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|Title:||CONQUAS assessment by semi-autonomous robot and application of its inspection data in BIM modelling||Authors:||Lee, Jin Long||Keywords:||DRNTU::Engineering||Issue Date:||2016||Abstract:||Construction industry, which amounts to 20% of global GNP, is by far the largest economic sector in the world. This also makes it the most labor-intensive sector. Automation in construction industry is a dream for every industry players. In contrary to manufacturing sector, construction sector faces many obstacles in automation. This is because of the distinctive nature and locations of the work environment which handicap standardization. However, some of the straight-forward tasks in construction processes are being researched to be automated. Example of these tasks are measuring, monitoring and lifting. There are only a few works dedicated to investigate on automating building inspection. This project delves into the feasibility of a robotic system to carry out Construction Quality Assessment System (CONQUAS) test. With the rising attention to the building quality by homeowners, Singapore which has recently tightened its foreign labor policy is one of the beneficiaries of this project. This project is divided into two parts: 1. Evaluate the sensing devices available in the market before incorporating them into the CONQUAS robotic system. Each selected sensing device was then tested on a testbed with built-in defects. 2. Propose a complete downstream system where inspection results can be stored and utilized over Building Information Modelling (BIM). New programs were written to facilitate the communication of inspector-contractor-inspector during the inspection stage and rectification stage. In the first part, four defects were selected because of their higher weightage in CONQUAS. These defects were hollowness, unevenness, misalignment and water seepage. A testbed was constructed with these defects embedded. Sensing devices were selected based on factors such as price, portability, ease of sourcing and speed of obtaining results. Infrared thermal camera, 2D laser scanner and voice recorder were selected for the experiment. All the raw data from the device was analyzed. Surveys and software were used to do the analysis. The results show that the selected devices are able to discover all the built-in defects with a certain degree of automation. At the end of first part, limitations and corresponding recommendations are pointed out to improve future study. In the second part, the general outline of the proposed downstream system: The inspection data from CONQUAS robotic system is fed into BIM model through .XML format file. BIM model is then updated with the discovered defects. Next, contractor is to rectify the defects using information from the updated BIM model. After rectification, contractor is to use the two programs written in this project to update BIM model again. Microsoft Visual Studio and Tekla Structures were used to achieve this. Input from Kimly Construction Pte Ltd was taken seriously in the drafting of proposed system. The proposed system was demonstrated before a research assistant was asked to try her hands at it. The comment shows that the proposed system is promising as it not only provides proper documentation of the inspection results but also systemizes rectification process.||URI:||http://hdl.handle.net/10356/67484||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||CEE Student Reports (FYP/IA/PA/PI)|
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