Performance Evaluation in Micro-Milling of Inconel 718 with Coated Tools through an Integrated Optimization Framework

Performance Evaluation in Micro-Milling of Inconel 718 with Coated Tools through an Integrated Optimization Framework | 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 Article Performance Evaluation in Micro-Milling of Inconel 718 with Coated Tools through an Integrated Optimization Framework Ahmad Waqar Tehami, Muhammad Rizwan Ul Haq, Ahmad Sajjad, Bilal Akbar Chuddher, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9251511/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Miniaturized systems demand micro-components exhibiting high dimensional fidelity, superior surface quality, and complex geometries for aerospace, biomedical, and microelectronic applications. Micro-milling offers flexibility and precision, but consistent performance remains challenging by rapid tool degradation, burr generation, and size-effect-dominated cutting mechanism, particularly in high strength alloys. This study investigates machinability of Inconel 718 in low-speed micro-milling using uncoated and three coated micro-end mills, with feed rates defined relative to cutting-edge radius. Taguchi L16 orthogonal array methodically assesses the impact of cutting speed, feed rate, depth of cut, and tool coating across four distinct levels each, on surface roughness, tool wear, and burr formation. The experimental outcomes were evaluated statistically using Analysis of Variance (ANOVA), while Grey Relational Analysis (GRA) was applied to identify optimal machining conditions. Results reveal that TiAlN coatings improve surface finish, nACo suppresses burr formation, and uncoated tools enhance wear resistance. The optimal condition from GRA is 10.5 µm/min cutting speed, 1.5 µm/tooth feed, and 120 µm depth of cut with uncoated tool. Response Surface Methodology (RSM) yielded average reductions of 23.81%, 11.49%, and 18.11% in surface roughness, tool wear, and burr formation, respectively. This integrated Taguchi-ANOVA-GRA-RSM Optimization (TANGRO) framework provides robust insights for optimal machining performance. Physical sciences/Engineering Physical sciences/Materials science Micro-milling Inconel 718 Multi-objective Optimization Analysis of Variance Grey Relational Analysis Response Surface Methodology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 30 Apr, 2026 Reviews received at journal 27 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviews received at journal 22 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviews received at journal 18 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 17 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Editor invited by journal 07 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 01 Apr, 2026 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. 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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-9251511","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":627795559,"identity":"c1e3cef0-a6b4-43e3-b152-d31733020b2b","order_by":0,"name":"Ahmad Waqar Tehami","email":"","orcid":"","institution":"National University of Sciences and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"Waqar","lastName":"Tehami","suffix":""},{"id":627795560,"identity":"7e644baa-a594-4eed-8bb5-6f7b6c89408b","order_by":1,"name":"Muhammad Rizwan Ul Haq","email":"","orcid":"","institution":"National University of Sciences and Technology","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Rizwan Ul","lastName":"Haq","suffix":""},{"id":627795561,"identity":"faa667ce-2613-4580-97c5-0b4dbc00cd8d","order_by":2,"name":"Ahmad Sajjad","email":"","orcid":"","institution":"National University of Sciences and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Sajjad","suffix":""},{"id":627795562,"identity":"6bfd47ba-03d6-481f-870b-e7fe491c7d9a","order_by":3,"name":"Bilal Akbar Chuddher","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYBACAwYGNiBiTmBgYD7M2AASOkC8FrZkkrXwGBOnxVzs8LPHPGXWefzSZz4bzmxjkOO7kcD84QceLZaz08yNec6lF0v25W5O3NjGYCx5I4FNsgefw27nsEnzth1O3HCGd/PBh20MiRuAWhh4iNGy/wzPY5CWeqAW5o9/iLKFh4cZ5LAEgxsJDNL4bAH6xUxyzrn0xBln2IwNZ5yTMJx55mGbtAweLebSyc8k3pRZJ/b3MD+W7Cmzkec7nnz44xs8WtCBBBBDomcUjIJRMApGAQUAALv5Tkwa5orDAAAAAElFTkSuQmCC","orcid":"","institution":"King Khalid University","correspondingAuthor":true,"prefix":"","firstName":"Bilal","middleName":"Akbar","lastName":"Chuddher","suffix":""},{"id":627795563,"identity":"e057b8d1-d44e-4ec7-9929-f88740b70533","order_by":4,"name":"Shahid Ikramullah Butt","email":"","orcid":"","institution":"National University of Sciences and Technology","correspondingAuthor":false,"prefix":"","firstName":"Shahid","middleName":"Ikramullah","lastName":"Butt","suffix":""},{"id":627795567,"identity":"44088bfa-973b-4a59-aecb-5015048ccd55","order_by":5,"name":"Abdulsalam Alqarni","email":"","orcid":"","institution":"King Khalid University","correspondingAuthor":false,"prefix":"","firstName":"Abdulsalam","middleName":"","lastName":"Alqarni","suffix":""},{"id":627795568,"identity":"96fbaaff-ec6b-4e1b-834c-1666e9d66909","order_by":6,"name":"Osamah Y. 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Micro-milling offers flexibility and precision, but consistent performance remains challenging by rapid tool degradation, burr generation, and size-effect-dominated cutting mechanism, particularly in high strength alloys. This study investigates machinability of Inconel 718 in low-speed micro-milling using uncoated and three coated micro-end mills, with feed rates defined relative to cutting-edge radius. Taguchi L16 orthogonal array methodically assesses the impact of cutting speed, feed rate, depth of cut, and tool coating across four distinct levels each, on surface roughness, tool wear, and burr formation. The experimental outcomes were evaluated statistically using Analysis of Variance (ANOVA), while Grey Relational Analysis (GRA) was applied to identify optimal machining conditions. Results reveal that TiAlN coatings improve surface finish, nACo suppresses burr formation, and uncoated tools enhance wear resistance. The optimal condition from GRA is 10.5 \u0026micro;m/min cutting speed, 1.5 \u0026micro;m/tooth feed, and 120 \u0026micro;m depth of cut with uncoated tool. Response Surface Methodology (RSM) yielded average reductions of 23.81%, 11.49%, and 18.11% in surface roughness, tool wear, and burr formation, respectively. 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