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.

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.

A Coupled Model for the Prediction of Surface Variation in Face Milling Large-Scale Workpiece With Complex Geometry

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Shun Liu ◽  
Sun Jin ◽  
Xue-Ping Zhang ◽  
Kun Chen ◽  
Ang Tian ◽  
...  
Keyword(s):  
Large Scale ◽  
Coupled Model ◽  
Prediction Method ◽  
Face Milling ◽  
Milling Force ◽  
Important Indicator ◽  
Surface Variation ◽  
Local Stiffness ◽  
Machining Parameter ◽  
Complex Components

Face milling commonly generates surface quality of variation, is especially severe for milling of large-scale components with complex surface geometry such as cylinder block, engine head, and valve body. Thus surface variation serves as an important indicator both for machining parameter selection and components' service performance such as sealing, energy consumption, and emission. An efficient and comprehensive numerical model is highly desired for the prediction of surface variation of entire surface. This study proposes a coupled numerical simulation method, updating finite element (FE) model iteratively based on integration of data from abaqus and matlab, to predict surface variation induced by face milling of large-scale components with complex surfaces. Using the coupled model, three-dimensional (3D) variation of large-scale surface can be successfully simulated by considering face milling process including dynamic milling force, spiral curve of milling trajectory, and intermittently rotating contact characteristics. Surface variation is finally represented with point cloud from iterative FE analysis and verified by face milling experiment. Comparison between measured and predicted results shows that the new prediction method can simulate surface variation of complex components well. Based on the verified model, a set of analyses are conducted to evaluate the effects of local stiffness nonhomogenization and milling force variation on machined surface variation. It demonstrates that surface variation with surface peaks and concaves is strongly correlated with local stiffness nonhomogenization especially in feed direction. And thus the coupled prediction method provides a theoretical and efficient way to study surface variation induced by face milling of large-scale complex components.

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.

Engineered-Based Machining Parameters Analysis for Aircraft Structural Parts

2014 ◽  
Vol 721 ◽  
pp. 109-112
Author(s):  
Fang Zhu ◽  
Xiong Fei Huang ◽  
Li Jun Meng
Keyword(s):  
Computer Experiment ◽  
Machining Process ◽  
Aviation Industry ◽  
Machining Parameters ◽  
Structural Part ◽  
Parameter Evaluation ◽  
Aircraft Structural Part ◽  
Parameters Analysis ◽  
Structural Parts ◽  
Machining Parameter

Modern aircraft structures need to be further integrated and parts to be enlarged, the structural parts which require high accuracy of size, shape, and good deformed surface finish, so digital machining process has become key technology in aviation industry. Machining parameters selection is an important phase of machining process, it has very important influence on the dimensional quality of an aircraft structural part. This paper develops a methodology to get an optimal machining parameters in an aircraft structural part machining process, which can satisfies the quality specifications and minimizes the expected value of the sum of machining costs at the same time. An engineered-based model is adopted to describe the machining process of aircraft structural part firstly and then a quantitative machining parameter evaluation methods driven by cost constraint is proposed, an optimal machining parameter is obtained through a computer experiment model which can explore a large number of machining process parameter alternatives. At last, we illustrate the validity and the significance of the engineered-based machining parameters analysis method for aircraft structural parts by a case study. The results have shown that the proposed method could significantly increase the efficiency of aircraft structural parts machining process.

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.

Numerical Simulation Investigation on Machining Deformation of Aviation Thin-Walled Parts Caused by Residual Stress

2021 ◽  
Vol 1032 ◽  
pp. 186-191
Author(s):  
Jie Deng ◽  
Shi Jie Zhou ◽  
Han Jun Gao ◽  
Ming Hui Lin ◽  
Xin Li
Keyword(s):  
Numerical Simulation ◽  
Residual Stress ◽  
Residual Stresses ◽  
Simulation Models ◽  
Cutting Parameters ◽  
Stress Distributions ◽  
Machining Deformation ◽  
Proposed Model ◽  
Thin Walled ◽  
Structural Parts

Holistic thin-walled parts are common structural parts of modern aircraft to reduce the weight and increase the stiffness. Over 90% of the materials are removed from the blank, as a result, large machining deformations occur to the parts, which causes the manufacturing discrepancies and even the scrap parts. In this paper, numerical simulation models are established to predict the machining deformation of two typical aviation thin-walled parts. The blank initial and machining induced residual stresses, as well as the cutting parameters, are considered in the model. The deformations and stresses after machining are calculated using the proposed model, and the deformation and stress distributions are analyzed.

Dynamics of the macromolecular composition of the biomass of microalgae in the morning under natural light. Model

2020 ◽  
pp. 45-52
Author(s):  
Alexander S. Lelekov ◽  
Anton V. Shiryaev
Keyword(s):  
Biochemical Composition ◽  
Initial Conditions ◽  
Natural Light ◽  
Photoautotrophic Growth ◽  
Structural Part ◽  
Basic Model ◽  
Microalgae Culture ◽  
Simulation Results ◽  
Structural Parts ◽  
Macromolecular Composition

The work is devoted to modeling the growth of optically dense microalgae cultures in natural light. The basic model is based on the idea of the two-stage photoautotrophic growth of microalgae. It is shown that the increase in the intensity of sunlight in the first half of the day can be described by a linear equation. Analytical equations for the growth of biomass of microalgae and its macromolecular components are obtained. As the initial conditions, it is assumed that at the time of sunrise, the concentration of reserve biomass compounds is zero. The simulation results show that after sunrise, the growth of the microalgae culture is due only to an increase in the reserve part of the biomass, while the structural part practically does not change over six hours. Changes in the ratio of the reserve and structural parts of the biomass indicate a change in the biochemical composition of cells.

scholarly journals Towards Efficient Milling of Multi-Cavity Aeronautical Structural Parts Considering ACO-Based Optimal Tool Feed Position and Path

Micromachines ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 88
Author(s):  
Yupeng Xin ◽  
Yuanheng Li ◽  
Wenhui Li ◽  
Gangfeng Wang
Keyword(s):  
High Speed ◽  
Tool Path ◽  
Milling Process ◽  
Ant Colony ◽  
Machining Accuracy ◽  
Ant Colony Optimization Algorithm ◽  
Peripheral Milling ◽  
Structural Part ◽  
Milling Method ◽  
Structural Parts

Cavities are typical features in aeronautical structural parts and molds. For high-speed milling of multi-cavity parts, a reasonable processing sequence planning can significantly affect the machining accuracy and efficiency. This paper proposes an improved continuous peripheral milling method for multi-cavity based on ant colony optimization algorithm (ACO). Firstly, by analyzing the mathematical model of cavity corner milling process, the geometric center of the corner is selected as the initial tool feed position. Subsequently, the tool path is globally optimized through ant colony dissemination and pheromone perception for path solution of multi-cavity milling. With the advantages of ant colony parallel search and pheromone positive feedback, the searching efficiency of the global shortest processing path is effectively improved. Finally, the milling programming of an aeronautical structural part is taken as a sample to verify the effectiveness of the proposed methodology. Compared with zigzag milling and genetic algorithm (GA)-based peripheral milling modes in the computer aided manufacturing (CAM) software, the results show that the ACO-based methodology can shorten the milling time of a sample part by more than 13%.

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