Multi-objective optimization of surface roughness and MRR in AISI 316L stainless steel processed by MQL end milling using taguchi, RSM, ANN, and RFR methods.

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Title: Multi-objective optimization of surface roughness and MRR in AISI 316L stainless steel processed by MQL end milling using taguchi, RSM, ANN, and RFR methods.
Authors: Natesh CP; Department of Mechanical Engineering, Channabasaveshwara Institute of Technology, Gubbi, Tumakuru, 572216, India., Siddeshkumar NG; Department of Mechanical Engineering, Channabasaveshwara Institute of Technology, Gubbi, Tumakuru, 572216, India., Srinivasa G; Department of Mathematics, New Horizon College of Engineering, Bengaluru, Karnataka, India., Shivaramakrishna A; Department of Mechanical Engineering, Ballari Institute of Technology and Management, Ballari, Karnataka, 583104, India., Pruthvi HM; Senior Engineer, L&T Technology Services, Bengaluru, Karnataka, India., Prasad CD; Department of Mechanical Engineering, RV Institute of Technology and Management, Bengaluru, Karnataka, 560076, India., Shashidhara YM; Department of Automobile Engineering, Malnad College of Engineering, Hassan, Karnataka, 573202, India., Amarendra HJ; Department of Mechanical Engineering, Malnad College of Engineering, Hassan, Karnataka, 573202, India., Tiwari A; Department of Mechanical Engineering, Suresh Gyan Vihar University, Jaipur, India., Aden AA; Department of Mechanical Engineering, Bulehora University, Bulehora, Ethiopia. ademhabibi@gmail.com.
Source: Scientific reports [Sci Rep] 2025 Oct 21; Vol. 15 (1), pp. 36583. Date of Electronic Publication: 2025 Oct 21.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
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ISSN:2045-2322
DOI:10.1038/s41598-025-20454-3