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Early visual identification of component clashes and deviations helps the operator avoid major rework and support maintenance documentation throughout installation.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/prototype-pipeline-modelling-using-interval-scanning-point-clouds/650759/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/prototype-pipeline-modelling-using-interval-scanning-point-clouds/650759.png","ImageObject",300,407,{"name":42,"@type":43},"Malam Tenang","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-10-24",true,{"@type":52,"interactionType":53,"userInteractionCount":33},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What does the paper evaluate for progressive pipeline assembly?","Question",{"text":62,"@type":63},"It evaluates whether deviations that arise as installation progresses are problematic and how well unorganized point clouds can support compliance checking.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"What data sources are used in the experiments?",{"text":67,"@type":63},"An extracted point cloud model from a scanned physical prototype is used together with a 3D CAD model representing nominal geometry, plus a synthetic dataset.",{"name":69,"@type":60,"acceptedAnswer":70},"How does the proposed approach help reduce rework?",{"text":71,"@type":63},"By enabling early visual awareness of potential deviations and component clashes during pipeline assembly, allowing the operator to detect and remediate major deviations sooner.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},650759,1792898283,{"code":4,"msg":81,"data":82},"success",[83,87,91,95,100,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":81,"data":131},{"doc_id":78,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":33,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},962093532863,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Adv. Manuf.  \n[https://doi.org/10.1007/s40436-024-00515-y](https://doi.org/10.1007/s40436-024-00515-y)  \nPrototype pipeline modelling using interval scanning point clouds  \nToa Pečur1 · Frédéric Bosché1 · Gabrielis Cerniauskas1 ·  \nFrank Mill1 · Andrew Sherlock2 · Nan Yu1  \nReceived: 8 January 2024 / Revised: 21 March 2024 / Accepted: 1 June 2024 © The Author(s) 2024  \nAbstract With the aid of computer aided design (CAD) and building information modelling (BIM), as-built to as-designed comparison has seen many developments in improving the workflow of manufacturing and construction tasks. Recently, evolution has been centred around automation of scene interpretation from three-dimensional (3D) scan data. The scope of this paper is to assess assemblies asthe installation process progresses and inferring if arising deviations are problematic (complex task) . The adequacy of utilising unorganised point clouds to compliance check are trialled with a real life down-scaled prototype model in conjunction with a synthetic dataset. This work aims to highlight areas where large rework could be avoided, in part by the detection of potential clashes of components early in the pipeline installation process. With the help of an extracted model in the form of a point cloud generated from a scanned physical model and a 3D CAD model representing the nominal geometry, an operator can be made visually aware of potential deviations and component clashes during a pipeline assembly process.  \nKeywords Point clouds · Modelling · Computer aided design (CAD) · Digital manufacturing · Interval scanning  \n* Nan Yu[nan.yu@ed.ac.uk](nan.yu@ed.ac.uk)  \n1 School of Engineering, The University of Edinburgh, Edinburgh EH9 3FB, Scotland, UK  \n2 National Manufacturing Institute Scotland, Paisley PA3 2EF, Scotland, UK  \n1 Introduction  \nTo enable the comparison of as-design computer aided design (CAD) or building information modelling (BIM) models with the as-built state of construction, a three-dimensional (3D) scan of the environment is required, usually from a scanner which outputs point clouds. Information on the comparison can then be used for a variety of applications from maintenance of structures [1] to collision detection when installing or disassembling components [2] . Comparing deviations from scan to CAD/BIM have been explored by numerous researchers such as Bosché et al. [3, 4] and Anil et al. [5]. Comparing deviations to models whose parts change significantly from the CAD/BIM are complex tasks as the final location of the parts could be in a significantly different pose (differing in translation and/or rotation) as well as hindered by occlusion effects from the scanning process. Utilising the local information becomes less robust with larger deviations not documented in CAD/BIM and requires manual operator intervention. However, not all deviations are critical, implying that deviations should be further examined to assess the impact on the sub-assemblies in place.  \nIn this study, the focus is on keeping an updated version of the as-is state of a piping assembly and sub-assemblies during the installation process utilising point clouds. The study aims to integrate quality control during the installation of the piping sub-assemblies and assembly without the explicit need of separate quality assurance stations for prefabrication. Sub-assemblies are not routinely compared with neighbouring sub-assemblies in quality control, albeit rather to identify deviations or defects within the current sub-assembly [6] . This study aims to reduce rework by giving the operator the ability and flexibility to detect andremediate major deviations earlier. Indirectly, this reduces  \nthe time for installing the components at the final location and lowers the tolerances experienced when installing the assemblies on site. This provides greater oversight from the current progress of the installation and enables documentation for maintenance purposes (as-is CAD/BIM is crea","cbCailE14kuINDbW","https://ap.wps.com/l/cbCailE14kuINDbW","pdf",8988579,18,"English","# Introduction\n## Background\n# Pipeline workflows","[{\"question\":\"What does the paper evaluate for progressive pipeline assembly?\",\"answer\":\"It evaluates whether deviations that arise as installation progresses are problematic and how well unorganized point clouds can support compliance checking.\"},{\"question\":\"What data sources are used in the experiments?\",\"answer\":\"An extracted point cloud model from a scanned physical prototype is used together with a 3D CAD model representing nominal geometry, plus a synthetic dataset.\"},{\"question\":\"How does the proposed approach help reduce rework?\",\"answer\":\"By enabling early visual awareness of potential deviations and component clashes during pipeline assembly, allowing the operator to detect and remediate major deviations sooner.\"}]","Prototype pipeline modelling using interval scanning point clouds | PDF",1792843019,45]