• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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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.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.6
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• pp.159-167
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• 2008

Cooling lubricants are used in machining operations in order to reduce friction at the tool-chip and tool-workpiece interfaces, cool both chip and tool, and remove chip. Furthermore, they influence a strong effect on the shearing mechanisms and, consequently, on the machined surface quality and tool wear. However, several researchers state that the costs related to cutting fluids is frequently higher than those related to cutting tools. Moreover, the cooling lubricants cause an increase in both worker's health and social problems related to their use and correct disposal. Therefore, many researchers have focused on the environmentally conscious machining technologies. One of the technologies is known as MQL(Minimum Quantity Lubrication) machining. In this paper, an experimental model to obtain the optimal cutting conditions in MQL turning was suggested, and the effects of cutting conditions on surface roughness and cutting force were analyzed. For these purposes, FFD (Fractional Factorial Design) and RSM (Response Surface Methods) were used for the experiment. Cutting force and surface roughness with different cutting conditions were measured through the external cylindrical turning of Al 6061 based on the experiment plan. The measured data were analyzed by regression analysis and verification experiments with random conditions were conducted to confirm the suggested experimental model.

• Journal of the Korean Society for Precision Engineering
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• v.5 no.1
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• pp.40-49
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• 1988

The chip control problem is one of the important subjects to be studied in the metal cutting process. Especially, an important practical problem concerns the form of chips pro- duced in machining since this has important implications relative to : 1. Personal safety. 2. Possible damage to equipment and product. 3. Handling and disposal of swarf after machining. 4. Cutting forces, temperatures, and tool life. However, a dependable way to predict the form of chips in a wide range of cutting conditions has not been established satisfactorily. In this paper, the relationship between the form of chips and the ratios of cutting forces were studied experimentally. According to what the experiments have been carried out in the turning process the main results can be summarized as follows : 1. By use of the multiple linear regression model, emperical formulas which are suitable to wide ranges of cutting conditions with accuracy were obtained satisfactorily. 2. The correlations between the form of chips based upon the classification by Henriksen and the ratios of cutting forces, namely (feeding force/thrust force), (principal force/feeding force) were determined. 3. Using above results, the algorithms which predict the form of chips were constituted. With these algorithms, the form of chips in a wide range of cutting of cutting conditions can be predicted.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1768-1771
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• 2003

Hard turning replaces grinding for finishing process with expectations of higher productivity and demanded surface quality. Especially for the surface roughness as surface quality demanded in finishing process of hard turning, know-how of machining characteristics of hardened materials by cutting force analysis should be accumulated in company with achievement of precision of elements and high stiffness design technology in hard turning. Considering chip formation mechanism of hardened materials, adequate cutting conditions are selected for machining experiments and cutting forces are measured according to cutting conditions. Increase of cutting forces especially thrust force and increase of dynamic instability could occur in hard turning. Analysis of dynamic characteristics of the cutting forces is executed to investigate relation between dynamic instability and surface roughness in hard turning. Investigation on effects of relative motion of machining system generated by vibration due to dynamic instability shows that ultimate surface roughness could be predicted considering relative motion of machining system with geometrical surface roughness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.6 s.165
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• pp.979-987
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• 1999

In a high precision vertical machining center, the estimation of cutting forces is important for many reasons such as prediction of chatter vibration, surface roughness and so on, and cutting forces are difficult to predict because they are very complex and time variant. In order to predict the cutting forces of end-milling process for various cutting conditions, a mathematical model is important and this model is based on chip load, cutting geometry, and the relationship between cutting forces and chip loads. Specific cutting force coefficients of the model have been obtained as interpolation function types by averaging farces of cutting tests. In this paper, the coefficients are obtained by neural network and the results of the conventional method and those of the proposed method are compared. The results show that the neural network method gives more correct values than the function type and that in teaming stage as the omitted numbers of experimental data increases the average errors increase.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.62-70
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• 1996

We experimented on cutting characteristics-cutting force, behavior of cutting temperature, surface roughness. chip thickness under low temperature, which generated by liquid nitrogen(77K). The work-pieces were freezed to-195 .deg. C and liquid nitrogen was also sprinkled on cutting area in order to decrease an experimental error of machining in low temperature. The workpiece was became to -195 .deg. C in5 minutes. In cooled condition surface roughness of workpiece was better than normal condition. In addition, we investigated the possibility that surface roughness of workpiece and cutting force can be predicted analyzing cutting conditions by the trained neural network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.79-82
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• 1997

The current from the feed motor of a machine tool contains substantial information about the machining state. There have been many researches that investigated the current as a measure for the cutting forces. However it has not been reported that indirect measurement of the cutting forces from the current of the feed motor at rest is possible. The cutting force normal to the machined surface influences the machined surface of the workpiece, which makes it necessary to estimate this force to control the roughness of the machined surface. But the unpredictable behavior of the current prevents applying the current to prediction of the cutting state. In this paper, empirical approach was conducted to resolve the problem. Also parametric adaptive and fuzzy logic control strategies are applied to the force regulation problem. As a result, the current is shown to be related to the accumulation of the infinitesimal rotation of the motor, and besides the unpredictable behavior of the current is shown to be caused by the relationship. Subsequently the relationship between the current and the cutting force is identified, and it is presented that control of machined surface using the current of the feed motor at rest is possible.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.411-415
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• 2004

In this paper, a double artificial neural network (ANN) approach and the efficient machining database building scheme are presented for the prediction of surface roughness in high-speed machining. In this approach, 4 machining parameters and used for the prediction of cutting force components, and the combinations of 4 parameters and the predicted cutting force components are finally used for the prediction of surface roughness. The experimental results comparing the these results with the predicted values using simple 4 input nodes have been also investigated to verify the effectiveness of the proposed approach.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.6
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• pp.9-15
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• 2011

Any relative deformation between the cutting tool and the workpiece at machining point results directly in geometric and dimensional errors. The sources of relative deformations between the cutting tool and the workpiece at the contact point may be due to vibration, thermal deformation and cutting forces. In this paper, geometric error prediction of workpiece in turning has been investigated. To reach this goal, turning experiments are carried out according to selected cutting conditions. The variable cutting conditions are cutting speed, depth of cut and feed rate. The results will be useful as a guidance to select cutting conditions to improve the geometrical accuracy.