SiC sources and compositions of additives were studied. Results revealed that, owing to its initial larger surface area, $\alpha$-SiC offers sinterability that is superior to that of $\beta$-SiC. A maximum density of $3.32\;g/cm^3$ (theoretical density [TD] of 99.7%) was obtained in $\alpha$-SiC-10 wt% ($6Al_2O_3-4Y_2O_3$) sintered at $1850^{\circ}C$ without high-energy ball milling. The maximum hardness and compression stress of the sintered body reached 2870 Hv and 1110 MPa, respectively. The optimum ultra-precision machining parameters were a grinding speed of 1243 m/min, work spindle rotation rate of 100 rpm, feed rate of 0.5 mm/min, and depth of cut of $0.2\;{\mu}m$. The surface roughnesses of the thus prepared final products were Ra = 4.3 nm and Rt = 55.3 nm for the aspheric lens forming core and Ra = 4.4 nm and Rt = 41.9 for the spherical lens forming core. These values were found to be sufficiently low, and the cores showed good compatibility between SiC and the diamond-like carbon (DLC) coating material. Thus, these glass lens forming cores have great potential for application in the lens industry.