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Experimental investigation and multi-response optimization of machinability of AA5005H34 using composite desirability coupled with PCA

  • Mohsin Iqbal Qazi
  • , Muhammad Abas*
  • , Razaullah Khan
  • , Waqas Saleem
  • , Catalin Iulian Pruncu*
  • , Muhammad Omair
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Minimum quantity lubricant (MQL) is an advanced technique in machining to achieve sustainability, productivity, higher precision, economic benefits, and a reduction in carbon foot-prints. 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 signif-icant 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.

Original languageEnglish
Article number235
Pages (from-to)1-24
Number of pages24
JournalMetals
Volume11
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  4. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Aluminum alloy
  • Analysis of variance
  • Composite desirability method
  • Milling
  • Minimum lubricant quantity (MQL)
  • Principal component analysis (PCA)
  • Signal to noise ratios
  • Taguchi orthogonal ar-ray

ASJC Scopus subject areas

  • General Materials Science
  • Metals and Alloys

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