Experimental Investigation and Multi-Response Optimization of Machinability of AA5005H34 Using Composite Desirability Coupled with PCA

Metals

Muhammad Omair¹  MohsinIqbal Qazi¹  Muhammad Abas²  Razaullah Khan³  Waqas Saleem⁴  CatalinIulian Pruncu⁵ 

[1] Department of Industrial Engineering, Jalozai Campus, University of Engineering and Technology Peshawar, Nowshera 24240, Pakistan;Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25120, Pakistan;Department of Mechanical Engineering Technology, University of Technology, Nowshera 24100, Pakistan;Department of Mechanical and Manufacturing Engineering, Institute of Technology, F91 YW50 Sligo, Ireland;Design, Manufacturing & Engineering Management, University of Strathclyde, Glasgow G1 1XJ, Scotland, UK;

关键词: milling;    minimum lubricant quantity (MQL);    aluminum alloy;    Taguchi orthogonal array;    signal to noise ratios;    analysis of variance;   

DOI  :  10.3390/met11020235

来源: DOAJ

【 摘 要 】

Minimum quantity lubricant (MQL) is an advanced technique in machining to achieve sustainability, productivity, higher precision, economic benefits, and a reduction in carbon footprints. The present research work aims to investigate the effect of the cutting process parameters of the end milling of AA5005H34 material under dry and MQL cutting environments. The key performance indicators of machining include the surface roughness profile, the material removal rate, and tool wear. Surface roughness parameters are measured with the help of the Mitutoyo surface roughness tester, and the cutting tool wear is measured according to the ISO 8688-2:1989 standard using a scanning electron microscope (SEM). Sixteen experiments are designed based on the Taguchi orthogonal array mixture design. Single responses are optimized based on signal to noise ratios, while for multi-response optimization composite desirability function coupled with principal component analysis is applied. Analysis of variance (ANOVA) results revealed that the feed rate followed by spindle speed, axial depth of the cut, width of the cut, and cutting environment are the most significant factors contributing to the surface roughness profile, material removal rate, and tool wear. The optimized parameters are obtained as cutting speed of 3000 rev/min, feed rate of 350 mm/min, axial depth of cut of 2 mm, and width of cut of 6 mm under an MQL environment.

【 授权许可】

Unknown