• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.129-134
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• 2002

In this study, the compliance measurement and cutting operation in tool - machine tool - workpiece system were carried out for the parameters identification of chatter vibration in turning.

• 한국공작기계학회논문집
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• 제11권6호
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• pp.83-90
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• 2002

In this study, the compliance measurement and cutting operation in tool - machine tool - workpiece system were carried out for the parameters identification of chatter vibration in turning.

• 한국섬유공학회:학술대회논문집
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• 한국섬유공학회 2000년도 봄 한국섬유공학회 학술발표회 논문집(Proceedings of the Korean Textile Conference)
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• pp.335-338
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• 2000

• 한국기계가공학회지
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• 제20권8호
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• pp.93-98
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• 2021

The complex effects of the machining parameters make it is difficult to control and predict surface roughness. The theoretical surface roughness observed during mechanical machining with a round tool is determined by the tool radius and pitch. However, it was revealed that other parameters, such as the depth of cut and cutting speed, also affect surface roughness. This study adapted the Taguchi method, which can analyze the effects of cutting parameters quantitatively with an efficient number of experiments, to optimize the parameters for better surface roughness. Experiments were designed based on an orthogonal array, and the quantitative effects on the surface roughness were analyzed using the S/N ratio. The surface roughness was affected by all parameters, especially the tool radius. The optimum cutting parameter values obtained in this study showed better surface roughness than the other combinations of the parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.292-292
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• 2000

Since high-power CO$_2$ Laser can be make a high densed energy to Local processing area, manufacturing processes using the laser can be processed for very Localized areas at a very fast rate with minimal or no distortion. Accordingly, the laser has been widely used in the fields of thermal manufacturing processes such as welding, fusion cutting, grooving, and heat treatment of metals. In particular, interest in the laser heat treatment process has grown tremendously in the past few years. In this process, maintaining the uniform hardening depth is important problem to obtain good quality products and to reduce heat induced distortion and residual stress. For achieving this objective, we introduced a new design technique of a fuzzy logic controller that greatly simplified the design procedure by defining several simplified design parameters. In the design procedure, the major design parameters of the controller are characterized by identifying several common aspects. From a series of simulation results, we found that the proposed design technique can be effectively used to design of a fuzzy logic controller for the LASER surface hardening process.

• International Journal of Precision Engineering and Manufacturing
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• 제9권4호
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• pp.74-78
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• 2008

High-speed tool steels are extensively used in tooling industries for manufacturing cutting tools, forming tools, and rolls. Electrical discharge machining (EDM) has been found to be an effective process for machining these extremely hard and difficult-to-cut materials. Extensive research has been conducted to identify the optimum machining parameters for EDM with different tool steels. This paper presents a fundamental study of the surface characteristics of SKH-51 tool steel machined by micro-EDM, with particular focus on obtaining a better surface finish. An RC pulse generator was used to obtain a better surface finish as it produces fine discharge craters. The main operating parameters studied were the gap voltage and the capacitance while the resistance and other gap control parameters were kept constant. A negative tungsten electrode was used in this study. The micro-EDM performance was analyzed by atomic force microscopy to determine the average surface roughness and the distance between the highest peak and lowest valley. The topography of the machined surface was observed using a scanning electron microscope and a digital optical microscope.

• 한국기계가공학회지
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• 제13권4호
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• pp.56-68
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• 2014

This paper presents an experiment on the modeling, analysis, prediction and optimization of machining parameters used during the turning process of the low-carbon steel known as ST40. The parameters used to develop the model are the cutting speed, the feed rate, and the depth of the cut. The experiments were carried out under various conditions, with three level of parameters and two different treatments for each level (with and without a lubricant), to determine the effects of the parameters on the surface roughness and electric current consumption. These effects were investigated using response surface methodology (RSM). A second-order model is used to predict the values of the surface roughness and the electric current consumption from the results of experiments which collected preliminary data. The results of the experiment and the predictions of the surface roughness and electric current consumption under both treatments were found to be nearly identical. This result shows that the feed rate is the main factor that influences the surface roughness and electric current consumption.

• 한국기계가공학회지
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• 제18권11호
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• pp.47-56
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• 2019

A deep neural network (DNN) model was proposed to predict the upset in the inertia friction welding process using a database comprising results from a series of FEM analyses. For the database, the upset length, upset beginning time, and upset completion time were extracted from the results of the FEM analyses obtained with various of axial pressure and initial rotational speed. A total of 35 training sets were constructed to train the proposed DNN with 4 hidden layers and 512 neurons in each layer, which can relate the input parameters to the welding results. The mean of the summation of squared error between the predicted results and the true results can be constrained to within 1.0e-4 after the training. Further, the network model was tested with another 10 sets of welding input parameters and results for comparison with FEM. The test showed that the relative error of DNN was within 2.8% for the prediction of upset. The results of DNN application revealed that the model could effectively provide welding results with respect to the exactness and cost for each combination of the welding input parameters.

• 한국기계가공학회지
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• 제19권11호
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• pp.35-41
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• 2020

The structure of the femur bone was analyzed. Moreover, the mechanical strength of the bone was determined by considering two parameters, namely, the outer wall thickness and inner filling density to realize the 3D printing of a cortical bone and spongy bone by using a fused deposition modeling type 3D printer and ABS material. A basic experiment was conducted to evaluate the variation trend in the mechanical strength of the test specimens with the change in the parameters. Based on the results, the parameters corresponding to the highest mechanical strength were selected and applied to the artificial bone, and the mechanical strength of the artificial bones was examined under a load. Moreover, we proposed an approximation method for the 3D printing parameters to enable the comparison of the actual bones and artificial bones in terms of the strength and weight.

• 산업공학
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• 제18권1호
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• pp.94-103
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• 2005

Digital Manufacturing is a technology to facilitate effective product developments and agile productions by digital environments representing the physical and logical schema and the behavior of real manufacturing system including manufacturing resources, processes and products. A digital factory as a well-designed and integrated environment is essential for successful applications of this technology. In this research, we constructed a sophisticated digital factory of an automotive company’ general assembly shop by measuring and 3-D CAD modeling using parametric methods. Specific parameters of each objects were decided by object-oriented schema of the general assembly shop. It is expected that this method is very useful for constructions of a digital factory, and helps to manage diverse information and re-use 3D models.