Optimization of surface roughness on slitting knives by titanium dioxide nano particles as an additive in grinding lubricant

Gilberto E. García, Federico Trigos, Demófilo Maldonado-Cortés, Laura Peña-Parás

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

An experimental design to optimize machining surface roughness measured by R a is developed in this paper. The objective is to develop a grinding lubricant containing nano particles as the main additive. A study of the influence of titanium dioxide (TiO 2) nano particles in surface roughness measured on cutting tool applications for the metal-mechanic industry (with illustration on slitting knives) is performed. Literature shows that a concentration of nano particles less or equal than 0.1% in weight has a significant influence. A response surface statistical analysis with control variables: concentration of nano particle, and manufacturing variables as spindle speed and feed rate on grinding machines were included. The analysis on slitting knives determines that spindle speed and feed rate have not significant influence on the surface quality, meanwhile the nano particles weight percentage in the oil-based lubricant was the only significant influence in the study. Response surface methodology leads to the best nano particle proportion making a significant improvement on the value of R a, from 0.9449 (for lubricant with no nano particles) to R a of 0.2805 with the best nano particle weight proportion of 0.055%, an almost 69% improvement on the response. Since the metal-mechanic industry is intensive in cutting processes, which is fundamental for industrial steel product transformation, this study opens the way to analyze another cutting tools that can be benefited from other nano particle types and concentrations.

Original languageEnglish
Pages (from-to)4111-4121
Number of pages11
JournalInternational Journal of Advanced Manufacturing Technology
Volume96
Issue number9-12
DOIs
Publication statusPublished - 1 Jun 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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