Leveraging Generative AI and CAD Automation for Efficient Automotive Wheel Design with Limited Data

Leveraging Generative AI and CAD Automation for Efficient Automotive Wheel Design with Limited Data | 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 Leveraging Generative AI and CAD Automation for Efficient Automotive Wheel Design with Limited Data Kun-Ying Li, Cheng-Kai Huang, Qing-Wei Chen, Hsuan-Cheng Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5041554/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 This study developed a method that leverages generative artificial intelligence and automated computer-aided design (CAD) technologies for the design of automotive wheel rims. First, numerous two-dimensional (2D) wheel rim designs are automatically generated by inputting prompts into Stable Diffusion, an image generation model, without predefining design parameters and constraints. Subsequently, the reasonableness of the generated 2D designs is examined, and reasonable designs are transformed into three-dimensional CAD models. The proposed method completes model training with a small amount of data and simultaneously establishes a mechanism for verifying the reasonableness of data generation, achieving reliable wheel rim design generation. Compared to existing big data methods, this approach is more easily applicable to industrial applications. Mechanical Engineering Artificial Intelligence and Machine Learning Generative AI Generative Design Stable Diffusion Model LoRa Image Processing 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-5041554","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350308931,"identity":"a8d54e8e-3b03-4f04-b553-1893ae962ab9","order_by":0,"name":"Kun-Ying Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kun-Ying","middleName":"","lastName":"Li","suffix":""},{"id":350308932,"identity":"20f90c55-5725-4801-b54e-6d5316999d5b","order_by":1,"name":"Cheng-Kai Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBAC/hk5BiBaDspnJqxF4sYZsBZjIGZsAGthI6DFILIHrCWxgXgt0jxmEj931KZvZz9j/oChwjqxQR5iCG4tcvzfJHvPHM/d2ZNj2MBwJj2xgY2HkBagLbxtx3I33OAxbGBsOwzUwruBoMMk/7YdSzcAa/lHjJbIHjNp3raaBIiWBiK0AAPZ2Fq27YDhhjNphTMSjqUbt7Hlf8CrBRiVhjffttXJGxw/vOHDhxpr2X7mYwl4tUDBYQgFUksoWmCgjkh1o2AUjIJRMCIBAA77RlvYePS+AAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Cheng-Kai","middleName":"","lastName":"Huang","suffix":""},{"id":350309001,"identity":"addbf2ae-e49e-46a4-98d0-ce507eb856a7","order_by":2,"name":"Qing-Wei Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Qing-Wei","middleName":"","lastName":"Chen","suffix":""},{"id":350309002,"identity":"99bbfc57-b5c3-42d0-9c9a-fc1dbf288139","order_by":3,"name":"Hsuan-Cheng Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hsuan-Cheng","middleName":"","lastName":"Zhang","suffix":""},{"id":350309003,"identity":"5273caaf-31c5-43b3-a1ae-b1dfb7931402","order_by":4,"name":"Tsann-Tay Tang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tsann-Tay","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2024-09-06 04:52:02","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-5041554/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5041554/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64150984,"identity":"58cbc372-17c7-45cf-9936-77d755ab066a","added_by":"auto","created_at":"2024-09-09 01:53:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1336570,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5041554/v1_covered_b9e786bf-5de9-4187-807a-b129617fb887.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eLeveraging Generative AI and CAD Automation for Efficient Automotive Wheel Design with Limited Data\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National Science and Technology Council","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":"Generative AI, Generative Design, Stable Diffusion Model, LoRa, Image Processing","lastPublishedDoi":"10.21203/rs.3.rs-5041554/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5041554/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study developed a method that leverages generative artificial intelligence and automated computer-aided design (CAD) technologies for the design of automotive wheel rims. 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