WITHDRAWN: Resilience-Oriented Lifecycle Automation of Structural RC Elements via a Multi-Agent System Framework
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Abstract Disjointed coordination between design, management, engineering, and production teams continues to hamper efficiency across various residential construction projects. This disconnect leads to costly delays in material specification approval, production scheduling, and component shipment. To address this issue, a Multi-Agent System (MAS) is developed to automate ERP workflows for the procurement, ordering, manufacturing, and shipping of reinforced concrete structural elements in residential housing construction. By leveraging the cohesive power of the compact Large Language Model (Phi4-14B) and Model Context Protocol (MCP), the system enhances communication between AI agents and human stakeholders, ensuring robust coordination across design validation, structural analysis, and manufacturing logistics. The Data Parser Agent digitizes and verifies material specifications, while the Structural Analyst Agent employs an accelerated Stochastic Finite Element Analysis (SFEA), utilizing Subset Simulation and Physics-Informed Neural Network (PINN) for rapid convergence without compromising accuracy. The Workflow Communicator Agent ensures closed-loop ERP integration, synchronizing project approvals and dispatching validated designs for production, with IoT-based tracking providing real-time status updates. By generating interpretable PDF/CSV reports detailing stress-strain curves, probabilistic failure modes, and sensitivity analyses, the system minimizes manual intervention while maintaining engineer oversight. Case studies conducted across 20 residential construction companies demonstrate an 88.5% reduction in coordination errors and a 71% improvement in lead times, particularly for high-variability concrete materials. This research establishes a novel AI-driven framework that bridges MAS and ERP systems, offering a scalable, autonomous enterprise digital management solution to streamline the lifecycle of reinforced concrete structural elements from specification approval to on-site delivery.
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WITHDRAWN: Resilience-Oriented Lifecycle Automation of Structural RC Elements via a Multi-Agent System Framework | Research Square window.SnipcartSettings = { analytics: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 WITHDRAWN: Resilience-Oriented Lifecycle Automation of Structural RC Elements via a Multi-Agent System Framework Artem Zaitsev This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7326131/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Editorial Note The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Editorial notes are used to provide important context regarding the topic of a preprint or to alert readers to potential issues concerning that preprint or a downstream publication associated with it. For more information on editorial notes, see our Editorial Policies . Abstract The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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. 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