Optimization of machining parameters in drilling of aluminium matrix composite (Al7050-12wt.% ZrO2) using Taguchi technique

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Abstract This study focused on optimizing the drilling variables for minimizing the surface roughness (Ra) of Al7050 alloy based composite using Taguchi technique. The stir casting route was adopted to synthesis the Al7050 matrix composite with addition of 12 wt. % ZrO2 particles as reinforcement. The different process parameters such as spindle speed (v), feed (f), and depth of cut (d) were chosen as the input parameters, while the Ra was considered as the output response. Based on the parameters selection, the drilling process was carried out on Taguchi L16 orthogonal design. The SN (signal-to-noise) ratio and ANOVA (analysis of variance) were applied to yield the optimal setting of parameters and their impact contribution on Ra for the drilled composite. The SN ratio results identified that the minimum value of Ra was achieved at 1600 rpm of spindle speed, 0.12 mm/rev of feed and 1.0 mm of depth of cut. ANOVA result observed that the most noteworthy parameter for Ra was feed (62.24%), followed by spindle speed (26.24%). The contour graphs revealed that the Ra value drastically reduced when an increase in depth of cut (d) and decrease in feed (f). The regression model has been formulated to establishing the relationship of drilling parameters on Ra.
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Optimization of machining parameters in drilling of aluminium matrix composite (Al7050-12wt.% ZrO2) using Taguchi technique | 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 Optimization of machining parameters in drilling of aluminium matrix composite (Al7050-12wt.% ZrO2) using Taguchi technique Anjani Kumar Rai, Alagarsamy S V, Ismail Hossain, Sathish Kannan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2701819/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Jun, 2023 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 study focused on optimizing the drilling variables for minimizing the surface roughness (Ra) of Al7050 alloy based composite using Taguchi technique. The stir casting route was adopted to synthesis the Al7050 matrix composite with addition of 12 wt. % ZrO 2 particles as reinforcement. The different process parameters such as spindle speed (v), feed (f), and depth of cut (d) were chosen as the input parameters, while the Ra was considered as the output response. Based on the parameters selection, the drilling process was carried out on Taguchi L 16 orthogonal design. The SN (signal-to-noise) ratio and ANOVA (analysis of variance) were applied to yield the optimal setting of parameters and their impact contribution on Ra for the drilled composite. The SN ratio results identified that the minimum value of Ra was achieved at 1600 rpm of spindle speed, 0.12 mm/rev of feed and 1.0 mm of depth of cut. ANOVA result observed that the most noteworthy parameter for Ra was feed (62.24%), followed by spindle speed (26.24%). The contour graphs revealed that the Ra value drastically reduced when an increase in depth of cut (d) and decrease in feed (f). The regression model has been formulated to establishing the relationship of drilling parameters on Ra. Al7050 alloy ZrO2 Drilling process Surface roughness Taguchi technique Full Text Cite Share Download PDF Status: Published Journal Publication published 26 Jun, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 17 May, 2023 Reviewers invited by journal 08 May, 2023 Reviewers agreed at journal 25 Mar, 2023 Editor assigned by journal 16 Mar, 2023 First submitted to journal 16 Mar, 2023 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-2701819","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":186360090,"identity":"506baf13-7862-4356-ba39-79c0ffe76faf","order_by":0,"name":"Anjani Kumar Rai","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anjani","middleName":"Kumar","lastName":"Rai","suffix":""},{"id":186360091,"identity":"cc6a6cd1-5528-4f96-89bd-d675ec541a27","order_by":1,"name":"Alagarsamy S 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