Digital Twin for Optimizing Production Throughput via Joint Planning of Robotic Fleet and Factory Layout

Digital Twin for Optimizing Production Throughput via Joint Planning of Robotic Fleet and Factory Layout | 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 Article Digital Twin for Optimizing Production Throughput via Joint Planning of Robotic Fleet and Factory Layout Sepideh Valiollahi, Ignacio Rodriguez, Stefan Nordborg Eriksen, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6965762/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 18 You are reading this latest preprint version Abstract Digital twin (DT) technology is transforming industrial processes by enabling proactive decisions, minimizing human intervention, and improving automation coordination. This study explores how DTs can optimize production throughput by jointly modeling production processes, factory layouts, and heterogeneous robotic fleets with specialized roles such as transportation and manipulation. The proposed DT framework realistically simulates robotic operation and coordination, workflow dynamics, and spatial constraints across both brownfield and greenfield layouts. In brownfield settings, constrained by legacy infrastructure, the DT identifies optimal fleet size and reveals scalability limits and diminishing returns due to congestion, emphasizing the need for lean automation. In greenfield environments, designed for automation, the DT enables joint optimization of spatial layout, robotic fleet size, and functional role balance. The DT also determines that bottlenecks may arise not only from physical constraints but also from imbalances within the robotic fleet, such as insufficient manipulation capacity relative to transport capability. In a representative case study, our proposed framework suggests that scaling robotic fleets up in brownfield layouts yields minimal gains. In contrast, scaling robotic fleets up to a balanced configuration in greenfield layouts results in up to 3.5x gains in production throughput, without reducing individual efficiency of the robots. Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Mathematics and computing/Computer science Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 04 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviews received at journal 02 Mar, 2026 Reviews received at journal 01 Mar, 2026 Reviews received at journal 25 Feb, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Editor invited by journal 12 Feb, 2026 Reviews received at journal 13 Jan, 2026 Reviewers agreed at journal 16 Dec, 2025 Reviewers agreed at journal 14 Dec, 2025 Reviewers agreed at journal 07 Nov, 2025 Reviewers invited by journal 09 Oct, 2025 Editor assigned by journal 29 Jul, 2025 Submission checks completed at journal 01 Jul, 2025 First submitted to journal 01 Jul, 2025 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-6965762","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":531874955,"identity":"ad51496d-d534-4a62-8903-da4b9e7ae113","order_by":0,"name":"Sepideh Valiollahi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABF0lEQVRIie2RsUrDQBjHv/DBdbmQNSUSX+HkhtJBfZWGgD5Al4IQC4Fkse55i0BAcTs4MEsewMElS1xTcDghg6nRulxDR8H7LXcc/x/8v+8ADIa/TbD+Ohii+HnixypkcazyHWRA2ajipJumbbtXfzYJk/odouBxQre1gotTJrBgGsWtSp5lScPnd3XKT0AGT7FdcArhWS7IcqFRmHuFaK9lkL8EieeC4EzaDx4AWrmgXBxSum6vRL1C3z4U3F6OKkAGZdoC+r1CgPYNd4qumFs9o7XpZ2FVnXjApD+PCfcoK8NMkqVufCdNEFS/MVZeN1O1iujMkfVWrW7O78u4cHVbHhg64++P7C54OL9XLDUaMhgMhv/KJwOJYpjZuRw+AAAAAElFTkSuQmCC","orcid":"","institution":"Aalborg University","correspondingAuthor":true,"prefix":"","firstName":"Sepideh","middleName":"","lastName":"Valiollahi","suffix":""},{"id":531874957,"identity":"78ea52c8-68f5-4409-9bd4-9202997e81d3","order_by":1,"name":"Ignacio Rodriguez","email":"","orcid":"","institution":"University of Oviedo","correspondingAuthor":false,"prefix":"","firstName":"Ignacio","middleName":"","lastName":"Rodriguez","suffix":""},{"id":531874959,"identity":"f0c16cf9-67c7-4a96-8e80-8048d5f98fc9","order_by":2,"name":"Stefan Nordborg Eriksen","email":"","orcid":"","institution":"Aalborg University","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"Nordborg","lastName":"Eriksen","suffix":""},{"id":531874963,"identity":"2828a3c2-f06e-4436-9e2f-98f90f711979","order_by":3,"name":"Weifan Zhang","email":"","orcid":"","institution":"Aalborg University","correspondingAuthor":false,"prefix":"","firstName":"Weifan","middleName":"","lastName":"Zhang","suffix":""},{"id":531874964,"identity":"81474523-4a5e-433d-b46c-9cdba341e501","order_by":4,"name":"Sebastian Damsgaard","email":"","orcid":"","institution":"Aalborg University","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Damsgaard","suffix":""},{"id":531874966,"identity":"d1345d15-4c31-4174-a879-e1f83ddb86d2","order_by":5,"name":"Preben E. Mogensen","email":"","orcid":"","institution":"Aalborg University","correspondingAuthor":false,"prefix":"","firstName":"Preben","middleName":"E.","lastName":"Mogensen","suffix":""}],"badges":[],"createdAt":"2025-06-24 12:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6965762/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6965762/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94226534,"identity":"a26b4172-9bbd-4ae0-898b-159e5c4209a4","added_by":"auto","created_at":"2025-10-23 19:52:57","extension":"json","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7396,"visible":true,"origin":"","legend":"","description":"","filename":"f86515a9eb7d4b1aa3015b5621d71a4d.json","url":"https://assets-eu.researchsquare.com/files/rs-6965762/v1/c461a79b14f5fc1d861dbb22.json"},{"id":94227007,"identity":"d2fe5597-cb71-49ba-93e5-8d2a15157f47","added_by":"auto","created_at":"2025-10-23 20:00:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1195128,"visible":true,"origin":"","legend":"","description":"","filename":"DigitalTwinforOptimizingProductionThroughputviaJointPlanningofRoboticFleetandFactoryLayout.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6965762/v1_covered_430535d7-39b1-4ec7-a5c8-e24309eb9de3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Digital Twin for Optimizing Production Throughput via Joint Planning of Robotic Fleet and Factory Layout","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6965762/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6965762/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Digital twin (DT) technology is transforming industrial processes by enabling proactive decisions, minimizing human intervention, and improving automation coordination. This study explores how DTs can optimize production throughput by jointly modeling production processes, factory layouts, and heterogeneous robotic fleets with specialized roles such as transportation and manipulation. The proposed DT framework realistically simulates robotic operation and coordination, workflow dynamics, and spatial constraints across both brownfield and greenfield layouts. In brownfield settings, constrained by legacy infrastructure, the DT identifies optimal fleet size and reveals scalability limits and diminishing returns due to congestion, emphasizing the need for lean automation. In greenfield environments, designed for automation, the DT enables joint optimization of spatial layout, robotic fleet size, and functional role balance. The DT also determines that bottlenecks may arise not only from physical constraints but also from imbalances within the robotic fleet, such as insufficient manipulation capacity relative to transport capability. In a representative case study, our proposed framework suggests that scaling robotic fleets up in brownfield layouts yields minimal gains. In contrast, scaling robotic fleets up to a balanced configuration in greenfield layouts results in up to 3.5x gains in production throughput, without reducing individual efficiency of the robots.","manuscriptTitle":"Digital Twin for Optimizing Production Throughput via Joint Planning of Robotic Fleet and Factory Layout","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 19:52:52","doi":"10.21203/rs.3.rs-6965762/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T05:41:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T12:33:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-02T22:53:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-01T10:35:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T09:13:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74873931968250653295949105215373767125","date":"2026-02-19T05:05:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246618084590741717770193902153204580322","date":"2026-02-18T18:14:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237828090903446938558492284648620300728","date":"2026-02-18T16:51:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322941194143153103053645260262430139695","date":"2026-02-14T15:06:01+00:00","index":"hide","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-13T03:25:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T14:58:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113763176405867811589477633288780008969","date":"2025-12-16T09:48:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292627658909321307367333396500233178808","date":"2025-12-14T15:57:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"301217628638243687046721799730326862368","date":"2025-11-07T09:12:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T13:31:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-29T15:15:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-01T16:59:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-01T16:58:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a46df18-9507-458e-a126-dbbad34ce9fa","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":56543050,"name":"Physical sciences/Engineering/Electrical and electronic engineering"},{"id":56543051,"name":"Physical sciences/Mathematics and computing/Computer science"}],"tags":[],"updatedAt":"2026-05-21T22:38:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 19:52:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6965762","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6965762","identity":"rs-6965762","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}