Digital Twin-Driven Dynamic Scheduling for Multi-Disturbance Manufacturing Workshops

Digital Twin-Driven Dynamic Scheduling for Multi-Disturbance Manufacturing Workshops | 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 Digital Twin-Driven Dynamic Scheduling for Multi-Disturbance Manufacturing Workshops Mingyi Guo, Menglin Li, Qi Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8572637/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 Production scheduling efficiency exerts a profound influence on overall workshop productivity. Discrete manufacturing workshops represent complex, multi-functional systems marked by frequent variability. Previous research on workshop scheduling frequently grapples with sluggish rescheduling responses and an overly narrow focus on influencing factors. To address these issues, this study integrated multiple critical disturbances, including employee absenteeism, tool wear, and non-conforming product quality, to construct a dynamic scheduling service system driven by multiple disturbances within the workshop. By incorporating Digital Twin theory, the system monitored dynamic events in the assembly workshop. A workshop scheduling planning model was developed based on these dynamic disturbances. An enhanced genetic algorithm subsequently assessed scheduling schemes directed toward minimizing both completion time and energy consumption. The system selected the most appropriate scheduling strategy based on the severity of disturbance impact, which thus augmented the timeliness and predictability of workshop scheduling. This approach ultimately optimizes workshop efficiency and reduces energy consumption. The development and subsequent validation of a workshop Digital Twin scheduling system confirmed the efficacy of the proposed scheduling strategy. Digital Twin Dynamic scheduling Scheduling Processing workshop Full Text 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. 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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-8572637","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":574029579,"identity":"e99b7fac-b1f6-4e7f-8bf3-90bab5b1aecd","order_by":0,"name":"Mingyi 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Workshops","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":"Digital Twin, Dynamic scheduling, Scheduling, Processing workshop ","lastPublishedDoi":"10.21203/rs.3.rs-8572637/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8572637/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProduction scheduling efficiency exerts a profound influence on overall workshop productivity. Discrete manufacturing workshops represent complex, multi-functional systems marked by frequent variability. Previous research on workshop scheduling frequently grapples with sluggish rescheduling responses and an overly narrow focus on influencing factors. To address these issues, this study integrated multiple critical disturbances, including employee absenteeism, tool wear, and non-conforming product quality, to construct a dynamic scheduling service system driven by multiple disturbances within the workshop. By incorporating Digital Twin theory, the system monitored dynamic events in the assembly workshop. A workshop scheduling planning model was developed based on these dynamic disturbances. An enhanced genetic algorithm subsequently assessed scheduling schemes directed toward minimizing both completion time and energy consumption. The system selected the most appropriate scheduling strategy based on the severity of disturbance impact, which thus augmented the timeliness and predictability of workshop scheduling. This approach ultimately optimizes workshop efficiency and reduces energy consumption. The development and subsequent validation of a workshop Digital Twin scheduling system confirmed the efficacy of the proposed scheduling strategy.\u003c/p\u003e","manuscriptTitle":"Digital Twin-Driven Dynamic Scheduling for Multi-Disturbance Manufacturing Workshops","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 15:26:29","doi":"10.21203/rs.3.rs-8572637/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"84d3d0ad-51f5-4fab-a5e8-ebe0f6852289","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-04T12:58:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 15:26:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8572637","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8572637","identity":"rs-8572637","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}