Optimization of bone drilling parameters using grey-based fuzzy algorithm

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

In this article a modified algorithm (grey based fuzzy algorithm) is used to optimize multiple performance characteristics in drilling of bone. Experiments have been performed with different cutting conditions using full factorial design. The quality parameters considered are temperature, force and surface roughness. Grey relational analysis (GRA) coupled with fuzzy logic is employed to obtain a grey fuzzy reasoning grade (GFRG) combining all the quality characteristics. The highest GFRG is obtained for the feed rate of 40 mm/min and the speed of 500 rpm and is the optimal level. Analysis of variance (ANOVA) carried out to find the significance of parameters on multiple performance characteristics revealed that the feed rate has the highest contribution on GFRG followed by the spindle speed. The optimum level of the process parameters obtained is validated by the confirmation experiment.

Original languageEnglish (US)
Pages (from-to)386-392
Number of pages7
JournalMeasurement: Journal of the International Measurement Confederation
Volume47
Issue number1
DOIs
StatePublished - 2014

Fingerprint

Fuzzy Reasoning
Fuzzy Algorithm
Drilling
drilling
Bone
bones
grade
optimization
Optimization
roughness
Analysis of variance (ANOVA)
Fuzzy logic
Grey Relational Analysis
factorial design
analysis of variance
Factorial Design
spindles
Surface roughness
Experiments
Analysis of variance

Keywords

  • Analysis of variance (ANOVA)
  • Bone drilling
  • Fuzzy logic
  • Grey relational analysis (GRA)
  • Multiple performance characteristics
  • Optimization

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Applied Mathematics

Cite this

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abstract = "In this article a modified algorithm (grey based fuzzy algorithm) is used to optimize multiple performance characteristics in drilling of bone. Experiments have been performed with different cutting conditions using full factorial design. The quality parameters considered are temperature, force and surface roughness. Grey relational analysis (GRA) coupled with fuzzy logic is employed to obtain a grey fuzzy reasoning grade (GFRG) combining all the quality characteristics. The highest GFRG is obtained for the feed rate of 40 mm/min and the speed of 500 rpm and is the optimal level. Analysis of variance (ANOVA) carried out to find the significance of parameters on multiple performance characteristics revealed that the feed rate has the highest contribution on GFRG followed by the spindle speed. The optimum level of the process parameters obtained is validated by the confirmation experiment.",
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