[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125223-en":3,"doc-seo-125223-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125223,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Towards the application of machine learning in digital twin technology - a multi-scale review","Review article examining the conceptual framework of digital twins and their applications across research domains, with emphasis on machine learning as a key enabler for development and integration. Highlights multidisciplinarity and multi-scale characteristics, showing how data-driven methods support modelling, visualisation, monitoring, and optimisation. Discusses benefits reported in current state-of-the-art uses and clarifies open challenges spanning advanced materials, smart buildings, and manufacturing systems.","Review  \nTowards the application of machine learning in digital twin technology: a multi‑scale review  \nLuigi Nele1 · Giulio Mattera1 · Emily W. Yap2 · Mario Vozza3,4 · Silvestro Vespoli1  \nReceived: 15 July 2024 / Accepted: 10 September 2024  \n© The Author(s) 2024 OPEN  \nAbstract  \nThis review article delves into the conceptual framework of digital twins and their diverse applications across research domains, highlighting the pivotal role of machine learning in shaping the development and integration of digital twin technology across multiple disciplines. Emphasising key features like multidisciplinarity and multi-scale aspects, the paper explores how data-driven techniques are employed for modelling, visualisation, monitoring, and optimisation within the digital twin framework, pinpointing the benefits introduced in the current state-of-the-art applications, and elucidates persisting challenges across various research fields, including advanced materials, smart buildings, and manufacturing systems.  \nKeywords Digital twin · Advanced statistics · Machine learning · Materials · Smart buildings · Manufacturing  \n1 Introduction  \nNowadays, advancements in various technologies field such as the Internet of Things (IoT) and Artificial Intelligence (AI) facilitated the digitalisation of assets across diverse industrial sectors. In particular, Digital Twins (DTs) represent a disruptive technology that can be synthesised as an integrated multi-physics, multi-scale, probabilistic simulations of a physical asset that leverages complex physical models, sensor data and historical information is able to replicate the behaviour of their real-world counterparts [1, 2] .  \nDTs, integrated within Cyber Physical Systems (CPS) [3, 4], can be used for different goals like feedback control, asset optimisation, visualisation and support to decision-making [5, 6] .  \nThe concept of a DT surpasses that of a digital model, as demonstrated in Fig. 1. A digital model enables a unidirectional flow of data, originating from the physical object and feeding into its digital representation. The digital model adjusts itself based on input from the physical asset, without directly intervening in the physical entity. Additionally, a digital model can be utilised offline to simulate what-if scenarios, facilitating the optimisation of the physical asset’s performance. Conversely, Digital Twins possess bidirectional communication capabilities [7, 8] allowing them to communicate with the physical entity via automatic decisions—based on real-time events happening in the physical world—or via visualisation with human users. A typical example of a DT application is the predictive maintenance in manufacturing systems. In this case, the DT collect data from the physical entity and elaborate it in the digital world. If an anomalous  \n* Luigi Nele, [nele@unina.it |](nele@unina.it |1Department of Chemical)[1](nele@unina.it |1Department of Chemical)[Department of Chemical](nele@unina.it |1Department of Chemical), Materials and Industrial Manufacturing Engineering, University of Naples Federico II, Naples, Italy. 2Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia. 3Department of Control and Computer Engineering (DAUIN), Polytechnic University of Turin, Turin, Italy. 4DAIMON Lab, CNR-ISMN, Bologna, Italy.  \nDiscover Applied Sciences  \n(2024) 6:502  \n| [https://doi.org/10.1007/s42452-024-06206-4](https://doi.org/10.1007/s42452-024-06206-4)  \nFig. 1 Comparison between Digital Model and Digital Twin: Visual depiction highlighting unidirectional data flow and offline scenario analysis in digital models, contrasted with bidirectional communication and real-time decision-making capabilities in digital twins  \nevent is detected by a monitoring module [9], the process can be stopped or the main parameters can be changed to adjust the process [10], interacting with the physical entity and closing the bi-directional communicatio","cbCaipLRxZ6Wog2E","https://ap.wps.com/l/cbCaipLRxZ6Wog2E","pdf",1922867,1,23,"English","en",105,"# Abstract\n# Introduction\n## Digital twins vs. digital models\n## Core components and layered framework\n## Machine learning roles in DTs","[{\"question\":\"What role does machine learning play in digital twin technology?\",\"answer\":\"Machine learning is presented as a pivotal component that enables data-driven or grey digital models and helps synthesize data from integrated sensors to provide actionable insights.\"},{\"question\":\"How do digital twins differ from digital models?\",\"answer\":\"Digital models primarily support unidirectional data flow and offline what-if simulation, while digital twins support bidirectional communication through real-time automatic decisions or interaction with users.\"},{\"question\":\"What tasks within the digital twin framework are highlighted?\",\"answer\":\"The framework emphasizes modelling, simulation, monitoring, data interpretation via visualisation, and decision-making, with applications such as anomaly detection, classification, feedback control, and optimisation.\"}]","Towards the application of machine learning in digital twin technology - a multi-scale review | PDF",1785897575,58,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"towards-the-application-of-machine-learning-in-digital-twin-technology-a-multi-scale-review-125223","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/towards-the-application-of-machine-learning-in-digital-twin-technology-a-multi-scale-review-125223/125223/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What role does machine learning play in digital twin technology?","Question",{"text":75,"@type":76},"Machine learning is presented as a pivotal component that enables data-driven or grey digital models and helps synthesize data from integrated sensors to provide actionable insights.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How do digital twins differ from digital models?",{"text":80,"@type":76},"Digital models primarily support unidirectional data flow and offline what-if simulation, while digital twins support bidirectional communication through real-time automatic decisions or interaction with users.",{"name":82,"@type":73,"acceptedAnswer":83},"What tasks within the digital twin framework are highlighted?",{"text":84,"@type":76},"The framework emphasizes modelling, simulation, monitoring, data interpretation via visualisation, and decision-making, with applications such as anomaly detection, classification, feedback control, and optimisation.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]