Influence of turning parameters on residual stresses and roughness of 42CrMo4+QT

Influence of turning parameters on residual stresses and roughness of 42CrMo4+QT | 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 Influence of turning parameters on residual stresses and roughness of 42CrMo4+QT Diego Díaz Salamanca, Miguel Muñiz-Calvente, Pejman Ebrahimzadeh, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4281735/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Aug, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract Residual stress and surface roughness have been recognized to play a critical role in the fatigue strength of metal components. Machining processes can induce different roughness and residual stress conditions depending on the parameters used in the process. Therefore, it is essential to develop knowledge that helps to predict the residual stresses and roughness that would be obtained from different machining conditions. The main aim of this work is to establish two phenomenological models to accurately predict residual stress and roughness values on specimens turned from 42CrMo4+QT. The models are derived on data of 4 process variables: (a) insert tip radius; (b) feed rate; (c) cutting speed; and (d) depth of cut. For this purpose, a wide experimental campaign has been developed, which includes the machining of 68 specimens under various cutting scenarios, and their subsequent measurement of residual stresses and roughness. Once the experimental data were obtained, the response surface method based on the central composite design was used to fit the models, obtaining a correlation index higher than 0.9 in both cases. In this article, it is concluded that feed rate and insert radius have a greater effect on the residual stress and roughness obtained, while cutting speed and depth of cut have a lesser impact on the results. It is hoped that the findings will establish a groundwork for the machining of this material type, ensuring controlled conditions of residual stress and roughness. Turning process Roughness Residual stresses Response surface methodology Full Text Supplementary Files SupplementoryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 27 Aug, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 12 Jun, 2024 Reviewers agreed at journal 25 Apr, 2024 Reviewers invited by journal 25 Apr, 2024 Editor assigned by journal 22 Apr, 2024 First submitted to journal 19 Apr, 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-4281735","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":295409860,"identity":"3e64c809-db53-46df-b5ac-f14e1abdde59","order_by":0,"name":"Diego Díaz 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