{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-2936"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-2936","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Level Of Acceptance (LOA) for Scan-to-BIM Creation","abstract":"<p>This dissertation presents two contributions to the use of Reality Capture and Scan-to-BIM for facility management (FM). The first manuscript proposes a novel construct for accurately defining scope on Scan-to-BIM projects. Combining the concepts of tolerance, accuracy, and density of point cloud measurements, it will aid laser scan usage in new construction as-built validation, help renovation of existing buildings that lack as-built documentation, and support facility managers who lack accurate plans and digital twins of their buildings by helping determine and communicate the appropriate requirement for Scan-to-BIM. In view of making this process more efficient and cost effective, this article stablishes a minimum scan density for different elements of interest to building owners and proposes a novel construct, Level Of Acceptance (LOA) Specification, for establishing and clearly communicating laser scanning requirements for varying types of projects. The second manuscript proposes a novel construct of scan efficiency, applied to a case study of approximately 31 buildings and over 450 scans, to measure the level of effort required to laser scan for facility management. In conjunction with this second construct, it presents a novel approach with custom API algorithm to extract meta data from the reality capture and incorporate it into BIM applications to reveal the correlation of room types within a building and scan efficiency. The importance of this research is that it provides building owners a rational basis for assessing the cost, schedule, and value of Scan-to-BIM on their assets.</p>","abstract_html":"&lt;p&gt;This dissertation presents two contributions to the use of Reality Capture and Scan-to-BIM for facility management (FM). The first manuscript proposes a novel construct for accurately defining scope on Scan-to-BIM projects. Combining the concepts of tolerance, accuracy, and density of point cloud measurements, it will aid laser scan usage in new construction as-built validation, help renovation of existing buildings that lack as-built documentation, and support facility managers who lack accurate plans and digital twins of their buildings by helping determine and communicate the appropriate requirement for Scan-to-BIM. In view of making this process more efficient and cost effective, this article stablishes a minimum scan density for different elements of interest to building owners and proposes a novel construct, Level Of Acceptance (LOA) Specification, for establishing and clearly communicating laser scanning requirements for varying types of projects. The second manuscript proposes a novel construct of scan efficiency, applied to a case study of approximately 31 buildings and over 450 scans, to measure the level of effort required to laser scan for facility management. In conjunction with this second construct, it presents a novel approach with custom API algorithm to extract meta data from the reality capture and incorporate it into BIM applications to reveal the correlation of room types within a building and scan efficiency. The importance of this research is that it provides building owners a rational basis for assessing the cost, schedule, and value of Scan-to-BIM on their assets.&lt;/p&gt;","abstract_has_math":false,"creators":["Ikerd, William Fulton, II"],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Lisa M. Victoravich","Glenn Mueller","Andrew G. 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