Optimization through NSGA-II during machining of A356Al/20%SiCp metal matrix composites using PCD Tool

International conference on Materials Engineering and characterization

工业技术（总论）;材料科学

Seeman, M.^1 ; Kanagarajan, D.^1 ; Sivaraj, P.^1 ; Seetharaman, R.^2 ; Devaraju, A.^3

Department of Manufacturing Engineering, Annamalai University, Annamalainagar, Tamilnadu

608 002, India^1

Department of Mechanical Engineering, University College of Engineering, Anna University, Dindigul, Tamilnadu

624 622, India^2

Department of Mechanical Engineering, Adhi College of Engineering and Technology, Kanchipuram, Tamilnadu

631605, India^3

关键词: Average surface roughness;    Multi-regression model;    Non dominated sorting genetic algorithm (NSGA II);    Nondominated solutions;    Polycrystalline diamond tools;    Polycrystalline diamonds;    Reinforcement particles;    Tool flank wear;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/574/1/012008/pdf
DOI  :  10.1088/1757-899X/574/1/012008

来源: IOP

【 摘 要 】

Metal matrix composite (MMC) has established growing usages in the engineering for lightweight high-strength application. However, because of abrasive nature of the reinforcement particles in MMC, machinability is reduced, tool wear is high, yet only diamond tools are appropriate for machining MMC. Being a complex process, it is very complicated to establish optimal parameters for improving cutting performance. Tool flank wear (VBmax) and Average surface roughness (Ra) are the most significant output responses, which decide the machinability of a material. The effect of cutting parameters on output responses of tool flank wear and average surface roughness are conflict with each one another so there is no single optimal mixture of cutting parameters. In this study multi regression model function, based on NSGA-II was used to optimize the machining of Al/20%SiCp MMC using tipped polycrystalline diamond (PCD) tool and also characterize the relationship among input parameters and output performance. The NSGA-II based non dominated solutions of 30 combinations chosen from 100 and presented; none of them superior to any other each and every one are best based on engineer requirement.