• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1059-1062
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• 1995

In cutting system, relative displacement between rool and workpiece is very important. Even though there have been so many works for modeling cutting process of end-milling, most of them have considered only one displacement of either tool or workpiece instead of both. In this paper, the relative displacement between tool and workpiece is considered for modeling cutting process of end-milling using simple experimental modal analysis and cutting force simulation program is developed. In cutting force model, instantaneous uncut chip thickness model is used and Runge-Kutta method is used for the simulation of time varying cutting system.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.82-91
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• 1996

In this study, we put our object to carry out adaptive modeling of cutting process in turning system, and to find out the optimal cutting conditions to maximize material removal rate under some constraints. We used a back-propagation neural network to model the cutting process adaptively and a genetic algorithm to find out optimal cutting conditions. The experimental results show that a back-propagation neural network could model the cutting process effciently, and optimized cutting conditions for maximizing the material removal rate were obtained through the adaptive process model and genetic algorithms. Therefore, the proposed approach can be applied to the real machining system.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.4
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• pp.353-358
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• 2015

Energy consumption reduction has become an important key word in manufacturing that can be achieved through the efficient and optimal use of raw materials and natural resources, and minimization of the harmful effects on nature or human society. The successful implementation of this concept can only be possible by considering a product's entire life cycle and even its disposal from the early design stage. To accomplish this idea with milling, minimum quantity lubrication (MQL) strategies and cutting conditions are analyzed through process modeling and experiments. In this study, a model to predict the cutting energy in the milling process is used to find the cutting conditions, which minimize the cutting energy through a Kriging meta-modeling process. The MQL scheme is developed first to reduce the amount of cutting oil and costs used in the cutting process, which is then employed for the entire modeling and experiments.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.06a
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• pp.68-75
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• 2000

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. Cutting force components are divided into static and dynamic components in this paper, and the static components of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force disparities are defined in this paper, and the relationships between normalized disparity and flank wear are established. Finally, Artificial neural network is used to learn these relationships and detect tool wear. According to the proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.261-269
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• 2009

Micro end-milling process is applied to fabricate precision mechanical parts cost-effectively. It is a complex and time-consuming job to select optimal process conditions with high productivity and quality. To improve the productivity and quality of precision mechanical parts, micro end-mill wear and cutting force characteristics should be studied carefully. In this paper, high speed machining experiments are studied to construct the optimum process design as well as the mathematical modeling of tool wear and cutting force related to cutting parameters in micro ball end-milling processes. Cutting force and wear characteristics under various cutting conditions are investigated through the condition monitoring system and the design of experiment. In order to construct the cutting database, mathematical models for the flank wear and cutting force gradient are derived from the response surface method. Optimal milling conditions are extracted from the developed experimental models.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.531-535
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• 1996

Computer aided conceptual solution of engineering problems can be effectively implemented by qualitative reasoning based on a physical model. Qualitative reasoning needs modeling paradigm which provides intellignet control of modeling assumptions and robust inferences without quantitative information about the system. We developed reasoning method using new algebra of qualitative mathematics. The method is applied to a conceptual design scheme of anadaptive control system of cutting process. The method identifies differences between proportional and proportional-integral control scheme of cutting process. It is shown that unfeasible investment could be prevented in the early conceptual stage by the qualitative reasoning procedures proposed in this paper.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.192-196
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• 2001

This work describes the modeling of cutting process for feedback control based on signal processing in end-milling. Here, cutting force is used to design control model by a variety of schemes which are moving average, ensemble average, peak value, root mean square and analog low-pass filtering. It is expected that each model offers its own peculiar advantage in following cutting force control.

• Steel and Composite Structures
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• v.19 no.6
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• pp.1467-1481
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• 2015

This paper presents a contribution to improving an analytical thermo-mechanical modeling of Oxley's machining theory of orthogonal metals cutting, which objective is the prediction of the cutting forces, the average stresses, temperatures and the geometric quantities in primary and secondary shear zones. These parameters will then be injected into the developed model of Karas et al. (2013) to predict temperature distributions at the tool-chip-workpiece interface. The amendment to Oxley's modified model is the reduction of the estimation of time-related variables cutting process such as cutting forces, temperatures in primary and secondary shear zones and geometric variables by the introduction the constitutive equation of Johnson-Cook model. The model-modified validation is performed by comparing some experimental results with the predictions for machining of 0.38% carbon steel.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.96-100
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• 1996

So far the analysis and modeling of cutting process is studied commonly assumed as being linear stochastic or chaotic without experimental verification. So we verified force signals of cutting process(ball end-milling) is low-dimensional chaos by calculating Lyapunov Exponents. reconstructing attractor using time delay coordinates and calcula-ting it's fractal dimension.