Prediction and analysis of material removal mode of hollow thin-walled aluminum alloy components in cutting process based on matrix perturbation method

2021 ◽  
Author(s):  
Yongcheng Mu ◽  
Shengfang Zhang ◽  
Fujian Ma ◽  
Ziguang Wang ◽  
Zhihua Sha
Keyword(s):  
Aluminum Alloy ◽  
Perturbation Method ◽  
Material Removal ◽  
Cutting Process ◽  
Matrix Perturbation ◽  
Thin Walled ◽  
Material Removal Mode

scholarly journals Experimental Study on the Influence of Tool Electrode Material on Electrochemical Micromachining of 304 Stainless Steel

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2311
Author(s):  
Jianxiao Bian ◽  
Baoji Ma ◽  
Haihong Ai ◽  
Lijun Qi
Keyword(s):  
Stainless Steel ◽  
Aluminum Alloy ◽  
Material Removal ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
304 Stainless Steel ◽  
Aluminum Alloy 6061 ◽  
Thin Walled ◽  
Alloy 6061 ◽  
Tungsten Steel

Different cathode materials have different surface chemical components and machining capacities, which may finally result in different machining quality and machining efficiency of workpieces. In this paper, in order to investigate the influence of cathode materials on the electrochemical machining of thin-walled workpiece made of 304 stainless steel, five cylindrical electrodes are used as the target working cathodes of electrochemical machining to conduct experiments and research, including 45# steel, 304 stainless steel, aluminum alloy 6061, brass H62, and tungsten steel YK15. The stray current corrosion, taper, and material removal rate were used as the criteria to evaluate the drilling quality of efficiency of a thin-walled workpiece made of 304 stainless steel. The research results show that from the perspectives of stray current corrosion and taper, aluminum alloy 6061 is an optimal tool cathode, which should be used in the electrochemical machining of thin-walled workpieces made of 304 stainless steel; on the aspect of material removal rate, the 45# steel, 304 stainless steel, and aluminum alloy 6061 present close material removal rates, all of which are higher than that of brass H62 and tungsten steel YK15. Based on comprehensive consideration of both machining quality and machining efficiency, the aluminum alloy 6061 is the best option as the cathode tool in the electrochemical machining of thin-walled workpieces made of 304 stainless steel.

scholarly journals Simulation of the ductile machining mode of silicon

2021 ◽  
Author(s):  
Hagen Klippel ◽  
Stefan Süssmaier ◽  
Matthias Röthlin ◽  
Mohamadreza Afrasiabi ◽  
Uygar Pala ◽  
...  
Keyword(s):  
Brittle Material ◽  
Material Removal ◽  
Machining Process ◽  
Ductile Material ◽  
Diamond Wire ◽  
Ductile Machining ◽  
Mesh Free ◽  
Diamond Wire Sawing ◽  
Material Removal Mode ◽  
Brittle Material Removal

AbstractDiamond wire sawing has been developed to reduce the cutting loss when cutting silicon wafers from ingots. The surface of silicon solar cells must be flawless in order to achieve the highest possible efficiency. However, the surface is damaged during sawing. The extent of the damage depends primarily on the material removal mode. Under certain conditions, the generally brittle material can be machined in ductile mode, whereby considerably fewer cracks occur in the surface than with brittle material removal. In the presented paper, a numerical model is developed in order to support the optimisation of the machining process regarding the transition between ductile and brittle material removal. The simulations are performed with an GPU-accelerated in-house developed code using mesh-free methods which easily handle large deformations while classic methods like FEM would require intensive remeshing. The Johnson-Cook flow stress model is implemented and used to evaluate the applicability of a model for ductile material behaviour in the transition zone between ductile and brittle removal mode. The simulation results are compared with results obtained from single grain scratch experiments using a real, non-idealised grain geometry as present in the diamond wire sawing process.

scholarly journals A surrogate-assisted optimization approach for multi-response end milling of aluminum alloy AA3105

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2419-2439
Author(s):  
Tamal Ghosh ◽  
Yi Wang ◽  
Kristian Martinsen ◽  
Kesheng Wang
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Data Driven ◽  
Optimal Cutting Parameters

Abstract Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

Experimental Investigation on Brittle-Ductile Transition in Electroplated Diamond Wire Saw Machining Single Crystal Silicon

2010 ◽  
Vol 431-432 ◽  
pp. 265-268 ◽  
Author(s):  
Yu Fei Gao ◽  
Pei Qi Ge
Keyword(s):  
Single Crystal ◽  
Material Removal ◽  
Single Crystal Silicon ◽  
Crystal Silicon ◽  
Diamond Wire ◽  
Brittle Ductile Transition ◽  
Wire Saw ◽  
Diamond Wire Saw ◽  
R Value ◽  
Material Removal Mode

Based on reciprocating electroplated diamond wire saw (REDWS) slicing experiments, a study on REDWS machining brittle-ductile transition of single crystal silicon was introduced. The machined surfaces and chips were observed by using Scanning Electron Microscope (SEM), and some experimental evidences of the change of material removal mode had been obtained. The experimental results indicate there is a close relationship between material removal mode and the ratio r value of ingot feed speed and wire speed, through controlling and adjusting the r value, the material removal mode can be complete brittle, partial ductile and near-ductile removal.

Numerical Simulation of Casting Deformation and Stress of A356 Aluminum Alloy Thin-Walled Frame Casting

2021 ◽  
Vol 1033 ◽  
pp. 24-30
Author(s):  
Yi Dan Zeng ◽  
Li Tong He ◽  
Jin Zhang
Keyword(s):  
Aluminum Alloy ◽  
Casting Process ◽  
Mold Temperature ◽  
Hot Cracking ◽  
Thin Wall ◽  
A356 Aluminum Alloy ◽  
Pouring Temperature ◽  
Thin Walled ◽  
Alloy Castings ◽  
A356 Aluminum

One of the main reasons for the scrap of cast thin-wall frame aluminum alloy castings is deformation and cracking. It is an effective method for solving the problem by predicting the distribution of casting stress, clarifying the size of the deformation and the location of the crack, and taking necessary measures in the process. This paper uses the ProCAST software to simulate the thermal stress coupling of A356 thin-walled frame castings, analyzes the influence of pouring temperature, pouring speed and mold temperature on the stress field distribution of castings, predicts the hot cracking trend and deformation, and optimizes Casting process..

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