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A cutting Force Prediction Model, Experimental Studies, and optimization of cutting parameters for Rotary Ultrasonic Face Milling of C/SiC Composites

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APPLIED COMPOSITE MATERIALS 2020年第4期27卷 407-431页

作者： Islam, Shafiul Yuan, Songmei Li, Zhen Beihang Univ Beijing Engn Technol Res Ctr High Efficient & Gre Sch Mech Engn & Automat Beijing 100191 Peoples R China

Ceramic matrix composites of type C/SiC have great potential because of their excellent properties such as high specific strength, high specific rigidity, high-temperature endurance, and superior wear resistance. However, the machining of C/SiC is still challenging to achieve desired efficiency and quality due to their heterogeneous, anisotropic, and varying thermal properties. Rotary ultrasonic machining (RUM) is considered as a highly feasible technology for advanced materials. cutting force prediction in RUM can help to optimize input variables and reduce processing defects in composite materials. In this research, a mathematical axial cutting force model has been developed based on the indentation fracture theory of material removal mechanism considering penetration trajectory and energy conservation theorem for rotary ultrasonic face milling (RUFM) of C/SiC composites and validated through designed sets of experiments. Experimental results were found to be in good agreement with theoretically simulated results having less than 15% error. Therefore, this theoretical model can be effectively applied to predict the axial cutting forces during RUFM of C/SiC. The surface roughness of the workpiece materials was investigated after machining. The relationships of axial cutting force and surface roughness with cutting parameters, including spindle speed, feed rate, and cutting depth, were also investigated. In order to identify the influence of cutting parameters on the RUFM process, correlation analysis was applied. In addition, response surface methodology was employed to optimize the cutting parameters.

关键词： C SiC composites Rotary ultrasonic face milling A predictive cutting force model Surface roughness optimization of cutting parameters

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Study on the optimization of cutting parameters in turning thin-walled circular cylindrical shell based upon cutting stability

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第1-4期69卷 891-899页

作者： Chen, Dong Lin, Bin Han, Zhilin Zhang, Yanbin Tianjin Univ Tianjin Key Lab Equipment Design & Mfg Technol Tianjin 300072 Peoples R China

Thin-walled circular cylindrical shell, one of the most typical difficult-to-cut workpieces, is prone to vibration and regenerative vibration especially during the cutting process. Being different from previous studies, this paper established a model of cutting dynamics that accounts for both workpiece deformation and tool vibration. The mathematical model of optimization on cutting parameters was built, with constraint conditions and objective function including cutting force, cutting power, surface roughness, cutting stability, and cutting efficiency. The optimal cutting parameters were subsequently acquired by adding the critical cutting width to the mathematical model. Finally, the orthogonal table of the three factors and five levels was adopted in accordance with the orthogonal experimental design, and the material removal rate improves about 8 % by implementing the program of particle swarm optimization. The dynamic tests of cutting process were conducted, verifying the stability of the optimal results that ensures the best surface quality.

关键词： Thin-walled circular cylindrical shell cutting stability Particle swarm algorithm optimization of cutting parameters

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An approach for improving the machining efficiency and quality of aerospace curved thin-walled parts during five-axis NC machining

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2018年第5-8期97卷 2477-2488页

作者： Jiang, Xiaohui Lu, Weiwei Zhang, Zhenya Univ Shanghai Sci & Technol Coll Mech Engn Shanghai 200093 Peoples R China

The processing of aerospace thin-walled parts with complex curved surfaces can hardly realize both high precision and high efficiency. It is challenging to choose the optimal processing scheme under the limited technological condition. This study proposes a tool path optimization for five-axis numerical control based on Mastercam numerical control programming software. Numerical control program is introduced to VERICUT software to implement simulation optimization through different cutting parameters. Different tool paths of surface processing are optimized to select the optimal cutting trajectory with the highest processing efficiency and the optimal surface quality. On this basis, with processing productivity as the object function, the processing parameters are optimized through control variable method to determine the optimal cutting force and cutting thickness on the premise of guaranteeing the processing quality (cutting force), so that both processing efficiency and processing quality can be perfected. Through experiments, the machining efficiency is increased by 61.5% after two optimization operations, and the machining quality is improved effectively (the average cutting force of finishing is reduced by 76.6% to the largest extent). This not only meets the requirements of processing precision and maximizes the efficiency of processing but also provides a reference for the further application of key parts in aerospace and some other fields.

关键词： Aerospace thin-walled parts Tool path optimization optimization of cutting parameters Processing efficiency Surface quality

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optimization of cutting conditions using artificial neural networks and the Edgeworth-Pareto method for CNC face-milling operations on high-strength grade-H steel

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2019年第5-6期105卷 2151-2165页

作者： Abbas, Adel Taha Pimenov, Danil Yurievich Erdakov, Ivan Nikolaevich Mikolajczyk, Tadeusz Soliman, Mahmoud Sayed El Rayes, Magdy Mostafa King Saud Univ Coll Engn Dept Mech Engn Riyadh 11421 Saudi Arabia South Ural State Univ Dept Automated Mech Engn Lenin Prosp 76 Chelyabinsk 454080 Russia South Ural State Univ Foundry Dept Lenin Prosp 76 Chelyabinsk 454080 Russia UTP Univ Sci & Technol Dept Prod Engn Al Prof S Kaliskiego 7 PL-85796 Bydgoszcz Poland

Computer Numerical Control (CNC) face milling is commonly used to manufacture products from high-strength grade-H steel in both the automotive and the construction industry. The various milling operations for these components have key performance indicators: accuracy, surface roughness (Ra), and machining time for removal of a unit volume min/cm(3) (T-m). The specified surface roughness values for machining each component is achieved based on the prototype specifications. However, poor adherence to specifications can result in the rejection of the machined parts, implying extra production costs and raw material wastage. An algorithm using an artificial neural network (ANN) with the Edgeworth-Pareto method is presented in this paper to optimize the cutting parameter in CNC face-milling operations. The set of parameters are adjusted to improve surface roughness and minimal unit-volume material removal rates, thereby reducing production costs and improving accuracy. An ANN algorithm is designed in Matlab, based on a 3-10-1 Multi-Layer Perceptron (MLP), which predicts the Ra of the workpiece surface to an accuracy of +/- 5.78% within the range of the experimental angular spindle speed, feed rate, and cutting depth. An unprecedented Pareto frontier for Ra and T-m was obtained for the finished grade-H steel workpiece using an ANN algorithm that was then used to determine optimized cutting conditions. Depending on the production objective, one or the other of two sets of optimum machining conditions can be used: the first one sets a minimum cutting power, while the other sets a maximum T-m with a slight increase (under 5%) in milling costs.

关键词： Artificial neural network (ANN) CNC optimization of cutting parameters Face milling Surface roughness High-strength grade-H steel Data mining

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A SVM-based design method for cutting edge profile stability of large-pitch thread turning tool considering vibration

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第9-10期125卷 4529-4547页

作者： Fu, Xiangfu Li, Kangnan Li, Zhe Wang, Xiurui Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Minist Educ Harbin 150080 Peoples R China

The violent vibrations generated during turning large-pitch screws seriously affect the tool wear, which reduces the cutting edge profile stability and affects the surface quality of the threads. We propose a new SVM-based design method for cutting edge profile stability of large-pitch thread turning tool considering the influence of vibration, and the model has also been validated experimentally. The simulation model of cutting process considering the influence of cutting vibration was established by simulating tool trajectory, and the influence of edge parameters and tool structure parameters on cutting edge profile stability was analyzed. Then, the data obtained from finite element simulation are used for training to establish the prediction model of cutting edge profile stability based on SVM. The average errors of cutting force, cutting temperature, and tool wear are 3.14%, 2.33%, and 3.91%, respectively, which proves the effectiveness of the prediction model. Furthermore, the optimization objective functions of blunt and chamfered edges were established, and the cutting parameters and tool structure parameters were optimized based on Artificial Bee Colony Algorithm. Results indicate that cutting edge profile-stabilized tool can be obtained by this method. The study builds a theoretical basis for suppressing vibration during the cutting process and provides technical assistance for tool design of different cutting edges.

关键词： Turning Vibration Large-pitch thread cutting edge profile stability optimization of cutting parameters

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Research on dynamic characteristics of turning process system based on finite element generalized dynamics space

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2024年第9-10期131卷 4683-4698页

作者： Fu, Xiangfu Li, Kangnan Zheng, Minli Wang, Chenglong Chen, Enyi Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Minist Educ Harbin 150080 Peoples R China

The dynamic behavior of the large-pitch screw during turning affects the stability of the cutting process, which in turn impacts the machining quality of the large-pitch screw. The large-pitch screw turning system among the machine tool, cutting tool, and the workpiece is taken as the present research object, and the frequency response function modeling of the large-pitch screw turning process system is carried out. The concept of generalized modal field and generalized stiffness field of large-pitch screw turning process system is introduced. Considering the dynamic change of the whole process system with the change of tool position, the dynamic characteristic information of the processing system is obtained and analyzed and ultimately reflects the inherent properties of the large-pitch screw turning process system and the ability to resist deformation. The cutting stability prediction model based on support vector machines (SVM) is established, and the average prediction error is 5.04%. The artificial bee colony algorithm is used to optimize the cutting parameters, and finally, the optimization method of large-pitch thread cutting stability based on SVM is proposed. This method can reduce the cutting vibration and effectively improve the cutting stability.

关键词： Dynamic modeling Turning Frequency response function optimization of cutting parameters

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