Carbide tool life prediction and modeling in SiCp/Al turning process via artificial neural network approach

2019 2nd International Conference on Composite Materials Science and Technology

Ali Laghari, Rashid^1 ; Li, Jianguang^1 ; Laghari, Asif Ali^2 ; Mia, Mozammel^3 ; Wang, Shu-Qi^1 ; Aibo, Wang^1 ; Poonam, K.K.^4

School of Mechatronics Engineering, Harbin Institute of Technology, Harbin

150001, China^1

School of Computer Science and Technology, Harbin Institute of Technology, Harbin

150001, China^2

Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka

1208, Bangladesh^3

Department of Science and Technology, Indus University, Karachi, Pakistan^4

关键词: Artificial neural network approach;    Experimental research;    Reinforced particles;    Sicp/al;    Tool life;    Turning process;    Wear mechanisms;    Workpiece materials;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/600/1/012022/pdf
DOI  :  10.1088/1757-899X/600/1/012022

来源: IOP

【 摘 要 】

The experimental research and theoretical analysis of tool life and attached wear with the tool during turning operation of SiCp/Al 45%vol: Fraction has been carried out. This research proposed the machining factors affecting the wear of carbide tool and the laws of wear affecting the life expectancy of the tool. Artificial neural network (ANN) was utilized for analyzing the cutting process, the training of ANN achieved by back-propagation on the basis of three input parameters such as cutting speed, feed and depth of cut. The wear and damage of cutting tools in the machining process of composite materials also depend on SiC reinforced particles size and volume. The effects of workpiece material components and different cutting process parameters on the tool wear mechanism were thoroughly analyzed and measured. The main wear form on the cutting tool and its major causes for different wear patterns were recognized as adhesive and abrasive, for such phenomena the cutting speed held as a most influencing factor.