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While industrial plant projects are becoming bigger, and global attention to the plant as a construct is increasing, space arrangement in plant projects is inefficient because of the complex structure of required facilities (e.g., complex MEP (mechanical, electrical, and plumbing) installations, specialized tools, etc.,). Furthermore, problems during installation, operation, and maintenance stages caused by inconsistencies between floor plans and actual layout are on the rise. Although some of these conflicts can be addressed through clash detection using BIM (building information modeling), quality BIM models are scarce, especially for existing industrial plants. This study proposes a way to address the complexities caused by changes during plant construction and securing space for the installation of equipment during the construction and lifecycle of built facilities. 3D cloud point data of space and equipment were collected using 3D laser scanning to conduct space matching. In processing the space matching, data were simplified by applying the 3D grid and by comparing the data, easier identification of the space for target equipment was accomplished. This study also proposed a pre-processing method based on sub-sampling that optimizes the point cloud data and verifies the processing speed and accuracy. Lastly, it finds free space for various equipment layouts required in industrial plant projects by space analysis, proposed algorithms, and processes for obtaining the coordinates of valid space for equipment arrangement. The proposed method of this study is expected to help solve the problems derived from arrangement and installation of new equipment in a complex plant site.
Donghyun Kim; Soonwook Kwon; Chung-Suk Cho; Borja García De Soto; Daeyoon Moon. Automatic Space Analysis Using Laser Scanning and a 3D Grid: To Industrial Plant Facilities. Sustainability 2020, 12, 9087 .
AMA StyleDonghyun Kim, Soonwook Kwon, Chung-Suk Cho, Borja García De Soto, Daeyoon Moon. Automatic Space Analysis Using Laser Scanning and a 3D Grid: To Industrial Plant Facilities. Sustainability. 2020; 12 (21):9087.
Chicago/Turabian StyleDonghyun Kim; Soonwook Kwon; Chung-Suk Cho; Borja García De Soto; Daeyoon Moon. 2020. "Automatic Space Analysis Using Laser Scanning and a 3D Grid: To Industrial Plant Facilities." Sustainability 12, no. 21: 9087.
Inaccurate information regarding the terrain in construction projects represents a major challenge to the earthwork process. Both construction quality and productivity have to be addressed by means of efficient construction information management in large earthwork projects in order to ultimately improve the cost-effectiveness of such projects. Research into the technologies for creating precise three-dimensional data and maps of earthwork sites is progressing steadily. These technologies aim to make it possible to conduct unmanned operations, leading to the effective management of earth working equipment. In recent years, as the importance of three-dimensional (3D) shape information management has grown in the construction industry, the research and application of 3D point cloud acquisition methods has likewise increased. The current method for acquiring point cloud data through laser scanning renders it difficult to acquire point clouds in large construction projects, especially in earthwork projects, due to the topographic conditions of the site as well as the physical and material limitations of the laser scanning equipment. In order to overcome and compensate for the limitations of laser scanning, image-processing technology involving unmanned aerial vehicles (UAVs) has been used to acquire point cloud data, although its application has been limited due to its low accuracy. Therefore, this study proposed a method for generating and merging hybrid point cloud data acquired from laser scanning and UAV-based image processing. In addition, a comparison was conducted between the datasets acquired from laser scanning and image processing, using examples from some case studies. Finally, an analytical comparison was performed to verify the accuracy of the UAV-based image processing technology for earthwork projects.
Daeyoon Moon; Suwan Chung; Soonwook Kwon; Jongwon Seo; Joonghwan Shin. Comparison and utilization of point cloud generated from photogrammetry and laser scanning: 3D world model for smart heavy equipment planning. Automation in Construction 2018, 98, 322 -331.
AMA StyleDaeyoon Moon, Suwan Chung, Soonwook Kwon, Jongwon Seo, Joonghwan Shin. Comparison and utilization of point cloud generated from photogrammetry and laser scanning: 3D world model for smart heavy equipment planning. Automation in Construction. 2018; 98 ():322-331.
Chicago/Turabian StyleDaeyoon Moon; Suwan Chung; Soonwook Kwon; Jongwon Seo; Joonghwan Shin. 2018. "Comparison and utilization of point cloud generated from photogrammetry and laser scanning: 3D world model for smart heavy equipment planning." Automation in Construction 98, no. : 322-331.