scholarly journals Research on Machining Errors Control by Adaptive CNC Machining Process for Near-Net-Shaped Jet Engine Blades

2021 ◽  
Author(s):  
Dongbo Wu ◽  
Hui Wang ◽  
Jie Yu
Keyword(s):  
Position Error ◽  
Cnc Machining ◽  
Machining Process ◽  
Transmission Model ◽  
Machining Error ◽  
Contouring Error ◽  
Machining Errors ◽  
Reduction Effect ◽  
Fixture System

Abstract This study proposes an adaptive CNC machining process based on on-machine measurement to control the machining error of near-net-shaped blades. The multi-source and multi-process machining error transmission model of a near-net-shaped blade is established, and the reduction effect of the machining error transmission chain by the adaptive CNC machining process is qualitatively analyzed based on the machining error transmission flow model. The effects of the adaptive CNC machining process on the positioning benchmark error, machining position error, and machining contouring error are explored based on an experiment for the adaptive CNC machining process. In particular, the ability of the adaptive CNC machining process to cooperatively control the blade position error and the contouring error is discussed in relation to the stiffness of the blade-fixture system. The results show that the adaptive CNC machining process can reasonably reduce the machining errors caused by the positioning benchmark. The final deviation band of the blade body is reduced by 60% based on this adaptive CNC machining process. The adaptive CNC machining process can optimize the contouring error and the position error of the blade tenon root with only the stiffness of the blade-fixture system prerequisite being ensured. The adaptive CNC machining process has the excellent ability to control machining errors to improve the machining quality of the blade.

scholarly journals Adaptive CNC Machining Process Optimization of Near- net- shaped Blade based on Machining Error data Flow Control

2021 ◽  
Author(s):  
Dongbo Wu ◽  
wang hui ◽  
he lei ◽  
Jie Yu
Keyword(s):  
Flow Control ◽  
Process Optimization ◽  
Error Control ◽  
Data Flow ◽  
Cnc Machining ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Error ◽  
Fixture System ◽  
Data Flow Control

Abstract Adaptive CNC machining process is one of the efficient processing solution for near- net- shaped blade, this study proposes an adaptive computer numerical control (CNC) machining process optimization scheme based on multi-process machining errors data flow control. The geometric and mechanical models of the multi-process adaptive CNC machining process are firstly constructed. The multi-process machining error data flow and the process system stiffness of near- net- shaped blade are then experimentally explored. The machining error flow collaborative control of the near- net- shaped blade multi-process CNC machining is finally realized by the adaptive CNC machining process under the premise of sufficient stiffness of the blade- fixture system. The results show that the dynamic displacement response of the blade multi-process CNC machining process is controlled within 0.007mm. The optimized adaptive CNC machining process based on the multi-process geometric machining error data flow control and the sufficient stiffness of blade- fixture system can realize the multi-process machining error control and high-precision machining of near- net- shaped blade. The process chain of the optimized adaptive CNC machining process is reduced by 87% compared with the low melting point alloy pouring process and 50% compared with adaptive CNC machining process of the twice on-machine measurement on the blade body.

A Generic, Geometric Approach to Accurate Machining-Error Predictions for 3-Axis CNC Milling of Sculptured Surface Parts: Part I — Modeling and Formulation

2006 ◽  
Author(s):  
Zezhong C. Chen ◽  
Wei Cai
Keyword(s):  
Tool Path ◽  
Cutting Tool ◽  
Geometric Model ◽  
Research Work ◽  
Geometric Approach ◽  
Cnc Machining ◽  
Sculptured Surface ◽  
Machining Error ◽  
Machining Errors ◽  
Tool Surface

In CNC machining, machining errors are usually caused by some of the sources such as cutting tool deflection, cutting tool wear, machine tool vibration, improper coolant/lubrication, and negative thermal effect. To increase product accuracy, much research has been carried out on the prediction of machining errors. However, in milling of sculptured surface parts, due to their curved shapes, the geometries of cutting tools do not match the parts’ surfaces well if the tools cut along the tool paths on the surfaces in a point-to-point way. As a consequence, machining error is inevitable, even if there is no other source of error in ideal machining conditions. To predict machining errors caused by this tool-surface mismatch, several methods have been proposed. Some of them are simple, and some represent the geometry of machined surfaces using cutter-swept surfaces. But none of these methods is accurate and practical. In this research work, a generic, geometric approach to predicting machining errors caused by the tool-surface mismatch is proposed for 3-axis sculptured surface milling. First, a new geometric model of the furrow formed by an APT tool moving between two neighboring cutter contact (CC) points is built. Second, the mathematical formula of cutting circle envelopes is derived. Then an algorithm for calculating machining errors in each tool motion is provided. Finally, this new approach is applied to two practical parts for the accurate machining-error predictions, and these predictions are then compared to the inaccurate predictions made by two established methods to demonstrate the advantages of this approach. This approach can be used in tool path planning for high precision machining of sculptured surface parts.

Experimental study on cutting factors of multi-layer machining for large aerospace thin-walled structural parts

2021 ◽  
pp. 095440892110403
Author(s):  
Hangzhuo Yu ◽  
Han Zhong ◽  
Yong Chen ◽  
Lei Lin ◽  
Jing Shi ◽  
...  
Keyword(s):  
Coordinate System ◽  
Experimental Method ◽  
Cutting Parameters ◽  
Machining Process ◽  
Machining Error ◽  
Machining Errors ◽  
Inner Surface ◽  
Thin Walled ◽  
Optimal Cutting Parameters ◽  
Cutting Path

Large aerospace thin-walled structures will produce deformation and vibration in the machining process, which will cause machining error. In this paper, a cutting experimental method based on multi-layer machining is proposed to analyze the influence of cutting tool, cutting path, and cutting parameters on machining error in order to obtain the optimal cutting variables. Firstly, aiming at the situation that the inner surface of the workpiece deviates from the design basis, the laser scanning method is used to obtain the actual shape of the inner surface, and the method of feature alignment is designed to realize the unification of the measurement coordinate system and machining coordinate system. Secondly, a series of cutting experiments are used to obtain the machining errors of wall thickness under different cutting tools, cutting paths, and cutting parameters, and the variation of machining errors is analyzed. Thirdly, a machining error prediction model is established to realize the prediction of machining error, and the multi-objective optimization method is used to optimize the cutting parameters. Finally, a machining test was carried out to validate the proposed cutting experimental method and the optimal cutting parameters.

Eliminating Redundant Operations While Improving Part Quality by Modeling Machining Errors

2005 ◽  
Author(s):  
John Agapiou ◽  
Eric Steinhilper ◽  
Pulak Bandyopadhyay ◽  
Jeffrey Q. Xie
Keyword(s):  
Main Axis ◽  
Machining Process ◽  
Single Pass ◽  
Form Errors ◽  
Part Quality ◽  
Machining Errors ◽  
Transmission Case ◽  
System Errors

A methodology to predict part quality was applied to the perpendicularity quality of the bell face and main axis of a transmission case. By modeling the quality of different processing sequences, we were able to show that the quality of the part - perpendicularity of critical features - does not improve significantly by performing two-pass machining process instead of a single-pass. This application of our quality methodology required the modeling of additional system errors which were not developed in the earlier version and which were needed to predict certain types of form errors. In addition to improved part quality, changing the existing line to a single-pass process eliminated a bothersome job-setting procedure and tooling costs at the second-pass and increased productivity of a rebalanced line.

The Monitoring System for Stability of CNC Machining Based on cDAQ and LabVIEW

2014 ◽  
Vol 1039 ◽  
pp. 177-182
Author(s):  
Man Meng ◽  
Wen Jun Zhang ◽  
Peng Chong Wang ◽  
Denis Niedenzu ◽  
Ying Zhong Tian
Keyword(s):  
Monitoring System ◽  
Online Monitoring ◽  
Cnc Machining ◽  
Machining Process ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Online Monitoring System ◽  
Main Factors ◽  
The Stability

In recent years, researching the stability of the CNC machining process is a hotpot in CNC industry. Based on cDAQ and labVIEW, online monitoring system is presented, meanwhile, both software structure and hardware structure are introduced in detail. Researches show that vibration and pressure are the main factors for the quality of the flatness. By studying the relative vibration between the spindle and the platform in the Z axis direction, as well as the shifty pressure that tool works on the flatness of the workpiece, four experiments are designed in this paper under different technological conditions including free moving, Axial Depth of cut, speed and feed speed, which verify the reliability of the online monitoring system.

The Improvement of the Machining Accuracy by Factor Analysis Approach

2012 ◽  
Vol 201-202 ◽  
pp. 333-336
Author(s):  
Zheng Hua Huang ◽  
Cheng Rong Jiang
Keyword(s):  
Factor Analysis ◽  
Machining Process ◽  
Analysis Approach ◽  
Machining Accuracy ◽  
Analysis Method ◽  
Machining Error ◽  
Error Sources ◽  
Machining Errors ◽  
Process System ◽  
Statistical Analysis Method

In machining, a complete machining process system consists of the machine tool, the fixture, the tool and the part together, the various errors are also inevitable. The factor analysis approach and the statistical analysis method were put forward to study the machining accuracy on the basis of the error sources analysis of the machining accuracy, and the measures were introduced to improve the machining accuracy by using the factor analysis approach. The change laws are grasped by the analysis of the machining errors, so as to take the appropriate measure to reduce the machining error and improve the machining accuracy.

scholarly journals A New Error Prediction Method for Machining Process Based on a Combined Model

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Zhou ◽  
Xiao Zhu ◽  
Jun Wang ◽  
Yan Ran
Keyword(s):  
Neural Network ◽  
Prediction Method ◽  
Machining Process ◽  
Error Prediction ◽  
Combined Model ◽  
Machining Error ◽  
Advantages And Disadvantages ◽  
Model Combining ◽  
Machining Errors ◽  
The Individual

Machining process is characterized by randomness, nonlinearity, and uncertainty, leading to the dynamic changes of machine tool machining errors. In this paper, a novel model combining the data processing merits of metabolic grey model (MGM) with that of nonlinear autoregressive (NAR) neural network is proposed for machining error prediction. The advantages and disadvantages of MGM and NAR neural network are introduced in detail, respectively. The combined model first utilizes MGM to predict the original error data and then uses NAR neural network to forecast the residual series of MGM. An experiment on the spindle machining is carried out, and a series of experimental data is used to validate the prediction performance of the combined model. The comparison of the experiment results indicates that combined model performs better than the individual model. The two-stage prediction of the combined model is characterized by high accuracy, fast speed, and robustness and can be applied to other complex machining error predictions.

An Optimization Model of High-Speed and High-Precision Machining Based on Model Predictive Control

2018 ◽  
Author(s):  
Jing Zhang ◽  
Jiexiong Ding ◽  
Qingzhao Li ◽  
Qicheng Ding ◽  
Zhong Jiang ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
High Precision ◽  
Predictive Control ◽  
Feed Rate ◽  
Optimization Model ◽  
High Speed ◽  
Machining Process ◽  
Precision Machining ◽  
Contouring Error

In the multi-axis high-speed and high-precision machining process, the contouring error and the feed rate of tool tip and affect the quality of machined workpiece and the processing efficiency, respectively. The faster feed motion will result in greater tracking error of each axis. The contouring error which directly affects the quality of machined part is caused by the tracking errors of the axes. Obviously, it is difficult to improve the contouring accuracy and increase the feed rate simultaneously. To this end, a novel optimization model is developed here based on the model predictive control method. First, the feed servo model of translational and rotary axes are established, and the contouring error model is afterwards constructed. Subsequently, the optimization algorithm is derived to achieve the high processing speed, and input constraints are addressed to avoid violation of the performance limitation of the drivers. In addition, contouring error constraint, which is obtained by calculating the contouring error of the processed path, is addressed to high contour accuracy. Finally, a simulation is conducted to verify the effectiveness and superiority of the proposed method.

Application of Tool Compensation in CNC Machining

2014 ◽  
Vol 800-801 ◽  
pp. 435-439 ◽  
Author(s):  
Lian Jun Zhang ◽  
Chun Li He ◽  
Guang Jun Chen
Keyword(s):  
Dynamic Parameter ◽  
Cnc Machining ◽  
Machining Process ◽  
Maximum Probability ◽  
Machining Error ◽  
Process Step ◽  
Machining Precision ◽  
Minimum Probability ◽  
Radius Compensation ◽  
Tool Compensation

Tool compensation determines the machining precision and quality . There are tool length compensation,tool radius compensation and corner radius compensation in CNC system .The parameters of these compensation are all static.The purpose of this study was that the machining precision and quality were improved by changing the parameters of tool compensation,based upon changing the static parameters into the dynamic parameters of tool compensation.The three tool compensations were introduced and discussed about these being used in machining process and the function in processing.The concept of dynamic tool compensation was proposed in this paper. The method was used that the dynamic parameter substituted the static parameter in the processing by calculating . The process machining crafts information was included in tool compensation in every process step. The computer program was finished about how to calculate the dynamic parameter. The results indicate that high-precision machining is within the range of the maximum probability and the large machining error is within the range of the minimum probability by useing this method. Further more, the end qualified product is more than before.Process indicators and tool compensation merged is a breakthrough research by probability calculating for impoving the machining precision.We confirmed that the proposed method could be l used widely.

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