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Analysis and optimization in hard turning of titanium grade-I using grey relational analysis
Titanium and its alloys are used mostly in military equipment, premium sports equipment, aircraft, spacecraft, bicycle equipment, medical devices, and consumer electronics because of its low weight density, extraordinary corrosion resistance, excellent tensile strength, and toughness at very high temperature. Here, the work deals with parametric optimization in hard turning of titanium. The three machining factors like: d (depth of cut), f (feed rate), and N (cutting speed) have been considered to study its effects on MRR and Rain hard turning of titanium grade-I. In this investigation, BBD (Box-Behnken Design) is implemented as the design matrix method with 15 total numbers of experiments and GREY-Taguchi for the optimization work. The most dominating machining characteristic property is the d and its contribution is about 53.11%. The second most influencing factor is feed. It’s contribution of 19.83% and having a P-value of 0.03, whereasN is insignificant factor. The first and second-order of the mathematical model are established to check the accuracy. Mathematical models show a good correlation between the predictive result of an experiment and the genuine results. It is found that the GRG optimal level is “d3, f2, N1” of the three cutting factors and Improvement in GRG is 0.458.
Analysis and optimization in hard turning of titanium grade-I using grey relational analysis
Titanium and its alloys are used mostly in military equipment, premium sports equipment, aircraft, spacecraft, bicycle equipment, medical devices, and consumer electronics because of its low weight density, extraordinary corrosion resistance, excellent tensile strength, and toughness at very high temperature. Here, the work deals with parametric optimization in hard turning of titanium. The three machining factors like: d (depth of cut), f (feed rate), and N (cutting speed) have been considered to study its effects on MRR and Rain hard turning of titanium grade-I. In this investigation, BBD (Box-Behnken Design) is implemented as the design matrix method with 15 total numbers of experiments and GREY-Taguchi for the optimization work. The most dominating machining characteristic property is the d and its contribution is about 53.11%. The second most influencing factor is feed. It’s contribution of 19.83% and having a P-value of 0.03, whereasN is insignificant factor. The first and second-order of the mathematical model are established to check the accuracy. Mathematical models show a good correlation between the predictive result of an experiment and the genuine results. It is found that the GRG optimal level is “d3, f2, N1” of the three cutting factors and Improvement in GRG is 0.458.
Analysis and optimization in hard turning of titanium grade-I using grey relational analysis
Int J Interact Des Manuf
Pandey, B. (Autor:in) / Mahto, S. (Autor:in) / Jha, B. K. (Autor:in)
01.05.2024
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Taguchi , Grey relational analysis (<italic>GRA</italic>) , Hard turning , Material removal rate (<italic>MRR</italic>) , Surface roughness (<italic>R</italic><sub><italic>a</italic></sub>) Engineering , Engineering, general , Engineering Design , Mechanical Engineering , Computer-Aided Engineering (CAD, CAE) and Design , Electronics and Microelectronics, Instrumentation , Industrial Design
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