Numerical Analysis of Thermal Error for a 4-Axises Horizontal Machining Center

2017 ◽  
Vol 868 ◽  
pp. 64-68
Author(s):  
Yu Bin Huang ◽  
Wei Sun ◽  
Qing Chao Sun ◽  
Yue Ma ◽  
Hong Fu Wang
Keyword(s):  
Machine Tool ◽  
Working Condition ◽  
Prediction Method ◽  
Thermal Error ◽  
Error Modeling ◽  
Model Verification ◽  
Design Stage ◽  
Thermal Errors ◽  
Machining Center ◽  
Machining Errors

Thermal deformations of machine tool are among the most significant error source of machining errors. Most of current thermal error modeling researches is about 3-axies machine tool, highly reliant on collected date, which could not predict thermal errors in design stage. In This paper, in order to estimate the thermal error of a 4-axise horizontal machining center. A thermal error prediction method in machine tool design stage is proposed. Thermal errors in workspace in different working condition are illustrated through numerical simulation and volumetric error model. Verification experiments shows the outcomes of this prediction method are basically correct.

Thermal Error Modeling of Machine Tools Based on M-RAN

2011 ◽  
Vol 121-126 ◽  
pp. 529-533
Author(s):  
Jian Han ◽  
Li Ping Wang ◽  
Ning Bo Cheng ◽  
Xu Wang
Keyword(s):  
Machine Tool ◽  
Eddy Current ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Test Results ◽  
Thermal Errors ◽  
Machining Center ◽  
Machining Errors ◽  
Minimal Resource

Thermal error in machine tools is one of the most significant causes of machining errors. This paper presents a new modeling method for machine tool error. Minimal-resource allocating networks (M-RAN) are used to establish the relationships between the temperature variables and thermal errors. Pt-100 thermal resistances and eddy current sensors are used to measure the temperature variables and the thermal errors respectively. A machining center is used to experiment. The test results show that method with minimal-resource allocating networks can predict the thermal errors of the machine accurately.

scholarly journals Thermal Error Minimization of a Turning-Milling Center with Respect to its Multi-Functionality

2020 ◽  
Vol 14 (3) ◽  
pp. 475-483
Author(s):  
Martin Mareš ◽  
◽  
Otakar Horejš ◽  
Jan Hornych
Keyword(s):  
Machine Tool ◽  
Transfer Functions ◽  
Thermal Error ◽  
Error Reduction ◽  
Model Verification ◽  
Thermal Errors ◽  
Modeling Approach ◽  
Machine Tool Structure ◽  
Calibration Time

Achieving high workpiece accuracy is a long-term goal of machine tool designers. Many causes can explain workpiece inaccuracy, with thermal errors being the most dominant. Indirect compensation (using predictive models) is a promising thermal error reduction strategy that does not increase machine tool costs. A modeling approach using transfer functions (i.e., a dynamic method with a physical basis) has the potential to deal with this issue. The method does not require any intervention into the machine tool structure, uses a minimum of additional gauges, and its modeling and calculation speed are suitable for real-time applications that result in as much as 80% thermal error reduction. Compensation models for machine tool thermal errors using transfer functions have been successfully applied to various kinds of single-purpose machines (milling, turning, floor-type, etc.) and have been implemented directly into their control systems. The aim of this research is to describe modern trends in machine tool usage and focuses on the applicability of the modeling approach to describe the multi-functionality of a turning-milling center. A turning-milling center is capable of adequately handling turning, milling, and boring operations. Calibrating a reliable compensation model is a real challenge. Options for reducing modeling and calibration time, an approach to include machine tool multi-functionality in the model structure, model transferability between different machines of the same type, and model verification out of the calibration range are discussed in greater detail.

Thermal Error Modeling of a CNC Machine Tool

2013 ◽  
Vol 303-306 ◽  
pp. 1782-1785
Author(s):  
Chong Zhi Mao ◽  
Qian Jian Guo
Keyword(s):  
Machine Tool ◽  
Back Propagation ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Accuracy ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Thermal Error Model

The purpose of this research is to improve the machining accuracy of a CNC machine tool through thermal error modeling and compensation. In this paper, a thermal error model based on back propagation networks (BPN) is presented, and the compensation is fulfilled. The results show that the BPN model improves the prediction accuracy of thermal errors on the CNC machine tool, and the thermal drift has been reduced from 15 to 5 after compensation.

Robust Machine Tool Thermal Error Modeling Through Thermal Mode Concept

2008 ◽  
Vol 130 (6) ◽  
Author(s):  
Jie Zhu ◽  
Jun Ni ◽  
Albert J. Shih
Keyword(s):  
Machine Tool ◽  
Thermal Error ◽  
Error Modeling ◽  
Thermal Mode ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Underlying Mechanisms ◽  
Modeling Strategy ◽  
Thermal Error Compensation ◽  
Insight Into

Thermal errors are among the most significant contributors to machine tool errors. Successful reduction in thermal errors has been realized through thermal error compensation techniques in the past few decades. The effectiveness of thermal error models directly determines the compensation results. Most of the current thermal error modeling methods are empirical and highly rely on the collected data under specific working conditions, neglecting the insight into the underlying mechanisms that result in thermal deformations. In this paper, an innovative temperature sensor placement scheme and thermal error modeling strategy are proposed based on the thermal mode concept. The modeling procedures for both position independent and position dependent thermal errors are illustrated through numerical simulation and experiments. Satisfactory results have been achieved in terms of model accuracy and robustness.

Study on the Application of the Combined Prediction Modeling Method to Thermal Error Modeling on NC Machine Tools

2007 ◽  
Vol 329 ◽  
pp. 779-784 ◽  
Author(s):  
Y.X. Li ◽  
Jian Guo Yang ◽  
Yu Yao Li ◽  
H.T. Zhang ◽  
G. Turyagyenda
Keyword(s):  
Prediction Model ◽  
Machine Tool ◽  
Thermal Error ◽  
Error Modeling ◽  
Primary Data ◽  
Analysis Model ◽  
Grey System ◽  
Trend Prediction ◽  
Thermal Error Modeling ◽  
Thermal Errors

Due to the complexity of machine tool thermal errors affected by various factors, a new combining prediction model, based on the theory of gery system GM (1,1) model, is applied to the trend prediction of machine tool thermal errors. The degree of smoothness of primary data sequence is first improved by function transform method and sequentially grey system GM (1,1) model is established; second, time series analysis model is established by remnant sequence of GM (1,1) model to amend the precision of grey system GM (1,1) model. Thus, the precision of combining prediction model is further improved. Through the prediction study on thermal error modeling in a spot NC turning center, testing results showed that combining prediction model can highly improve machine tool’s prediction precision and make it more effective for real-time compensation of machine tool thermal error.

Thermal Error Robust Modeling and Real Time Compensation Based on the GA-BPN Theory on a Vertical Machine Centre

2010 ◽  
Vol 97-101 ◽  
pp. 3211-3214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Yan Li ◽  
Yong Chang Yu
Keyword(s):  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Process ◽  
Field Analysis ◽  
Cnc Machine Tools ◽  
Thermal Errors ◽  
Machining Center ◽  
Thermal Error Model ◽  
Thermal Error Compensation

Thermal errors generally account for as much as 70% of the total errors of CNC machine tools, are the most contributor to the workpiece dimensional precision in precision machining process. Thermal error compensation is an effective way to decreasing thermal errors. Precision mode is a key to thermal error compensation. In this paper thermal error modeling method based on the artificial neural networks (ANN) algorithm is applied for a vertical machining center. Four key temperature points of a vertical machining center were obtained based on the temperature field analysis. A novel genetic algorism-Back propagation neural network (GA-BPN) thermal error model was proposed on the basis of four temperature points. The emulations and experiments prove that there was about a 60% increase in machine tool precision.

Thermal Error Modeling and Compensation of a CNC Machining Center

2012 ◽  
Vol 490-495 ◽  
pp. 1516-1520
Author(s):  
Jian Han ◽  
Li Ping Wang ◽  
Lian Qing Yu ◽  
Hai Tong Wang
Keyword(s):  
Clustering Analysis ◽  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Cnc Machining ◽  
Thermally Induced ◽  
Thermal Errors ◽  
Machining Center ◽  
Novel Approach ◽  
Cnc Machining Center

Error modeling and compensation is the most effective way to reduce thermal errors. In this paper, a novel approach to predict the thermal error of machine tool based on M-RAN is presented, clustering analysis is used to select the temperature variables, and then an easy and economical measurement system is applied to measure the temperature variables and thermal shift of CNC machining center. The thermally induced errors are estimated in real-time using the trained M-RAN network. The proposed approach is verified through error compensation test.

Evaluation for Static and Dynamic Characteristics of a Miniaturized Machine Tool According to Its Configuration

2006 ◽  
Author(s):  
J. H. Lee ◽  
S. H. Yang ◽  
Y. S. Kim
Keyword(s):  
Machine Tool ◽  
Dynamic Characteristics ◽  
Manufacturing System ◽  
Error Modeling ◽  
Design Stage ◽  
Volumetric Error ◽  
Actual System ◽  
Static And Dynamic Characteristics ◽  
Spindle Unit ◽  
Small Parts

Miniaturization for manufacturing system has been studied widely since the development of the smallest lathe in the world. Several prototypes are implemented, which are used to produce small parts with high precision. Accuracy and stiffness are the most important factors for design in the development of miniaturized systems. This study presents a method to evaluate static and dynamic characteristics of a miniaturized machine tool (mMT) according to its configuration before building the actual system. The proposed error estimation technique shows that volumetric error can be estimated indirectly at the design stage using error components of one axis and HTM (Homogeneous Transform Matrix), unlike the error modeling technique through direct measurement. Thus, accuracy of the system based on its configuration is analyzed at the design stage itself. The proposed analysis procedure is shown for the case of a 3 axis machine tool. In addition, dynamic characteristics of spindle unit affecting the spindle error are studied.

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