• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.2
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• pp.110-116
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• 2011

The current study investigated the friction property of angle and width effect for micro-scale grooved crosshatch pattern on SKD11 steel surface against bearing steel using pin-on-disk type. The samples fabricated by photolithography process and then these are carry out the electrochemical etching process. We discuss the friction property due to the influence of a hatched-angle and a width of groove on contact surface. We could be explained the lubrication mechanism for a Stribeck curve. So It was found that the friction coefficient depend on an angle of the crosshatch on contact surface. It was thus verified that micro-scale crosshatch grooved pattern could affect the friction reduction. Also, it is play an important a width of groove to be improved the friction property. I was found that friction property has a relationship between a width and an angle for micro-grooved pattern.

• Journal of the Korean institute of surface engineering
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• v.35 no.3
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• pp.133-140
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• 2002

The Ti-Si-N coating layers were synthesized on SKD 11 steel substrate by a DC reactive magnetron co-sputtering technique with separate Ti and Si targets. The high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS) analyses for the coating layers revealed that microstructure of Ti-Si-N layer was nanocomposite, consisting of nano-sized TiN crystallites surrounded by amorphous $Si_3$$N_4$ phase. The highest hardness value of about 39 GPa was obtained at the Si content of ~11at.%, where the microstructure had fine TiN crystallites (about 5nm in size) dispersed uniformly in amorphous matrix. As the Si content in Ti-Si-N films increased, the TiN crystallites became from aligned to randomly oriented microstructure, finer, and fully penetrated by amorphous phase. Free Si appeared in the layers due to the deficit of nitrogen source at higher Si content. Friction coefficient and wear rate of the Ti-Si-N coating layer significantly decreased with increase of relative humidity. The self-lubricating tribe-layers such as $SiO_2$ or (OH)$Si_2$ seemed to play an important role in the wear behavior of Ti-Si-N film against steel.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.5-11
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• 2016

This study analyzed the damage to a slitting knife after cutting steel sheets. Damages to the structure were observed and wear tests were conducted. In addition, the degradation on the damaged and undamaged parts was compared with a micro Vickers hardness test. Weibull statistical analysis was carried out in order to evaluate the reliability of the micro Vickers hardness measured data. Spalling of the edge portion occurred by degradation during use over a long period. Rough parts in the specimens were caused by damage because the slitting knife was used for 1 year. The friction coefficient and wear loss at the damaged parts of the knife edge were slightly larger from shock due to repetitive cutting operation. The micro Vickers hardness followed a two-parameter Weibull probability distribution.

• Journal of the Korean institute of surface engineering
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• v.36 no.2
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• pp.122-127
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• 2003

Ti - Si - N hard films were deposited on SKD11 steel substrates by a hybrid deposition system, where TiN was deposited by AIP method while Si was incorporated by sputtering one. The microstructure of Ti-Si-N films was revealed to be a composite of TiN crystallites and amorphous Si3N4 by instrumental analyses. The highest hardness value of about 45 Gpa was obtained at the Si content of around 7.7 at.%. With increase of Si content, the size of TiN crystallites was reduced and their distribution was changed from aligned to randomly orientated states. Surface roughness of Ti-Si-N film also decreased with increase of Si content.

• Journal of the Korean institute of surface engineering
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• v.39 no.2
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• pp.70-75
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• 2006

As technology advances, there is a demand for development of hard, solid lubricant coating. (Ti,Cr)N-$MoS_2$, films were deposited on SKD 11 tool steel substrate by co-deposition of $MoS_2$, with (Ti,Cr)N using a D.C. magnetron sputtering process. The influence of the $N_2/Ar$ gas ratio, the deposition temperature, the amount of $MoS_2$ in the films, and the bias voltage on the mechanical and the structural properties of the films were investigated. Wear tests were performed on the films deposited in various conditions.

• Journal of the Korean institute of surface engineering
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• v.37 no.1
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• pp.1-4
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• 2004

MoS$_2$-Ti films were deposited on SKD-11 tool steel substrate by a D.C. magnetron sputtering system. The influence of deposition parameters on the adhesion of the films was investigated by the scratch test. Crosssection morphology was evaluated using FE-SEM. The plasma etching played an important role on the adhesion of the films. The appropriate etching conditions roughened the surface, resulting In the improved adhesion of the film. The adhesion of the film increased with the interlayer thickness up to 110 nm and then decreased slightly with further increasing of interlayer thickness. The adhesion was highest at a bias voltage of -50 V. Further increase of the bias voltage decreased the film adhesion.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.4
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• pp.76-82
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• 2018

3D formed Electrical Discharge Machining (EDM) and hole EDM were conducted for die and mold manufacturing with electrodes which were made by mechanical machining and wire EDM. It is difficult to machine the hardened material after heat treatment and quenching with traditional machining. The only method of machining hardened material is die-sinking EDM. In this research, hole EDM was conducted for heat-treated cold-worked tool steel (SKD11) for use as a die material. The EDM surfaces were analyzed by pulse-on time and peak current of EDM current, according to the machining conditions of EDM. The EDM surface profiles were affected by the peak current. The contribution of each factor is peak current (91.63%) and pulse-on time (0.93%). The best surface roughness was obtained with a $130{\mu}s$ pulse-on time and a 14.2 A peak current. With uniform EDM processing, the surface deteriorated with increasing pulse-on time and peak current. The thickness of the solidified layer induced by EDM was increased as the peak current, crater shapes, and erupted shapes of EDM surfaces were increased. Therefore, microcracking gaps induced by surface tension were increased.

• Tribology and Lubricants
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• v.25 no.3
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• pp.163-170
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• 2009

We developed a compact micro indentation testing device (designated SNUT) which is capable to measure Young's modulus of a sample using depth and applied load data during indentation. Performance of this device was evaluated using pure Ti, pure Ni, and die steel (SKD11). As a result of analysing the indentation test data, the frame compliance $C_f$ was found to influence mainly the modulus by 80% among several factors affecting accuracy of Young's modulus. Project area, which was determined by indirect indentation method, was modified using direct SEM observation. Finally, Young's modulus error was reduced to 5% after taking into consideration the frame compliance and modified projected area from 80% error without any these two correction factors. The performance of SNUT and MTS instruments was compared using same specimen (pure Ti).

• 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 Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.117-124
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• 2021

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.