|dc.description.abstract||Fabrication of steel assemblies is a challenging process using existing machines to perform the tasks involved such as cutting, drilling, and punching. Due to inaccuracies in the fabrication processes, imperfections will inevitably happen. In addition to the fabrication inaccuracies, errors may occur during transportation or due to the temperature changes on construction sites. These challenges become more important in the offsite construction as it requires sequenced fabrication, transportation and installation. Current approaches for quality inspection, in general, and discrepancy analysis, in particular, lack a sufficient level of automation and are prone to error due to the intensive manual work involved. Hence, a proactive framework is substantially required to systematically monitor the fabrication process and control the accuracy of assemblies in order to expedite the erection and installation processes. Additionally, finding defective assemblies is traditionally done through fitting trials on construction sites, which has always been a key challenge as it is associated with rework. Furthermore, realigning the defective assemblies is currently performed based on the workers’ experience and lacks automated planning. Therefore, detecting the defective parts in a timely manner and in a systematic way can expedite the erection process and avoids significant delays in construction projects and huge costs as a consequence.
This research aims to improve the fabrication and installation processes by detecting the incurred inaccuracies automatically and plan for realignment of the defective components systematically. In summary, the required framework to achieve these objectives includes four primary steps:
(1) Preprocessing and basic compliance checking,
(2) Spatial discrepancy detection and characterization,
(3) Calculation of the required alignments and adjustments, and
(4) Generalization of the realignment planning and actuation strategy frameworks for parallel systems.
The automated compliance checking and discrepancy analysis is performed employing advanced 3D imaging technologies which have recently opened up a wide range of solutions to acquire as-built status. Characterization of the detected discrepancies is performed by employing robotics forward kinematics concepts and combining with 3D imaging techniques. The required alignment is calculated accordingly using the robotic analogy and inverse kinematic concept. Although the proposed approach can be applied in any types of construction assembly, this thesis mainly focuses on industrial facilities such as steel pipe modules and pipe spools, in particular. Contributions of developing the described framework include:
(1) Developing a proactive strategy for rework avoidance,
(2) Algorithmic and programmable framework,
(3) Efficiency and robustness of the functions and metrics developed, and
(4) Time effectiveness of the framework.||en