Enhancing Hard Turning performance on AISI 02 Steel with CuO Nano Cutting Fluids

Enhancing Hard Turning performance on AISI 02 Steel with CuO Nano Cutting Fluids | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Hard Turning performance on AISI 02 Steel with CuO Nano Cutting Fluids Mohamed Bacha, Mohamed ELBAH, Hamdi Laouici, Mohamed Athmane Yallese, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4748068/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jan, 2025 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract This research investigates the machinability of AISI 02 tool steel under various lubrication conditions, focusing on the application of Minimum Quantity Lubrication (MQL) and an innovative Cupric oxide (CuO)-based nanofluid. A temperature and tool wear investigation were undertaken for machining environment. A comprehensive experimental setup, utilizing L36 Taguchi-based orthogonal arrays to conduct trials under dry, MQL, and NMQL (Nanofluid MQL) conditions. The study meticulously examines the impact of four principal machining parameters: cutting speed, feed rate, environment, and cutting depth on critical outcomes such as surface roughness, cutting force, and power consumption. Employing Response Surface Methodology (RSM), the research delineates the optimal machining conditions that enhance these parameters. Notably, the feed rate was found to significantly affect surface roughness, while both cutting depth and feed rate were instrumental in determining cutting force and power consumption. The use of Cu nanofluid with MQL substantially enhanced machining performance. The paper culminates with an exploration of cutting condition optimization through the Desirability Function (DF) and the multi objectives Manta Ray Foraging Optimizer (MOMRFO), aiming to minimize surface roughness ( Ra ), cutting force ( Ft ), and power consumption ( Pc ). The results indicate that both DF and MOMRFO yield highly effective optimal settings, offering substantial contributions to the domain of hard machining. Hard turning MQL NMQL RSM DF MOMRFO AISI 02 CuO Full Text Cite Share Download PDF Status: Published Journal Publication published 24 Jan, 2025 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 29 Nov, 2024 Reviewers agreed at journal 28 Sep, 2024 Reviewers invited by journal 22 Jul, 2024 Editor assigned by journal 21 Jul, 2024 First submitted to journal 19 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4748068","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":330321688,"identity":"69a4e69a-41f5-4ff5-a5f3-f69eef078bc4","order_by":0,"name":"Mohamed Bacha","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Bacha","suffix":""},{"id":330321689,"identity":"09aed776-d04a-4f95-b261-04b657bb47d2","order_by":1,"name":"Mohamed 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A temperature and tool wear investigation were undertaken for machining environment. A comprehensive experimental setup, utilizing L36 Taguchi-based orthogonal arrays to conduct trials under dry, MQL, and NMQL (Nanofluid MQL) conditions. The study meticulously examines the impact of four principal machining parameters: cutting speed, feed rate, environment, and cutting depth on critical outcomes such as surface roughness, cutting force, and power consumption. Employing Response Surface Methodology (RSM), the research delineates the optimal machining conditions that enhance these parameters. Notably, the feed rate was found to significantly affect surface roughness, while both cutting depth and feed rate were instrumental in determining cutting force and power consumption. The use of Cu nanofluid with MQL substantially enhanced machining performance. 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