Experiment and Analysis on Side Milling Deformation of Thin-Walled Workpieces Using Laddered Symmetrical Tool Path

2013 ◽  
Vol 710 ◽  
pp. 233-237
Author(s):  
Yong Qiang He
Keyword(s):  
Parameter Optimization ◽  
Tool Path ◽  
Cutting Parameters ◽  
Deformation Characteristics ◽  
Side Milling ◽  
Machining Center ◽  
Thin Walled ◽  
Aluminum 7075 ◽  
Machining Parameter ◽  
Deformation Error

The aluminum 7075 workpieces are machined on a vertical machining center KX650 using laddered symmetrical tool path. The deformation characteristics are studied under different cutting conditions. Different cutting parameters are changed one by one in side milling tests to find out their impact on deformation error. The analyzed result provides a solid basis for machining parameter optimization in side milling thin-walled workpieces.

scholarly journals Multi-Criteria Selection of the Optimal Parameters for High-Speed Machining of Aluminum Alloy Al7075 Thin-Walled Parts

Metals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1570
Author(s):  
Dejan Lukic ◽  
Robert Cep ◽  
Jovan Vukman ◽  
Aco Antic ◽  
Mica Djurdjev ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
High Speed ◽  
Tool Path ◽  
Dimensional Accuracy ◽  
Cutting Parameters ◽  
Optimal Level ◽  
Machining Parameters ◽  
Thin Walled ◽  
Machining Parameter ◽  
Selection Of

Thin-walled parts made of aluminum alloy are mostly used as structural elements in the aerospace, automobile, and military industries due to good homogeneity, corrosion resistance, and the excellent ratio between mechanical properties and mass. Manufacturing of these parts is mainly performed by removing a large volume of material, so it is necessary to choose quality machining parameters that will achieve high productivity and satisfactory quality and accuracy of machining. Using the Taguchi methodology, an experimental plan is created and realized. Based on its results and comparative analysis of multi-criteria decision making (MCDM) methods, optimal levels of machining parameters in high-speed milling of thin-walled parts made of aluminum alloy Al7075 are selected. The varying input parameters are wall thickness, cutting parameters, and tool path strategies. The output parameters are productivity, surface quality, dimensional accuracy, the accuracy of forms and surface position, representing the optimization criteria. Selection of the optimal machining parameter levels and their ranking is realized using 14 MCDM methods. Afterward, the obtained results are compared using correlation analysis. At the output, integrative decisions were made on selecting the optimal level and rank of alternative levels of machining parameters.

A Bi-Directional Ultrasonic Elliptical Vibration Actuator (BUEVA) for Micro Machining

2009 ◽  
Author(s):  
Ali H. Ammouri ◽  
Ramsey F. Hamade
Keyword(s):  
Tool Path ◽  
Cutting Parameters ◽  
Micro Machining ◽  
Tool Positioning ◽  
Elliptical Vibration ◽  
Machining Center ◽  
Precise Tool ◽  
Multilayer Actuator ◽  
Tool Motion ◽  
Ultrasonic Elliptical Vibration

Presented is the detailed design and implementation of a bi-directional ultrasonic elliptical vibration actuator (BUEVA) for micro machining. Removal of material occurs via a generated elliptical tool motion resembling a natural ‘spoon feeding’ action in contrast to in-plane, horizontal motion utilized by most existing setups. The motion is generated by two stacked ceramic multilayer actuator ring (SCMAR) piezo elements vibrating out of phase in the tool’s axial and transverse directions. The amplitude of vibration of the tool is controlled in order to vary the cutting depth according to the desired cutting parameters. To ensure precise tool positioning, the BUEVA actuator is fitted to a 3-axis precision machining center that provides the necessary tool path. The cutting forces and the resulting surface finish are both numerically modeled and then experimentally measured by a 3-axis mini dynamometer and a surface profilometer, respectively. Preliminary cutting results show good dimensional definition and surface integrity.

Chatter Prediction Based on NC Physical Simulation in Machining Ti6Al4V Thin-Walled Components

2013 ◽  
Vol 395-396 ◽  
pp. 1008-1014
Author(s):  
Yu Li ◽  
Chao Sun
Keyword(s):  
Tool Path ◽  
Physical Simulation ◽  
Prediction Method ◽  
Cutting Parameters ◽  
Simulation Software ◽  
Cnc Machining ◽  
Machining Process ◽  
Chatter Stability ◽  
Chatter Prediction ◽  
Thin Walled

Chatter has been a problem in CNC machining process especially during machining thin-walled components with low stiffness. For accurately predicting chatter stability in machining Ti6Al4V thin-walled components, this paper establishes a chatter prediction method considering of cutting parameters and tool path. The fast chatter prediction method for thin-walled components is based on physical simulation software. Cutting parameters and tool path is achieved through the chatter stability lobes test and finite element simulation. Machining process is simulated by the physical simulation software using generated NC code. This proposed method transforms the NC physical simulation toward the practical methodology for the stability prediction over the multi-pocket structure milling.

scholarly journals A Data-driven Minimum Stiffness Prediction Method for Machining Regions of Aircraft Structural Parts

2021 ◽  
Author(s):  
Jiarui Chen ◽  
Yingguang Li ◽  
Xu Liu ◽  
Tianchi Deng
Keyword(s):  
Prediction Method ◽  
Cutting Parameters ◽  
Data Driven ◽  
Calculation Methods ◽  
Structural Part ◽  
Average Percentage ◽  
Thin Walled ◽  
Structural Parts ◽  
Local Stiffness ◽  
Machining Parameter

Abstract Large thin-walled structural parts have been widely used in aircrafts for the purpose of weight reduction. These parts usually contain various thin-walled complex structures with weak local stiffness, which are easy to deform during machining if improper cutting parameters are selected. Thus, local stiffness has to be seriously considered during the machining parameter planning. Existing stiffness calculation methods mainly include mechanics calculation methods, empirical formula methods, finite element methods, and surrogate-based methods. However, due to the structural complexity, these methods are either inaccurate or time consuming. To address this issue, this paper proposes a data-driven method for stiffness prediction of aircraft structural parts. First, machining regions of aircraft structural part finishing are classified into bottom, sidewall, rib and corner to further define the minimum stiffness of machining regions. Then, by representing the part geometry with attribute graph as the input feature, while computing the minimum stiffness using FEM as the output label, stiffness prediction is turned to a graph learning task. Thus, a graph neural network (GNN) is designed and trained to map the attribute graph of a machining region to its minimum stiffness. In the case study, a dataset of aircraft structural parts is used to train four GNN models to predict the minimum stiffness of the defined four types of machining regions. Compared with FEM results, the average percentage errors on the test set are 6.717%, 7.367%, 7.432% and 5.962% respectively. In addition, the data driven model once trained, can greatly reduce the time in predicting the stiffness of a new part compared with FEM, which indicates that the proposed method can meet the engineering requirements in both accuracy and computational efficiency.

Research on 5 Axis Tool-Path Based on Constant Shearing Stress for Milling Thin-Wall Ceramics

2015 ◽  
Vol 778 ◽  
pp. 152-158
Author(s):  
Quan Ping Sun ◽  
Hai Bing Wu ◽  
Qian Liang Chen
Keyword(s):  
High Speed ◽  
Tool Path ◽  
Cutting Parameters ◽  
Good Method ◽  
Air Cooling ◽  
Thin Wall ◽  
Shearing Stress ◽  
Crack Control ◽  
Tool Paths ◽  
Machining Center

Ceramics is a material of hardness and brittle, so crack arises easily when it is machined. To improve its cutting performance and enhance machining quality, a dynamic model based on constant-shearing-stress is built for milling ceramics, therefore some cutting parameters can be optimized by the model for no crack machining; moreover, an algorithm of 5 axis tool-path designed with constant-shearing-stress is put forward. According to the model and the algorithm, 5 axis tool paths of decreasing-cutting-depth and decreasing-feed-rate are realized; these are really accurate and smooth through VERICUT software simulating. Using Mikron high-speed machining center, several experiments were done to find a good method of crack control in milling thin-wall ceramics. The results show that the experiment based on the 5 axis tool paths with high pressure air cooling and regional cutting is rather successful because of no cracking in cutting thin-wall ceramics, compared to others.

Rapid Parameter Optimization of High Speed Milling Aluminum Alloy Thin-Walled Workpiece

2010 ◽  
Vol 431-432 ◽  
pp. 41-44
Author(s):  
Feng Xu ◽  
Jian Jun Zhu ◽  
Xiao Jun Zang ◽  
Xin Wu
Keyword(s):  
Parameter Optimization ◽  
High Speed ◽  
Removal Rate ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Cutting Conditions ◽  
Optimal Parameters ◽  
High Speed Milling ◽  
Thin Walled ◽  
Optimal Cutting Parameters

At present, the lack of the optimal cutting parameters of high speed milling is the obstacle to its widely application. In this paper, the simplified and rapid optimization method is proposed on high speed milling alloy thin-walled workpiece. The normal selection method of cutting tools and cutting conditions is put forward as the precondition of parameter optimization. The acquirement method of optimal parameters is presented. The maximal critical axial depths of cut at the different cutting conditions are achieved according to chatter stability theory. The materials removal rate is selected as the optimal objective. The optimal parameters are filtrated up and validated according to the constraint conditions including machining tool, cutting tools, surface quality and precision of the parts.

Machining Parameter Optimization of Bidirectional CFRP Composite Pipe by Genetic Algorithm

2014 ◽  
Vol 56 (9) ◽  
pp. 728-736 ◽  
Author(s):  
Krishnasamy Vijaykumar ◽  
Kavan Panneerselvam ◽  
Abdullah Naveen Sait
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Composite Pipe ◽  
Cfrp Composite ◽  
Machining Parameter

scholarly journals Energy efficient cutting parameter optimization

2021 ◽  
Author(s):  
Xingzheng Chen ◽  
Congbo Li ◽  
Ying Tang ◽  
Li Li ◽  
Hongcheng Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Parameter Optimization ◽  
Energy Efficient ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Current Status ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization

AbstractMechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

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