Affiliations: [a]
Saveetha School of Engineering [SIMATS], Department of Mathematics, Saveetha Engineering College (Autonomous), Chennai, Tamil Nādu, India
| [b]
Department of Mathematics, Saveetha School of Engineering [SIMATS], Chennai, Tamil Nādu, India
| [c]
Department of Mathematics, Saveetha Engineering College (Autonomous), Chennai, Tamil Nādu, India
Correspondence:
[*]
Corresponding author. K. Ruth Isabels, Research Scholar, Saveetha School of Engineering [SIMATS], Department of
Mathematics, Saveetha Engineering College (Autonomous), Chennai -602105, Tamil Nādu, India.
Email [email protected].
Abstract: This work tackles the problem of maximizing machining parameters to improve the strength and resilience of 17-4 precipitation hardening (17-4 PH SS) stainless steel, which is renowned for its strong ductility but challenging machinability. We investigate different turning input parameter combinations and machining environments (dry, oil, ionic liquid), focusing on cutting temperature and flank wear as critical parameters. We analyze eighteen experimental outcomes using a VIKOR multi-criteria decision-making (MCDM) technique using CRITIC and intuitionistic fuzzy VIKOR. Expert analyses emphasize how important the machining environment is, especially when using ionic liquids (IL). Expert preferences are taken into consideration as the hybrid CRITIC intuitionistic fuzzy R-VIKOR technique balances flank wear and cutting temperature. Criteria similarity is evaluated by the Jaccard distance coefficient, but opponent’s subjective regret and group utility are given priority in the R-VIKOR method. Compromise values are determined by an enhanced normalization technique, and parameter analysis shows that the approach is more accurate and effective than previous ones. The machining parameters for (17-4 PH SS) are being optimized by this research, which is important for businesses that need high-performance materials with intricate machining requirements.
