Distributed Numerical Control Strategy for Error Compensation on CNC Machine Tools

2013 ◽  
Vol 415 ◽  
pp. 188-191 ◽  
Author(s):  
Si Tong Xiang ◽  
Mu Wen Shen ◽  
Jian Guo Yang
Keyword(s):  
Control Strategy ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Numerical Control ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Machine Interface ◽  
Siemens 840D ◽  
Thermal Error Compensation

A distributed numerical control (DNC) strategy for error compensation on Fanuc and Siemens CNC machine tools is proposed. A DNC network is built in multi-Fanuc CNC machine tools and the error compensation of all the machine tools is realized simultaneously. A human machine interface (HMI) is developed for Siemens 840D CNC machine tools, error components are decoupled in the X, Y and Z directions and they are compensated by 840Ds own function of thermal error compensation. Experimental verification is conducted and it proves that the proposed DNC strategy for error compensation is an effective and precision manner to improve the accuracy of machine tools.

Robustness of thermal error compensation modeling models of CNC machine tools

2013 ◽  
Vol 69 (9-12) ◽  
pp. 2593-2603 ◽  
Author(s):  
En-Ming Miao ◽  
Ya-Yun Gong ◽  
Peng-Cheng Niu ◽  
Chang-Zhu Ji ◽  
Hai-Dong Chen
Keyword(s):  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Thermal Error Compensation

scholarly journals A cuckoo search optimisation-based Grey prediction model for thermal error compensation on CNC machine tools

2017 ◽  
Vol 7 (2) ◽  
pp. 146-155 ◽  
Author(s):  
Ali M. Abdulshahed ◽  
Andrew P. Longstaff ◽  
Simon Fletcher
Keyword(s):  
Prediction Model ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Cuckoo Search ◽  
Grey Model ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Content Type ◽  
Thermal Error Compensation

Purpose The purpose of this paper is to produce an intelligent technique for modelling machine tool errors caused by the thermal distortion of Computer Numerical Control (CNC) machine tools. A new metaheuristic method, the cuckoo search (CS) algorithm, based on the life of a bird family is proposed to optimize the GMC(1, N) coefficients. It is then used to predict thermal error on a small vertical milling centre based on selected sensors. Design/methodology/approach A Grey model with convolution integral GMC(1, N) is used to design a thermal prediction model. To enhance the accuracy of the proposed model, the generation coefficients of GMC(1, N) are optimized using a new metaheuristic method, called the CS algorithm. Findings The results demonstrate good agreement between the experimental and predicted thermal error. It can therefore be concluded that it is possible to optimize a Grey model using the CS algorithm, which can be used to predict the thermal error of a CNC machine tool. Originality/value An attempt has been made for the first time to apply CS algorithm for calibrating the GMC(1, N) model. The proposed CS-based Grey model has been validated and compared with particle swarm optimization (PSO) based Grey model. Simulations and comparison show that the CS algorithm outperforms PSO and can act as an alternative optmization algorithm for Grey models that can be used for thermal error compensation.

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