• Tribology and Lubricants
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• v.39 no.5
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• pp.216-219
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• 2023

This study employs molecular dynamics simulations to investigate the material behavior of workpieces in waterjet machining processes. To gain fundamental insights into waterjet machining, simulations were conducted using pure water, excluding abrasive particles. The simulation model comprised thousands of water molecules interacting with a single crystal metal workpiece. Water molecule clusters were imparted with various velocities to initiate collisions with the metal workpiece. The material behavior of the metal surface was analyzed with respect to the applied velocity conditions, considering the intricate interplay between water molecules and the workpiece at the atomic scale. The results demonstrated that the machining of the metal workpiece occurred only when water molecules were endowed with velocities above a certain threshold. In cases where energy was insufficient, the metal workpiece exhibited a slight increase in surface roughness due to mild plastic deformation, without undergoing substantial material removal. When machining occurred, the ejection of material revealed a 3-fold symmetric pattern, confirming that material removal in waterjet machining of the metal workpiece is primarily driven by plastic deformation-induced material ejection. This research provides crucial insights into the mechanisms underlying waterjet machining and enhances our understanding of material behavior during the process. The findings can be valuable in optimizing waterjet machining techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.1038-1043
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• 1997

To adapt the neural network proess for the purpose of determination of optimal utting onditions (optimal cutting speed and feed rate), some selection strategies for the machining factors are necessary, which is considered planning cutting process. In this case, factors that have both nonlinearity and strong relationship must be selected. Although tool grade and chemical properties of workpiece material have strong effect to cutting speed, it's not easy to find a analytic relation between them. In this paper, a mathematical method for determining the optimal amount of cutting (depth of cut, feed rate) is presented by tool goemetry and heat generation during cutting process. And various tool grade and workpiece material groups ase classified based on its chemical properties. Thier chemical composition and hardness are used as input pattern for neural network learnig. The result of learning shows the relationship between tool grade and workpiece material and it is proved that it can be used as a sub-system for automatic process planning system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.4
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• pp.57-63
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• 2011

The aim of this study is to analyze turning process using commercial FEM simulation code. Various simulation models of orthogonal cutting process for 3 layers of metallic material have been simulated and analyzed. The workpiece material used for the orthogonal plane-strain metal cutting simulation consists of three layers, which are Allow Tool Steel, Aluminum and Stainless Steel. The finite element model is composed of a deformable workpiece and a rigid tool. The tool penetrates through the workpiece at a constant speed and constant feed rate. As an analytical result, detailed cutting temperature, strain, pressure, residual stress for both a tool and each layer of workpiece were obtained during the turning process. It has been closely observed that the chip flow curve deforms continuously.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.79-89
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• 1998

In determining optimal cutting condition for face milling operation, tool wear is an important factor. For the purpose of establishing the relationship between various machining factors and tool wear, cutting tests have been performed. As a result, hardness and chemical composition of workpiece material, chemical composition and grain size of cutting tool and cutting speed have been selected as machining factors. In addition, relationship between feed rate and workpiece hardness has been observed. Prior to utilizing cutting conditions recommended by ‘Machining Data Handbook(MDH)’ as a knowledge base, an analysis for the validity of the MDH has been provided. Based on this analysis, tool life criteria applied by MDH has been modified. Finally, using MDH recommended data for neural network trainning, the results from the trained neural network for optimal cutting condition for some given workpiece and cutting tool can be used as reference cutting conditions.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.70-77
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• 2003

The centerless through-feed grinding is performed by passing the workpiece between the grinding wheel and the regulating wheel. So, the amount of removed material around the leading end, of the workpiece is always more than that around the trailing end until the leading end leaves the grinding wheel. Because of this, there are differences in diameters along the workpiece axis during grinding, and workpiece axis is not parallel to the grinding wheel axis and the contact lines between the workpiece and wheels. Thus the ground workpiece shows tapering error inherently. To eliminate this error, the workpiece axis must be kept to be parallel to the grinding wheel axis. And, the direction of the workpiece axis can be controlled by the work-rest blade. Therefore, the effects of work-rest blade inclination angle on the through-feed centerless ground part are investigated in this study. As a result, it is found that there is a positive inclination angle of the work-rest blade for minimizing the tapering error of a ground workpiece.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.507-513
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• 1998

In surface grinding, the conditions of the grinding wheel has much more significant effect on the machined workpiece as compared to other metal removal processes. The contact between the grinding wheel and the workpiece introduce heat and resistance, which restrict the self-dressing of the grits and result in burrs cracks on the workpiece. Therefore, before or during the grinding operation, it is necessary to self-dressing the grinding wheel for more accurate performance. In general, however, the choice of the dressing time has made by the operator's own decision or the condition of the workpiece. In this paper, a new method for finding the optimal dressing time of the grinding wheel is proposed. In order to develop a more sophisticated methodology, a non-contacting in-process optical measurement method using a laser beam has been introduced to find the glazing, loading, and spilling of the grinding wheel Simultaneously, a three-dimensional computer simulation of the grinding operation has been attempted based on the contact mechanism between the grinding wheel and the workpiece. The grains of the grinding wheel are simulated and the optimal dressing time is determined based on the amount of grain wear and work surface roughness.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.173-180
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• 2000

In the process of grinding a long slender type workpiece, such as ballscrew, by the external cylindrical grinding machine, the cylindricity of the workpiece depends on the distance of rests, the stiffness of supports, the diameter and material of workpiece. Conventionally the process needs to be supported by one or more rests to prevent static deflection and vibration. In this paper, the optimal position of the rests was investigated in order to minimize the cylindricity due to the static deflection, by taking compliance of the workpiece and structure into account. In order to obtain the optimal position of rests, a new modeling that is considering the spring effect of all support elements was established. Since it is so complicated to obtain the optimal position analytically for various conditions due to discontinuity, a genetic algorithm u as utilized.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.38-43
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• 2003

The dimensions of die and workpiece are changed continuously during loading, unloading, and ejecting stage. Finally, to predict precisely the dimension of forged part and get the die dimension for the net-shape components, the analysis of die and workpiece should be evaluated from the loading to ejecting. Therefore, the experimental and FEM analysis are peformed to investigate the elastic characteristics at workpiece and die in the closed-die upsetting for ferrous material. FE techniques are proposed to consider the unloading and ejecting stages and estimate more precisely the dimension of forged part and die. The dimensional changes for the workpiece were evaluated quantatively during loading, unloading, and ejecting stages. The strains measured by the strain gages were compared with the estimated values by the FEM.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.899-902
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• 1997

The heat generated during surface grinding process can lead to elevate a grinding temperature, which cause the thermal damage to the workpiece material. Because of this reason, it is important to be able to predict the temperature which is occurred during grinding. The process parameters, therefore, should be adjusted properly to yield the acceptable workpiece temperature. In this study, we conducted an experimentation to obtain and also to analyze the temperature distribution of the workpiece with accordance in varying the grinding condition. For measuring the workpiece temperature, thermocouples of the CA type were inserted into the predetermined locations of the workpiece.

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.222-228
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• 2001

In the milling operation, the burr can be generated on the intersection of cutting tool and workpiece. Due to burr formation, we expect lower efficiency in the operation and the cost increase. In order to understand the burr formation mechanism in the milling operation on the arbitrary feature, we developed an algorithm to analyse and predict the exit burr formation mechanism. Firstly, the recognition of arbitrary shaped workpiece was done through the CAD data. This data includes point information on the vertices of the workpiece. Secondly, tile CAM data regarding tool geometry, tool path, cutting speed, and material data are retrieved to simulate the actual cutting process. Thirdly, we predict the exit burr formation on the edge of workpiece based on the geometric analysis. Lastly, an algorithm implemented in the Windows environment to visualize the burr formation simulation. With this information, we can predict which portion of workpiece would have the exit burr in advance so that we call manage to find a way to minimize the edit burr formation in the actual cutting.