• 한국기계가공학회지
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• 제18권10호
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• pp.75-82
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• 2019

Few studies have been conducted regarding theoretical turning force modelling while considering cutting constant. In this paper, a new cutting force modelling technique was suggested which considers the specific cutting force coefficients for turning. The specific cutting force is the multiplication of the cutting force coefficient and uncut chip thickness. This parameter was used for experimental modelling and prediction of theoretical cutting force. These coefficients, which can be obtained by fitting measured average forces in several conditions, were used for the formulation of three theoretical cutting forces for turning. The cutting force mechanism was verified in this research and its results were compared with each of the experimental and theoretical forces. The deviation of force was incurred by a small amount in this model and the predicted force considering feed rate, nose radius, and radial depth shows a physical behavior in main force, normal force, and feeding force, respectively. Therefore, this modelling technique can be used to effectively predict three turning forces with different tool geometries considering cutting force coefficients.

• 한국생산제조학회지
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• 제22권3호
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• pp.437-446
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• 2013

There have been numerous studies on end milling processes. However, these have been restricted to the application of tools for special cutting purposes. A side milling cutter can handle long, deep, and open slots in a more efficient manner, and it provides the best stability and productivity for this type of milling. In this paper, a method to predict the cutting forces in side milling is described, and simulated cutting forces are compared with those obtained by cutting experiments. In particular, the side milling process easily generates relative motion between the tools and the workpiece because it produces intermittent cutting forces that cause vibrations over a wide frequency range. Therefore, the application of a dynamic cutting model instead of a static cutting model is appropriate to forecast the cutting forces more accurately.

• Design & Manufacturing
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• 제17권4호
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.721-724
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• 2000

This paper presents a prediction of tool deflection and resulting machining error fur sculptured surface productions in the ball-end milling process. Due to the different materials and the dimensions of the tool holder and cutter, a cantilever hem model with three uniform sections is proposed fur the tool deflection model. The ability of this model has been verified by a machining experiment. In this study, cutting force and machining error are investigated. This paper provides the prediction of machining error for sculptured surface to improve machining quality for industrial application.

• 한국공작기계학회논문집
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• 제17권5호
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• pp.116-122
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• 2008

In order to establish automation or optimization of the machining process, predictions of the forces in machining are often needed. A new model fur farces in milling with the experimental model based on the specific cutting pressure and the Oxley's predictive machining theory has been developed and is presented in this paper. The specific cutting pressure is calculated according to the definition of the 3 dimensional cutting forces suggested by Oxley and some preliminary milling experiments. Using the model, the average cutting forces and force variation against cutter rotation in milling can be predicted. Milling experimental tests are conducted to verify the model and the predictive results agree well with the experimental results.

• 한국기계가공학회지
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• 제2권2호
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• pp.22-30
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• 2003

Cutting force signals are very useful to evaluate the cutting state, but many disturbing factors are occurring during cutting. For the reliability of the analysis, selecting pure cutting force signals from the original ones is needed. In the current study, using the ICA(Independent Component Analysis) effective cutting force components are seperated from the original signals. And using this, as input data of MLP(Multi-Layer Perception) cutting forces are predicted Experimental results are then compared with the predicted ones to verify the validation of the proposed model.

• 한국공작기계학회논문집
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• 제12권5호
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• pp.1-7
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• 2003

In order to predict vibrations occurred during end-milling processes, the cutting dynamics was modelled by using neural network and combined with structural dynamics by considering dynamic cutting state. Specific cutting force constants of the cutting dynamics model were obtained by averaging cutting forces. Tool diameter, cutting speed, fled, axial and radial depth of cut were considered as machining factors in neural network model of cutting dynamics. Cutting farces by test and by neural network simulation were compared and the vibration displacement during end-milling was simulated.

• 한국CDE학회논문집
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• 제3권3호
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• pp.161-167
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• 1998

Cutting forces in ball-end milling of slanted surfaces are calculated. The cutting area is determined from the Z-map of the surface geometry and current cutter location. The obtained cutting area is projected onto the cutter plane normal to the Z-axis and compared with cutting edge element location. Cutting force is calculated by integration of elemental cutting forces of engaged cutting edge elements. Experiments with various slanted angles were performed to verify the proposed cutting force estimation model. It is shown that the proposed method predicts cutting force effectively for any geometry including sculptured surfaces with cusp marks and surfaces with pockets and holes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.61-66
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• 1994

Tool condition monitoring is one of the most important aspects to improve productivity and quality and to achieve intelligent machining system. The tool state is classified into three groups as chipping, wear and fracture. In this study, wear of a ceramic cutting tool for hardened die material (SKD11) was investigated. Flank wear was occured more dominant than crarer wear. Therefore, to predict flank wear, the modeling of cutting force has been performed. The modeling of cutting force by an assumption that act the stress distribution on the tool face obtained through a numerical analysis. The relationships between the cutting force and the tool wear can be constructed by machining paraneters with cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions of the flank wear is approximately in good agreement with experimental result.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.104-115
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• 1999

Cutting process, in general, is a closed-loop system consisting of structural dynamics and cutting dynamics, with the cutting forces and the relative displacements between tool and workpiece being the associated variables. There have been a number of works on modeling the cutting process of endmilling, most of which assumed that either one of the tool or workpiece be negligible in tis displacement. In this paper, the relative displacement between tool and workpiece was considered. The proposed model used experimental modal analysis for structural dynamics and an instantaneous uncut chip thickness model for cutting dynamics. Simulation of the model, a time varying cutting system, was performed using 4th order Runge-Kutta method. Subsequent simulation results were utilized to predict chatter over a variety of experiments in slotting operation, showing good agreement.