Indian and International Scenario on Research in Thermal Error Minimization in CNC Machine Tool

2011 ◽  
Vol 110-116 ◽  
pp. 1799-1807
Author(s):  
Sunilkumar S. Honnungar ◽  
V. Prabhu Raja ◽  
P. R. Thyla ◽  
M. Thirumalaimuthukumaran

— High speed machine tool is one of the basic needs in catering to a wide range of machining parameters with tight tolerance band. In high speed machine tool many key factors like geometric, cutting force and thermal errors decides the performance of the machine. However amongst these three, error due to thermal deformation is an important factor in influencing the accuracy level of component produced. A survey amongst Indian machine tool manufacturers reveals that there is a strong need to infuse recent technological developments in thermal error prediction and derive methodologies to minimize the same in high speed machine tool. This paper attempts snapshots of a review relating to the errors causing thermal deformations and the modeling techniques developed by researchers and practitioners globally in present scenario. The conclusions made at the end of this paper may not give the full solutions to the problems relating to thermal error but, gives a broad perspective for the Indian machine tool manufacturers’, practitioners as well researchers in India to look in to the research relating to thermal error modeling, analysis and corrective measures.

2013 ◽  
Vol 303-306 ◽  
pp. 1782-1785
Author(s):  
Chong Zhi Mao ◽  
Qian Jian Guo

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.


2010 ◽  
Vol 135 ◽  
pp. 170-173 ◽  
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang

Four key temperature points of a CNC machine tool were obtained in this paper, and a thermal error model based on the four key temperature points was proposed by using based back propagation neural network. A thermal error compensation system was developed based on the proposed model, and which has been applied to the CNC machine tool in daily production. The results show that the thermal error in workpiece diameter has been reduced from 33 to 6 .


2008 ◽  
Vol 392-394 ◽  
pp. 30-34 ◽  
Author(s):  
J.H. Shen ◽  
Jian Guo Yang

This paper presents a partial least squares neural network modeling method for CNC machine tool thermal errors. This method uses the neural network learning rule to obtain the PLS parameters instead of the traditional linear method in partial least squares regression so as to overcome the multicollinearity and nonlinearity problem in thermal error modeling. The basic principle and architecture of PLSNN is described and the new method is applied on the thermal error modeling for a CNC turning center. After model validation with two groups of new testing data and performance comparison with other five different modeling methods, PLSNN performs better than the others with better robustness.


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