• Transactions of Materials Processing
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• v.23 no.1
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• pp.29-34
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• 2014

The damage level of the die surface was predicted by estimating the surface roughness with a finite element analysis and the wear characteristics. Wear and friction tests were conducted to compare the wear characteristics for three kinds of surface treatments - CrN, TiAlN and AlCrN coatings. A prediction model was derived from the surface roughness results with respect to contact pressure and sliding speed which were obtained from the wear test. Surface roughness values for the damage regions of the die surface were compared between the experiments and the prediction model, which shows fairly good agreement with each other.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.813-819
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• 2008

For the wear characteristics assessment of Saemaul train passing through curves, an analysis model for multi-car system has been developed. By using this model and ADAMS/Rail, sensitivity analyses have been conducted for the wear characteristics by changing the related parameters. According to the increase of running speed, the wear number, the sliding mean and friction coefficient were increased. At high speed, the wear number, the sliding mean and friction coefficient of left wheel showed higher than right wheel. If the cant increased, the wear number the sliding mean and friction coefficient increased. but decreased based on the balance cant value by the curvature and running speed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.1042-1047
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• 2001

A mechanistic model is developed to predict the thrust force and cutting torque of drilling process including wear. A mechanistic oblique cutting force model is used to develop the drilling force model. The cutting lips are divided into small elements and elemental forces are calculated by multiplying the specific cutting pressure with the elemental chip area. The specific cutting pressure is a function of chip thickness, cutting velocity, rake angle and wear. The total forces are then computed by summing the elemental forces. Measured cutting forces are in good agreement with the simulated cutting forces.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.8
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• pp.1205-1215
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• 2002

The purpose of this study was to develop a production line using simulation method, which could improve work allocation, labor utility and productivity. Using simulation software AIM, a simulation model of functional sports wear assembly line was developed. A functional sports wear production factory were analysed to gather data necessary for this research. Factory layouts, production facilities, work time of each unit jobs were investigated. The data obtained were used as to build a base simulation model. Then, the base simulation model was verified using the obtained data, such as daily productivity. Using simulation method, low alternative production plans were suggested, which were to enhance productivity, and work efficiency and to reduce queue length and throughput time.

• Journal of the Korean Society for Railway
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• v.10 no.6
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• pp.772-778
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• 2007

For the wear characteristics assessment of Saemaul train passing through curves, an analysis model for multi-car system has been developed. By using this model and ADAMS/Rail, sensitivity analyses have been conducted for the wear characteristics by changing the related parameters. At low speed, the wear number and the sliding mean of right wheel showed higher than left wheel, while those of left wheel showed higher than right wheel at high speed. According to the decrease of curve radius, the wear number and the sliding mean were increased. When the length of transition curve was increased, the wear number and the sliding mean was increased. And according to increase of cant, the wear number and the sliding mean were increased.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3031-3037
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• 1996

In cold forming processes, due to high working pressure action on the die surface, failure mechanics must be considered before die design. One of the main reasons of die failure in industrial application of metal forming technologies is wear. Die wear affects the tolerances of formed parts, metal flow and costs of process etc. The only way to control these failures into devlop methods which allow prediction of die wear and which are suited to be used in the design state in order to optimize the process. In this paper, the forming propcesses that involve cold forward extrusion and wire drawing were simulated by rigid plastic finite element method and its output were used for predicting die wear by Archard wear model. The simulation results were compared with the measured worn dies.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.3
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• pp.44-54
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• 1991

A Study was made on falnk wear in carbide tools in turning SUS304 steel. When an austenitic stainless steel (SUS304 steel) is cut with the tool, saw-toothed chip are produced. It is found that machining SUS304 steel would make a tool worn fast. For increasing productivity, tool wear has to be predicted and controlled. An amended cutting geometry consisting of a negative rake angle ($-6^{\circ}$ ) and a high clearance angle ($-17^{\circ}$ ) is proposed for decreasing carbide tool wear (flank) in the machining of SUS304 steel. The amended cutting geometry is found to make the flank wear lower than a general cutting geometry (rake angle $6^{\circ}$ , clearance angle $5^{\circ}$). The effects of the three cutting variables (cutting speed, feed, tool radius) on the flank wear analyzed by fiting a simple first-order model containing interaction terms to each flank wear parameter by means of regression analysis and the predicted from first-order regression analysis model equation of flank wear.

• Tribology and Lubricants
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• v.28 no.3
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• pp.124-129
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• 2012

The prediction of fretting wear is a significant issue for the design of contacting mechanical components such as flexible couplings and splines, jointed structures and so on. In our earlier study, we developed a numerical model to predict the fretting wear using boundary element method. The developed algorithm needs experimental fretting wear coefficients and friction coefficients between two moving materials to get more reliable results. In this study, therefore, we demonstrated the measurement method of the fretting wear coefficients and friction coefficients using disk on plate tribometer with piazo actuator and gap sensor. For four different material combinations, the fretting wear coefficients and friction coefficients are acquired through the fretting wear experiment and the analysis of the measured values. Thess results are useful to predict the quantative fretting wear rate in the developed algorithm.

• Tribology and Lubricants
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• v.5 no.1
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• pp.36-43
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• 1989

Scanning electron microscopic observations were carried out on the worn surface and the wear debris of ceramic materials to investigate the wear mechanism of those in dry rolling contact. It was found from the scanning electron microscopic observations that the wear in ceramic materials is related to brittle fracture and has two types of wear mechanisms, small scale wear and larvae scare wear. Plate-like wear debris were created from the initial surface cracks and defects. The small scale wear was related to real contact area and large scale wear was related to HertzJan contact area. A wear model was proposed on the basis of scanning electron microscopic observations.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1026-1034
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• 2021

Tire wear and defect are important factors for safe driving condition. These defects are generally inspected by some specialized experts or very expensive equipments such as stereo depth camera and depth gauge. In this paper, we propose tire safety vision inspector based on deep neural network (DNN). The status of tire wear is categorized into three: 'safety', 'warning', and 'danger' based on depth of tire tread. We propose an attention mechanism for emphasizing the feature of tread area. The attention-based feature is concatenated to output feature maps of the last convolution layer of ResNet-101 to extract more robust feature. Through experiments, the proposed tire wear classification model improves 1.8% of accuracy compared to the existing ResNet-101 model. For detecting the tire defections, the developed tire defect detection model shows up-to 91% of accuracy using the Mask R-CNN model. From these results, we can see that the suggested models are useful for checking on the safety condition of working tire in real environment.