Development of Transformations between Designed and Built Structural Systems and Pipe Assemblies

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

Construction Scene Point Cloud Acquisition, Object Finding and Clutter Removal in Real Time

Within industrial construction, piping can constitute up to 50% of the cost of a typical project. It has been shown that across the activities involved in pipe fabrication, pipe fitting has the highest impact on the critical path. The pipe fitter is responsible for interpreting the isometric drawing and then performing the tack welds on piping components so that the assembly complies with the design. Three main problems in doing this task are identified as: (1) reading and interpreting the isometric drawing is challenging and error prone for spatially complicated assemblies, (2) in assemblies with tight allowable tolerance, a number of iterations will take place to fit the pipes with compliance to the design. These iterations (rework) will remain unrecorded in the production process, and (3) no continuous measurement tool exists to let the fitter check his/her work in progress against the design information and acceptance specifications. Addressing these problems could substantially improve pipe fitters’ productivity. The objective of this research is to develop a software package integrating a threefold solution to simplify complex tasks involved in pipe fabrication: (1) making design information easier to understand, with the use of a tablet, 3D imaging device and an application software, (2) providing visual feedback on the correctness of fabrication between the design intent and the as-built state, and (3) providing frequent feedback on fabrication using a step-by-step assembly and control framework. The step-by-step framework will reduce the number of required iterations for the pipe fitter. A number of challenges were encountered in order to provide a framework to make real time, visual and frequent feedback. For frequent and visual feedback, a real time 3D data acquisition tool with an acceptable level of accuracy should be adopted. This is due to the speed of fabrication in an industrial facility. The second challenge is to find the object of interest in real time, once a point cloud is acquired, and finally, once the object is found, to optimally remove points that are considered as clutter to improve the visual feedback for the pipe fitters. To address the requirement for a reliable and real time acquisition tool, Chapter 3 explores the capabilities and limitations of low cost range cameras. A commercially available 3D imaging tool was utilized to measure its performance for real time point cloud acquisition. The device was used to inspect two pipe spools altered in size. The acquired point clouds were super-imposed on the BIM (Building Information Model) model of the pipe spools to measure the accuracy of the device. Chapter 4 adapts and examines a real time and automatic object finding algorithm to measure its performance with respect to construction challenges. Then, a K-Nearest Neighbor (KNN) algorithm was employed to classify points as being clutter or corresponding to the object of interest. Chapter 5 investigates the effect of the threshold value “K” in the K-Nearest Neighbor algorithm and optimizing its value for an improved visual feedback. As a result of the work described in this thesis, along with the work of two other master students and a co-op student, a software package was designed and developed. The software package takes advantage of the investigated real time point cloud acquisition device. While the object finding algorithm proved to be effective, a 3-point matching algorithm was used, as it was more intuitive for the users and took less time. The KNN algorithm was utilized to remove clutter points to provide more accurate visual feedback more accurate to the workers

Integration of 3D Feedback Control Systems for Fabrication of Engineered Assemblies for Industrial Construction Projects

A framework and methods are presented in this thesis to support integration of 3D feedback control systems to improve dimensional conformance during fabrication of engineered assemblies such as process piping, structural steel, vessels, tanks, and associated instrumentation for industrial construction projects. Fabrication includes processes such as cutting, bending, fitting, welding, and connecting. Companies specializing in these processes are known as fabricators, fabrication shops or fab shops. Typically, fab shops do not use 3D feedback control systems in their measurement and quality control processes. Instead, most measurements are done using manual tools such as tape measures, callipers, bubble levels, straight edges, squares, and templates. Inefficiency and errors ensue, costing the industry tens of billions of dollars per year globally. Improvement is impeded by a complex fabrication industry system dependent on deeply embedded existing processes, inflexible supply chains, and siloed information environments. The goal of this thesis is to address these impediments by developing and validating a new implementation framework including several specific methods. To accomplish this goal, several research objectives must be met: 1. Determine if 3D dimensional control methods are possible for fab shops that do not have access to 3D models corresponding to shop drawings, thus serving as a step toward deploying more integrated, sophisticated and higher performing control systems. 2. Discover ways to solve incompatibility between requested information from fabrication workers and the output information delivered by state-of-the-art 3D inspection systems. 3. Conduct a credible cost-benefit analysis to understand the benefits required to justify the implementation costs, such as training, process change management, and capital expenditures for 3D data acquisition units for fab shops. 4. Investigate ways to compare quality and accuracy of dimensional control data sourced from modern point cloud processing methods, conventional surveying methods, and hand tools. Methodologies used in this research include: (1) an initial literature review to understand the knowledge gaps coupled with informal interviews of practitioners from industrial research partners, which was revisited throughout the development of the dissertation, (2) development of a conceptual framework for 3D fabrication control based on 3D imaging, (3) development and validation of algorithms to address key impediments to implementation of the framework, (4) experiments in the fab shop environment to validate elements of the framework, and (5) analysis to develop conclusions, identify weaknesses in the research, understand its contributions, and make recommendations. By developing and testing the preceding framework, it was discovered that three stages of evolution are necessary for implementation. These stages are: 1. Utilization of 3D digital templates to enable simple scan-vs-3D-model workflows for shops without access to 3D design models. 2. Development of a new language and framework for dimensional control through current ways of thinking and communication of quality control information. 3. Redefining quality control processes based on state-of-the-art tools and technologies, including automated dimensional control systems. With respect to the first stage, and to address the lack of access to 3D models, a framework for developing 3D digital template models was developed for inspecting received parts. The framework was used for developing a library of 600 3D models of piping parts. The library was leveraged to deploy a 3D quality control system that was then tested in an industrial-scale case study. The results of the case study were used to develop a discrete event simulation model. The simulation results from the model and subsequent cost-benefit analysis show that investment in integrating the scan-vs-3D-model quality control systems can have significant cost savings and provide a payback period of less than two years. With respect to the second stage and to bridge the gap between what 3D inspection systems can offer and what is expected by the fabrication workers, the concept of Termination Points was further defined and a framework for measuring and classifying them was developed. The framework was used to developed applications and tools based on the provided set of definitions. Those applications and tools were further analyzed, and the results are reported in each chapter. It is concluded that the methods developed based on the framework can have sufficient accuracy and can add significant value for fabrication quality control

Automated Pipe Spool Recognition in Cluttered Point Clouds

Construction management is inextricably linked to the awareness and control of 3D geometry. Progress tracking, quality assurance/quality control, and the location, movement, and assembly of materials are all critical processes that rely on the ability to monitor 3D geometry. Therefore, advanced capabilities in site metrology and computer vision will be the foundation for the next generation of assessment tools that empower project leaders, planners, and workers. 3D imaging devices enable the capture of the existing geometric conditions of a construction site or a fabricated mechanical or structural assembly objectively, accurately, quickly, and with greater detail and continuity than any manual measurement methods. Within the construction literature, these devices have been applied in systems that compare as-built scans to 3D CAD design files in order to inspect the geometrical compliance of a fabricated assembly to contractually stipulated dtolerances. However, before comparisons of this type can be made, the particular object of interest needs to be isolated from background objects and clutter captured by the indiscriminate 3D imaging device. Thus far, object of interest extraction from cluttered construction data has remained a manual process. This thesis explores the process of automated information extraction in order to improve the availability of information about 3D geometries on construction projects and improve the execution of component inspection, and progress tracking. Specifically, the scope of the research is limited to automatically recognizing and isolating pipe spools from their cluttered point cloud scans. Two approaches are developed and evaluated. The contributions of the work are as follows: (1) A number of challenges involved in applying RANdom SAmple Consensus (RANSAC) to pipe spool recognition are identified. (2) An effective spatial search and pipe spool extraction algorithm based on local data level curvature estimation, density-based clustering, and bag-of-features matching is presented. The algorithm is validated on two case studies and is shown to successfully extract pipe spools from cluttered point clouds and successfully differentiate between the specific pipe spool of interest and other similar pipe spools in the same search space. Finally, (3) the accuracy of curvature estimation using data collected by low-cost range-cameras is tested and the viability of use of low-cost range-cameras for object search, localization, and extraction is critically assessed

Simulation Modelling and Analysis of Impact of 3D Feedback Workflow on Prefabrication of Industrial Construction

The construction industry has not been experiencing the same level of productivity increase as the manufacturing industry, due to their divergent production methods. While traditional construction projects are unique, craft-based, and typically done on-site, manufacturing is able to mass produce standardized products on assembly lines in a controlled environment. Efforts to improve construction productivity take advantage of the more established and mature manufacturing processes and techniques, such as modularization and off-site assembly. As civil industry work requirements become more demanding, and modular component tolerance continues to decrease for more complex projects, there exists a need to incorporate and utilize quality control technologies similar to what have been used in the manufacturing and automotive industries for years. Rework of items that failed quality checks leads to significant waste of resources, resulting in reduced overall productivity represented by additional time and manpower spent on correcting the errors. The solution set to this problem ultimately needs to address lost productivity due to rework, and generate value from its operation in the industrial fabrication workflow. The use of 3D data acquisition and 3D feedback is proposed to be part of the quality control process of pipe spool fabrication, which takes place during fitting and before shipment to site. The existing prevailing workflow and the proposed workflow using the new technology are assessed using discrete-event simulation, and three implementation scenarios are investigated, which are: (1) nuclear projects, (2) small bore non-nuclear projects, and (3) large bore non-nuclear projects. They represent different quality control processes for their particular requirements, as well as their specific activity process times given the nature of their assemblies. The analysis of the simulation results show that the revised workflow improved performance for all three project types, specifically in rework reduction and overall fabrication time reduction. Risk assessment was also carried out, in order to quantify the risk mitigation and accrued benefits by implementing the revised fabrication workflow for pipe spool assembly. The difference in risk was considered as a project benefit under economic analysis, and it was found that the relatively short payback period for the fabricator justifies the initial technology investment required to set up the platform for 3D feedback in the revised workflows

An ontology-based data integration framework for construction information management

Information management during the construction phase of a built asset involves multiple stakeholders using multiple software applications to generate and store data. This is problematic as data comes in different forms and is labour intensive to piece together. Existing solutions to this problem are predominantly in proprietary applications, which are sometimes cost prohibitive for small engineering firms; or conceptual studies with use cases that cannot be easily adapted. In view of these limitations, this research presents an ontology-based data integration framework that makes use of open source tools that support Semantic Web technologies. The proposed framework enables: rapid answering of queries over construction data integrated from heterogeneous sources; data quality checks; and reuse of project software resources. The attributes and functionalities of the proposed solution align with the requirements common to small firms with limited information technology skill and budget. Consequently, this solution can be of great benefit for their data projects

Impact of Spatial Cognitive Abilities on the Effectiveness of Augmented Reality in Construction and Fabrication

Modular construction has emerged to help address the challenges posed to the construction industry by stagnant productivity rates and a shortage of skilled labor as it allows for greater automation and for work to be completed in a controlled fabrication shop environment as opposed to on a construction site. This requires tighter tolerance controls than traditional stick-built construction because the components must fit together easily with minimal on-site intervention. Modular construction has become widespread in industrial piping construction projects. Pipe spools are assembled in a fabrication shop, installed in a module and then the modules are shipped to the construction site for installation. Since piping components account for up to 50% of the cost of an industrial construction project, it is imperative to assemble these components quickly and correctly. In recent years, augmented reality has become increasingly prevalent as technological advances allow for higher quality digital environments at lower price points. These advances coupled with the increased accessibility of high-quality inexpensive 3D scanning technologies has made it possible to develop augmented reality solutions for real-time conformance control of pipe spool assemblies. An experiment was designed and conducted with the objective of assessing how an augmented reality software can increase productivity and reduce rework in pipe spool assembly. Forty engineers and twenty-one pipe fitters were recruited to assemble a PVC pipe spool using either a two-sided isometric drawing or an augmented reality software. The participants were assessed for the time required to complete the assembly and for the amount of rework they had to complete to create a compliant assembly. They were also surveyed regarding their personal interest in technology and their input on how to best implement this technology. Participants were asked to complete a short test to assess their spatial skills. The results of the completed study show that the use of an augmented reality software can increase productivity and minimize the impact of rework for both expert (pipe fitter) and drawing-literate (engineer) users. The revised workflow created through the usage of such a software essentially eliminates traditional rework. It was found that all users can benefit from the use of such a tool but that users who have lower spatial cognitive skills benefit the most

A Model for Automated Construction Materials Tracking

Materials management is a critical factor in construction project performance, particularly in the industrial sector. Research has shown that construction materials and installed equipment may constitute more than 50% of the total cost for a typical industrial project. Therefore the proper management of this single largest component can improve the productivity and cost efficiency of a project and help ensure its timely completion. One of the major problems associated with construction materials management is tracking materials in the supply chain and tracking their locations at job sites. Identification is integral to this process. Research projects conducted during the last decade to automate the identification and tracking of materials have concluded that such automation can increase productivity and cost efficiency as well as improve schedule performance, reduce the number of lost items, improve route and site optimization, and improve data entry. However, these technologies have been rapidly evolving, and knowledge concerning their implementation is sparse. One new approach enables locating of components within a few meters at a cost at least a magnitude lower than preceding technologies. It works by combining GPS located reads of RFID tags read at a rate of several thousand Hertz in order to estimate the location of these inexpensive tags which are attached to key construction materials. This technology was rapidly prototyped and deployed on two large industrial construction projects in 2007 and 2008. This thesis analyzes and synthesizes the data and experiences from these unique and large scale field trials as well as the literature in order to develop a general implementation model for automated construction materials tracking for industrial projects. It is concluded from the model that this new automated construction materials tracking technology is likely to be successful if implemented full scale on well selected future projects. This conclusion is supported by subsequent industry decisions

Deploying 3D scanning based geometric digital twins during fabrication and assembly in offsite manufacturing

Verifying geometric compliance in offsite manufacturing (OSM) is key for ensuring adequate fit-up, structural integrity, building system performance, and assembly alignment on site. The use of a geometric digital twin (gDT) from 3 D scanning can be used to digitize an assembly to detect and resolve potential problems in a prescient manner. The contribution of this article is the development of a framework for deploying and comparing three distinct gDT approaches for use during fabrication and assembly in OSM: (1) a scan-vs-BIM approach, (2) a scan-to-BIM approach and (3) a parametric BIM updating approach. Results from a commercial building project show that scan-vs-BIM is the most accurate approach, parametric BIM updating produces the most semantically rich gDT, and scan-to-BIM is a middle-tiered option, striking a balance between representational accuracy and semantic enrichment. This study concludes that future research should develop a hybrid solution of these gDT approaches and additional more accurate measurement technologies for optimal deployment in OSM

Streamlining Digital Modeling and Building Information Modelling (BIM) Uses for the Oil and Gas Projects

The oil and gas industry is a technology-driven industry. Over the last two decades, it has heavily made use of digital modeling and associated technologies (DMAT) to enhance its commercial capability. Meanwhile, the Building Information Modelling (BIM) has grown at an exponential rate in the built environment sector. It is not only a digital representation of physical and functional characteristics of a facility, but it has also made an impact on the management processes of building project lifecycle. It is apparent that there are many similarities between BIM and DMAT usability in the aspect of physical modeling and functionality. The aim of this study is to streamline the usage of both DMAT and BIM whilst discovering valuable practices for performance improvement in the oil and gas projects. To achieve this, 28 BIM guidelines, 83 DMAT academic publications and 101 DMAT vendor case studies were selected for review. The findings uncover (a) 38 BIM uses; (b) 32 DMAT uses and; (c) 36 both DMAT and BIM uses. The synergy between DMAT and BIM uses would render insightful references into managing efficient oil and gas’s projects. It also helps project stakeholders to recognise future investment or potential development areas of BIM and DMAT uses in their projects