Automated Topography Slicing for Support-Free 3-Axis FDM

Automated Topography Slicing for Support-Free 3-Axis FDM | 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 Automated Topography Slicing for Support-Free 3-Axis FDM Joshua Nti, Michael Robert Tucker, Markus Bambach, Michael Wüthrich This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9354022/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Support-free fabrication of geometries with extended overhangs remains a fundamental challenge in non-planar fused deposition modeling (FDM), as conventional 3-axis printers cannot reorient the nozzle to maintain favorable deposition angles. To overcome this limitation, this work proposes a novel method called automated topography slicing. The proposed pipeline performs automatic overhang detection, heightmap-driven deformation-field generation, geometry warping, slicing, and inverse G-code reconstruction in a fully automated manner without requiring additional hardware or multi-axis kinematics. Experimental validation on a benchmark Tube Bracket and two additional geometries (Stanford Bunny and Elbow Junction Tube) demonstrates generality across free-form and slender features and confirms print feasibility and extrusion stability using an off-the-shelf 3-axis FDM printer. Across three geometries, the method consistently reduces support material with predictable dimensional trade-offs. High-resolution optical measurements, including full-field geometric deviation mapping, Geometric Dimensioning and Tolerancing (GD&T) evaluation, and surface roughness analysis, reveal that the reverse-mapped G-code accurately preserves the intended geometry, while observed deviations on large unsupported regions are primarily attributable to thermo-mechanical warping during material deposition. These findings delineate the boundary between algorithmic accuracy and process-induced deformation and motivate future extensions that incorporate feedback-driven or compensation-based strategies to further improve dimensional fidelity. Overall, this work establishes a practical, measurement-informed foundation for support-free, deformation-based additive manufacturing on standard 3-axis FDM systems. Heightmap-driven deformation Support-free FDM Topography-based slicing 3-axis additive manufacturing G-code back-transformation Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-9354022","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619491300,"identity":"a6499d5e-c66b-4821-8884-7d5fd061850c","order_by":0,"name":"Joshua Nti","email":"","orcid":"https://orcid.org/0009-0008-8178-6696","institution":"Ashesi University","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Nti","suffix":""},{"id":619491301,"identity":"73f2a19f-2356-4eea-800f-709dd7cf1a7d","order_by":1,"name":"Michael Robert Tucker","email":"","orcid":"https://orcid.org/0000-0001-5769-2085","institution":"ETH Zurich","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Robert","lastName":"Tucker","suffix":""},{"id":619491302,"identity":"79e90ea6-343a-4d36-a82c-12f84d850666","order_by":2,"name":"Markus Bambach","email":"","orcid":"https://orcid.org/0000-0002-8790-0807","institution":"ETH Zurich","correspondingAuthor":false,"prefix":"","firstName":"Markus","middleName":"","lastName":"Bambach","suffix":""},{"id":619491303,"identity":"d655ae17-2537-42c6-9d77-13e3136653f7","order_by":3,"name":"Michael Wüthrich","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAlElEQVRIiWNgGAWjYLCCDwwHQBQb8ToYZ5CshZmHJC0GN5KPbrb5c0fe4ADzswdEaklLu53D88xwwwE2cwOitJjdyDG7nSNxmHHbAR42CSK15H+7bWFw2J4ULTlstxkSDicSr8X+zDOzmz0HDifvP8xmRpwWyfbkZzd+/DlsO7O9+RlxWhCAmUT1o2AUjIJRMArwAAA0jzLAZ3s76wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0461-1717","institution":"ZHAW","correspondingAuthor":true,"prefix":"","firstName":"Michael","middleName":"","lastName":"Wüthrich","suffix":""}],"badges":[],"createdAt":"2026-04-08 08:36:14","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9354022/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9354022/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724265,"identity":"31b8a511-28a3-4437-bbc3-706be94cb7aa","added_by":"auto","created_at":"2026-04-12 18:27:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":25534094,"visible":true,"origin":"","legend":"","description":"","filename":"JoshuaNtiHeightmapBasedNonplanarslicing.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9354022/v1_covered_ea6d1b6e-30b7-4c19-805e-de80562c8dbf.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cem\u003eAutomated Topography Slicing for Support-Free 3-Axis FDM\u003c/em\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"ZHAW","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heightmap-driven deformation, Support-free FDM, Topography-based slicing, 3-axis additive manufacturing, G-code back-transformation","lastPublishedDoi":"10.21203/rs.3.rs-9354022/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9354022/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSupport-free fabrication of geometries with extended overhangs remains a fundamental challenge in non-planar fused deposition modeling (FDM), as conventional 3-axis printers cannot reorient the nozzle to maintain favorable deposition angles. To overcome this limitation, this work proposes a novel method called automated topography slicing. The proposed pipeline performs automatic overhang detection, heightmap-driven deformation-field generation, geometry warping, slicing, and inverse G-code reconstruction in a fully automated manner without requiring additional hardware or multi-axis kinematics. Experimental validation on a benchmark Tube Bracket and two additional geometries (Stanford Bunny and Elbow Junction Tube) demonstrates generality across free-form and slender features and confirms print feasibility and extrusion stability using an off-the-shelf 3-axis FDM printer. Across three geometries, the method consistently reduces support material with predictable dimensional trade-offs. High-resolution optical measurements, including full-field geometric deviation mapping, Geometric Dimensioning and Tolerancing (GD\u0026amp;T) evaluation, and surface roughness analysis, reveal that the reverse-mapped G-code accurately preserves the intended geometry, while observed deviations on large unsupported regions are primarily attributable to thermo-mechanical warping during material deposition. These findings delineate the boundary between algorithmic accuracy and process-induced deformation and motivate future extensions that incorporate feedback-driven or compensation-based strategies to further improve dimensional fidelity. 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