Title :
Optimization of multi-pass turning of slender bar using artificial neural networks and genetic algorithm
Author :
Bodi, Cui ; Yingjian, Li
Author_Institution :
Dept. of Mech. Eng., Huaihai Inst. of Technol., Lianyungang
Abstract :
Optimization of cutting parameters is very important issues in manufacturing engineering. For slender bar turning operations, drum-shaped error is one of the most important product quality characteristics. In this work, an artificial neural network model was developed firstly to describe the relationship between cutting parameters and drum-shaped error in slender bar turning process. Based on the obtained model, cutting parameter was optimized to satisfy the specified drum-shaped error and economics criterion in multi-pass turning of slender bar. Due to the high complexity of the machining optimization problem, genetic algorithm was employed to resolve this problem. Experimental results show that the proposed optimization method is both effective and efficient for slender bar turning operations.
Keywords :
cutting; genetic algorithms; neural nets; turning (machining); artificial neural network; cutting parameter; drum-shaped error; economics criterion; genetic algorithm; machining; manufacturing engineering; multi pass slender bar turning optimization; product quality; Artificial neural networks; Biological system modeling; Economic forecasting; Genetic algorithms; Machining; Neural networks; Optimization methods; Power system modeling; Predictive models; Turning; artificial neural network; drum-shaped error; genetic algorithm; optimization; slender bar;
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
DOI :
10.1109/ICIEA.2009.5138401
