Open AccessOptimization of process parameters during machining of Ti6Al7Nb by grey relational analysis based on Taguchi
Author(s) -
Anjali Gupta,
Rajesh Kumar,
Harish Kumar,
Harshit Garg
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1240/1/012121
Subject(s) - grey relational analysis , taguchi methods , orthogonal array , machining , lubrication , surface roughness , mechanical engineering , process (computing) , engineering drawing , materials science , computer science , engineering , mathematics , statistics , composite material , operating system
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.