Optimization of process parameters during machining of Ti6Al7Nb by grey relational analysis based on Taguchi

Anjali Gupta, Rajesh Kumar, Harmesh Kumar, Harry Garg

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


This paper presents the optimization of parameters considering multiple response characteristics during turning of Ti6Al7Nb under the Minimum Quantity Lubrication (MQL) conditions by Grey Relational Analysis (GRA) based on Taguchi. The parameters chosen in this study are type of cutting oil, flow rate of cutting fluid and cutting speed. Response characteristics selected to evaluate the machining performance are tool flank wear and surface roughness. Firstly, the experiments designed on Taguchi L9 orthogonal array (OA) are conducted and then grey relational analysis is used to optimize both the tool flank wear and surface roughness simultaneously. Further, Analysis of Variance (ANOVA) has been carried out to find significant process parameters. All the three process parameters are found significant and the most significant factor found is cutting oil with 66.37% contribution towards grey relational grade.

Original languageEnglish
Article number012121
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - 7 Aug 2019
Externally publishedYes
Event2nd International Conference on New Frontiers in Engineering, Science and Technology, NFEST 2019 - Kurukshetra, Haryana, India
Duration: 18 Feb 201922 Feb 2019

Bibliographical note

Publisher Copyright:
© 2019 IOP Publishing Ltd. All rights reserved.


  • Machining
  • Minimum quantity lubrication
  • cuttingoil
  • wetlubrication


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