Conceptualization of Digital Twin-Enabled New Product Design Framework for the Automotive Industry 

Conceptualization of Digital Twin-Enabled New Product Design Framework for the Automotive Industry | 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 Conceptualization of Digital Twin-Enabled New Product Design Framework for the Automotive Industry Chandrasekaran Muthappan, Rajesh PK This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4534391/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 The digital twin (DT) has created various opportunities for product development businesses to exploit data obtained from the physical model. Ideally, many companies are strengthening their use cases by incorporating obtained physical data into a virtual model. Emerging communication technologies, such as the 5th generation mobile network (5G), the Internet of Things (IoT), Industrial Internet of Things (IIoT) sensors, and so on, enable the collection of data from physical products and its transmission to cloud computing, also known as big data. With the lack of standard architecture, many businesses use their own big data to develop their digital models without any roadmap. This research provides a novel DT-enabled new product design framework allowing interaction between the DT and product design environments. This system will enable data to be taken from various physical entities, stored in a centralized location, and then fed into a digital entity, which processes the data and converts it into information for decision-making. The digital entity employs various technologies to transform data into information, including artificial intelligence (AI) and machine learning (ML) models, mathematical models, and simulation models. These models generate processed synthetic or DT data, which is then used for control/monitoring and visualization/interaction reasons. In this research, data classed as visualization and interaction is integrated with the new product design framework at all four design stages, namely concept design, detailed design, design verification, and redesign, with varied data contributions to the design. A case study that used DT data processed using the AI / ML model throughout the conceptual design phase was presented. Using synthetic data, the design concept of the medium-duty truck frame assembly was iteratively tested using ten load instances before being finished. The results are encouraging since the overall weight of the frame assembly was reduced by 9% while maintaining the frame assembly's strength and safety factor. The design iterations have come down to 3 iterations from 6 iterations, which is a 50% improvement over the traditional product development processes. New product design framework Digital thread Digital twin environment Static structural analysis Frame assembly Medium-duty truck and Weight optimization Full Text Additional Declarations No competing interests reported. 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. 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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-4534391","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":315974856,"identity":"b18e4f51-c34a-417f-aa47-144d1cad5726","order_by":0,"name":"Chandrasekaran Muthappan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYDACCSDmYYARIMDeACQMLEjRwnMApEWCFC0SCTBx7IB/dvOzB2/32Nnz8xx+9uHnDoZofsnnVzf8KJBg4G/vTsBqyZ1j5oZzniUnzuxtM57Ze4Yhd+bsnLKbPUCHSZw5uwGbFgOJBDNpngPMCQbnGYwZeNsYcjfczkm7wQPUYiCRi0NL+jeglnp7+/Psnxn/ArXsv3km7eYfvFpyQLYcZtzA22PMDLZFgv3YbXy2SNzIKZOcc+B44owzZ4qZZdskcmecyWG7LWMgwYPLL/wz0rdJvDlQbc/fk76Z8W2bTW5/+/FnN9/8sZHjb+/FqgXDViDmMQCxeAioRAHsD0hRPQpGwSgYBcMfAAAyb2A7+ua96QAAAABJRU5ErkJggg==","orcid":"","institution":"Anna University, Chennai","correspondingAuthor":true,"prefix":"","firstName":"Chandrasekaran","middleName":"","lastName":"Muthappan","suffix":""},{"id":315974858,"identity":"beef0ebd-3039-4947-9833-958413fffe82","order_by":1,"name":"Rajesh PK","email":"","orcid":"","institution":"Anna University, Chennai","correspondingAuthor":false,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"PK","suffix":""}],"badges":[],"createdAt":"2024-06-05 13:17:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4534391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4534391/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60716511,"identity":"dbea1af9-94d1-4d25-9b5e-cda67e564c9e","added_by":"auto","created_at":"2024-07-19 23:31:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1775325,"visible":true,"origin":"","legend":"","description":"","filename":"J2DigitalTwinenabledproductDesignFrameworkV7.1FMSD.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4534391/v1_covered_6611212f-1423-4575-976b-f710ebf35421.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":" Conceptualization of Digital Twin-Enabled New Product Design Framework for the Automotive Industry ","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"New product design framework, Digital thread, Digital twin environment, Static structural analysis, Frame assembly, Medium-duty truck, and Weight optimization","lastPublishedDoi":"10.21203/rs.3.rs-4534391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4534391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The digital twin (DT) has created various opportunities for product development businesses to exploit data obtained from the physical model. 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