Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning
© SAGE Publications.The application of automatic as-built modeling based on laser scanning can potentially facilitate progress tracking and control in industrial plant construction. Although notable work has been conducted in the as-built modeling field, the level of automation and ability for progr...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
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2016
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| Online Access: | http://purl.org/au-research/grants/arc/LP130100451 http://hdl.handle.net/20.500.11937/50965 |
| _version_ | 1848758579448774656 |
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| author | Chai, J. Chi, H. Wang, X. Wu, Changzhi Jung, K. Lee, J. |
| author_facet | Chai, J. Chi, H. Wang, X. Wu, Changzhi Jung, K. Lee, J. |
| author_sort | Chai, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © SAGE Publications.The application of automatic as-built modeling based on laser scanning can potentially facilitate progress tracking and control in industrial plant construction. Although notable work has been conducted in the as-built modeling field, the level of automation and ability for programs to recognize semantic information is low. Semantic information, such as an installation schedule for industrial components, is vital for identifying actual construction progress. Unfortunately, as the current practices lack the ability to use robust process mapping to turn such information into corresponding as-built models, the current successful rate of recognition remains low. To fill these gaps, this article describes a new as-built modeling process for industrial components by incorporating segmentation and three-dimensional object recognition techniques from computer vision fields. Following the generation of the as-built model, the tracking process is able to identify schedule delays through deviation analysis between the as-built and four-dimensional as-designed models. The modeling process can be integrated in a concurrent construction environment, which provides precise feedback for planners and site managers to simultaneously maintain the quality of construction plans. A case study is conducted, which demonstrates that the developed process enables as-built modeling with semantic information and automatic construction progress tracking. With a certain number of as-built components of a dehydration module being captured, a successful recognition rate of over 90% is achieved. Furthermore, the processing time of the case study lies within an acceptable time period, which supports efficient progress tracking. The results show the feasibility of the developed process, which promises to save time and labor costs during construction. |
| first_indexed | 2025-11-14T09:46:14Z |
| format | Journal Article |
| id | curtin-20.500.11937-50965 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:46:14Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-509652023-02-02T03:24:10Z Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning Chai, J. Chi, H. Wang, X. Wu, Changzhi Jung, K. Lee, J. © SAGE Publications.The application of automatic as-built modeling based on laser scanning can potentially facilitate progress tracking and control in industrial plant construction. Although notable work has been conducted in the as-built modeling field, the level of automation and ability for programs to recognize semantic information is low. Semantic information, such as an installation schedule for industrial components, is vital for identifying actual construction progress. Unfortunately, as the current practices lack the ability to use robust process mapping to turn such information into corresponding as-built models, the current successful rate of recognition remains low. To fill these gaps, this article describes a new as-built modeling process for industrial components by incorporating segmentation and three-dimensional object recognition techniques from computer vision fields. Following the generation of the as-built model, the tracking process is able to identify schedule delays through deviation analysis between the as-built and four-dimensional as-designed models. The modeling process can be integrated in a concurrent construction environment, which provides precise feedback for planners and site managers to simultaneously maintain the quality of construction plans. A case study is conducted, which demonstrates that the developed process enables as-built modeling with semantic information and automatic construction progress tracking. With a certain number of as-built components of a dehydration module being captured, a successful recognition rate of over 90% is achieved. Furthermore, the processing time of the case study lies within an acceptable time period, which supports efficient progress tracking. The results show the feasibility of the developed process, which promises to save time and labor costs during construction. 2016 Journal Article http://hdl.handle.net/20.500.11937/50965 10.1177/1063293X16670449 http://purl.org/au-research/grants/arc/LP130100451 restricted |
| spellingShingle | Chai, J. Chi, H. Wang, X. Wu, Changzhi Jung, K. Lee, J. Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title | Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title_full | Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title_fullStr | Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title_full_unstemmed | Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title_short | Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| title_sort | automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning |
| url | http://purl.org/au-research/grants/arc/LP130100451 http://hdl.handle.net/20.500.11937/50965 |