Title :
Experimental Study and Genetic Algorithm-based Optimization of Cutting Parameters in Drilling High Manganese Steel
Author :
Liang, Yang ; Li, Xu
Author_Institution :
Sch. of Mech. Eng., Dalian Jiaotong Univ., Dalian, China
Abstract :
In this study, the genetic algorithm is used to find the optimal cutting parameters for surface greatest productivity in drilling. In order to overcome shortcoming that the traditional welding stationary type drill bit is not easy to be replaced and has poor manufacturability, the machinery clamped type cemented carbide multiface drill has been developed. The cutting parameter optimization result based on the greatest productivity is given using the genetic algorithm, and the experimental study of drilling the high-manganese steel has been carried on using this result. The conclusion that the design of clamped type cutting tool is feasible has been obtained, Cutting force and torque have decreased corresponding and efficiency has been enhanced in the processing.
Keywords :
cermets; cutting; cutting tools; drilling; genetic algorithms; manganese alloys; steel; FeCMgJkJk; cemented carbide multiface drill; cutting force; cutting parameters; cutting torque; drilling; genetic algorithm; high-manganese steel; machinery clamped-type cutting tools; optimization; Blades; Drilling; Feeds; Materials; Optimization; Steel; Torque; cemented carbide tools; experimental study; genetic algorithm; optimization of parameters;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.215