Papers by Keyword: Machining

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Authors: Ji Hong Yang, Shou Jin Sun, Milan Brandt, Wen Yi Yan
Abstract: A 3D finite element model of the machining of Ti6Al4V alloy has been developed. This model is able to simulate the formation of continuous or discontinuous chips during the cutting process that depends on the cutting conditions. In this model, the yield stress is considered as a function of the strain, the strain rate and the temperature. The dynamic effects, thermo-mechanical coupling, constitutive damage law and contact friction are taken into account. The stresses and temperature fields, chip formation and tool forces are obtained at different stages of the cutting process.
Authors: Zhan Qiang Liu, Xing Ai, Zhao Hui Wang
Abstract: This paper presents a comparison study of surface hardening by grinding versus machining. The technological, economical and ecological merits of machining hardening and grind-hardening process for steels are described. The mechanisms of machining hardening and grind-hardening of steels are investigated and compared. The phase transformation, plastic deformation and white layer generation are the principal factors contributing to the hardened surface layer by machining and grinding. The influences of the process parameters on the penetrated hardness are given for both grind-hardening and machining hardening operations. The future development trends of the grind-hardening and machining hardening are also presented.
Authors: Edilson Rosa Barbarosa Jesus, J.L. Rossi
Authors: Rui Jian, Jun Zhao
Abstract: This paper is concerned with the problem of license plate recognition of vehicles. A recognition algorithm based on dynamic sliding window to binarize license plate characters is proposed. While a connected domain approach is presented to cope with the degradation characters. There are three steps to recognize the characters. First, the characters are classified by their features. Then, based on such classification a grid method is used to construct the feature vector. Finally, least square support vector machine is employed to recognize these characters. The test results show the high recognition rate and also illustrate the effectiveness of the proposed algorithm.
Authors: Dong Jin Zhang, Chen Wang, Gang Liu, Ming Chen
Abstract: As a typical difficult-to-cut material, the nickel-based superalloy GH4169 has been used in many kinds of aeronautical key structures and turbine components because of its high yield stress and anti-fatigue performance even in high temperature. In this paper, finite element method (FEM) is introduced to study the saw-tooth chip formation in detail. By the way of Lagrange approach, adiabatic shear band (ASB) is simulated and the chip forming mechanism is interpreted by adiabatic shearing theory via the comparison of two models, one of which has a failure criterion and another not. The comprehensive comparison and analysis of chip morphology between simulation and experiment are also presented in this paper.
Authors: Jun Wang
Abstract: Increasing the performance of the abrasive waterjet (AWJ) cutting technology for engineering materials is the ultimate aim of research in this field. This paper presents a review on the studies using a controlled nozzle oscillation technique to increase the cutting performance of the AWJ cutting technology and the associated mechanisms primarily based on the work in the author’s laboratory. Primary attention is paid to the discussions of the depth of cut, the effect and selection of process parameters and the advantages by using this technique in both single- and multi-pass cutting modes.
Authors: Manik Rajora, Alexander H. Shih, Pan Zou, Bei Zhi Li, Steven Y. Liang
Abstract: Surface roughness is an important outcome in the machining process and it plays a major role in the manufacturing system. Prediction of surface roughness has been a challenge to researchers because it is impacted by different machining parameters and the inherent uncertainties in the machining process. Prediction of surface roughness will benefit the manufacturing process to be more productive and competitive at the same time to reduce any pre-processing of the machined workpiece in order to meet the technical specifications. In this study, a hybrid GA-LM ANN is proposed for the prediction of surface roughness during roughing process in turning operation. To verify the performance of the proposed approach, the results are compared with the results obtained by training an ANN using GA or LM. The results have shown that the hybrid ANN outperformed the other two algorithms.
Authors: Zoltán Pálmai
Abstract: The common feature of the different forming technologies is that the deformation is concentrated into a relatively narrow shear zone. The behaviour of the material can be defined only by specific material properties, the definition of which is difficult and costly. We have developed a new method for the comparatively simple and cheap definition of these specific material properties based on the well known theory and the sophisticated measuring technology of cutting. To achieve this we have developed our previous dynamic technological model, which is described by evolution and delay differential equations. As an example, in the case of a steel with 13% Cr content T, C555520−≈8.26.2−≈=φεγ, the thermal softening 4410−−≈=sφεγ&&≈κ0.98±0.016 MPa/K, the strain rate sensitivity constant k≈0.034±0.009 and the strain hardening exponent n0.170.005.
Authors: De Huai Zeng, Yuan Liu, Lian Bo Jiang, Li Li, Gang Xu
Abstract: In this paper, support vector regression with ant colony optimization is presented for the prediction of tool-chip interface temperature depends on cutting parameters in machining. Ant colony (ACO) optimization was developed to optimize three parameters of SVR, including penalty parameter C, insensitive loss function ε and kernel function σ. SVR constructs hyperplane in high dimension space and fits the data in non-linear form. Normalized mean square error (NMSE) of fitting result is used as target of ant colony optimization. ACO finds the best parameters which correspond to the NMSE. The results showed that the proposed approach, by comparing with back-propagation neural network model, was an efficient way to model tool–chip interface temperature with good predictive accuracy.
Authors: Y.P. Han, J.F. Meng, J.Q. Zhou
Abstract: A new type of non-chisel-edge shallow-drill is developed for machining high manganese steel, which is a typical hard-to-machine material. The marked characteristic of the drill is that the cutting edge is non-chisel-edge, consisting of a section of straight line and a part of curve nearby the center. The characteristics of machining performance of this drill are analyzed. Measures adopted in design for improving cutting performance and prolonging tool life are also presented. Applied example indicates that this new drill has good cutting performances and long life. Compared with common twist drill, the axial thrust cutting force of this tool is reduced 30~50 percent.
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