Using 3D Scanning for Accurate Estimation of Termination Points for Dimensional Quality Assurance in Pipe Spool Fabrication

Increased prefabrication and modularization have resulted in fabrication shops producing more complex assemblies with tighter tolerances. Most measurements in fabrication shops are still done using manual tools that are not accurate enough for engineering tolerance specifications, which can lead to rework. Three dimensional (3D) scanning and measurement systems can provide increased accuracy and digital integration capabilities, however they do not sufficiently support fast and accurate dimensional quality assurance (DQA) of pipe spool fabrication. This is because no dimensional quality assurance methods to date have focused solely on termination points for pipe spool assemblies. In the present article, a new scan-vs-BIM method is developed to accurately estimate termination points for 3D scanned cylindrical assemblies. This method relies on statistically fitting circular features at termination points and thus eliminating conventional issues with target placement for laser trackers and measurement readings for tape measures. The method is tested in an industrial-scale experiment, where 30 pipe spool assemblies were fabricated, and more than 400 quality control steps completed. The accuracy of termination point detection was benchmarked against results from a laser tracker and compared against commercial scan-to-BIM software. Results show that the developed method has an average accuracy of 1.01 mm and is significantly better than the scan-to-BIM software with an average accuracy of 4.75 mm.

Construction stakeholders’ perceived benefits and barriers for environment-friendly modular construction in a hospitality centric environment

Modular construction techniques can not only significantly contribute to improved project cost, schedule, and quality performance, but also sustainability by reducing site disruption and waste generated, creating better relocatability and reusability. However, there are still difficulties in developing and implementing modularization in a hospitality centric environment. Thus, the primary goal of this research is to identify the opportunities and challenges of implementing sustainable modular construction techniques in a hospitality-centric environment. In this study, the approach includes the formulation of a survey, which was distributed to 600 industry professionals in Las Vegas and completed by 63 industry professionals, followed by three personal interviews. The results showed that: 1) 85% percent of survey participants expected an improvement in schedule, and 65% of that elected to use a form of modularization actually experienced an improved schedule; 2) 62% of the participants claimed that they would keep using modular methods in the next 12 months, whereas 44% of the participants claimed they would increase their use of modularization in the next five years; 3) two of the top five expected benefits achieved included less site disruption (noise/traffic and dust) and reduced waste, which contribute towards sustainable construction; 4) transportation/logistics was selected by industry professionals as a key barrier in the implementation of modular construction; 5) to implement more sustainable construction, practitioners require additional research to improve and overcome the key barrier of transportation/logistics; 6) if construction professionals gain more modular project experience, their perceived benefits and barriers could increase and decrease, respectively. The results from this research provide valuable insights for implementing sustainable modular methods in hospitality-centric environments.

Overview of the Characteristics of the Modular Industry and Barriers to its Increased Market Share

Modular and offsite construction approaches reduce project duration and cost by synchronizing offsite and onsite work. Project activities are undertaken in a controlled offsite facility to minimize the effects of inclement weather and site disruptions, while meeting safety and quality requirements. To study the characteristics of modular and offsite construction, questionnaires have been conducted during the last decade by many organizations, including the Modular Building Institute (MBI), the Buildoffsite campaigning organization in the United Kingdom, the Canadian Manufactured Housing Institute, the National Institute of Building Sciences, McGraw-Hill Construction, and the Fails Management Institute. This paper introduces comprehensive analysis of the results of a questionnaire survey carried out in collaboration between members of the Department of Building, Civil & Environmental Engineering at Concordia University, the Modular Building Institute, NRB Inc., and the Department of Civil & Environmental Engineering at the University of Alberta. The questionnaire focuses on two issues: (1) the characteristics of the modular and offsite construction industry, and (2) the barriers against increased market share in this industry. For the latter, an effort was made to address a set of five factors identified in a workshop on the topic of challenges and opportunities for modular construction in Canada held in Montréal in 2015 to analyze barriers to growth of modular construction in the Canadian context. Key findings of this survey include requests for use of a separate building code for modular construction design, innovative financing and insurance solutions, standards that consider procurement regulations, and for financial institutions to create lending programs suited for modular construction.

Combined Application of 4D BIM Schedule and an Immersive Virtual Reality on a Modular Project: UNLV Solar Decathlon Case

The use of a 4D schedule as technological advancement has brought significant improvement to the planning and execution of construction projects, through visualizing step-wise construction progress, following a sequence of pre-planned activities, and finalizing a baseline schedule with necessary changes. Moreover, the application of immersive virtual reality (IVR) to create an interactive 4D BIM schedule of a planned structure has made it possible to create a detailed plan of any construction project. Because of these benefits, the use of 4D schedules and immersive virtual reality in the construction industry has increased, leading to improved planning and execution. However, past studies have given little attention to the applications of such technologies on modular projects. Thus, this research applied a 4D schedule, along with immersive virtual reality, on a modular project, and verified their benefits and effectiveness. The results showed that most of the participants who experienced a 4D BIM schedule, along with immersive virtual reality (4D/IVR), strongly agreed that it is an easy and straightforward way to visualize the project, understand the schedule, and find any errors. Moreover, while fewer than half of the participants scheduled the assembly sequence correctly with conventional schedule and 2D drawings, almost all of them sequenced the assembly successfully with 4D/IVR. Based on the findings, this research concludes that the implementation of a 4D BIM schedule, along with virtual reality technology, can enhance the fabrication and assembly performance of modules.

Integrating machine learning with QFD for selecting functional requirements in construction automation

An important aspect of the conceptual design is at the customer requirement definition stage, where an optimal number of functional requirements are specified with the application of quality function deployment. To facilitate a systematic specification of functional requirements, state-of-the-art unsupervised machine learning techniques will be introduced in the feature selection of functional requirements. However, the scarcity of references on unsupervised feature selection in the literature reflects the difficulty associated with this topic. At the customer requirement definition phase, three techniques will be proposed for selecting functional requirements, namely: (a) principal component analysis, (b) forward orthogonal search, and (c) Kohonen self-organizing map neural network. These machine learning feature selection techniques address the limitations of current approaches in systematically determining the minimum functional requirements from the mapping of customer requirements in quality function deployment. When applied to the conceptual design of the transportable automated wood wall framing machine that is under development at the University of Alberta, the proposed feature selection techniques have been observed to be: (i) fast, (ii) amenable to small quality function deployment dataset, and (iii) adequate in realizing design objectives. The results presented in this paper can be easily extended to online determination of customer requirements and functional requirements, project management, contract management, and marketing.

Feasibility and Implications of the Modular Construction Approach for Rapid Post-Disaster Recovery

The adverse social and financial impacts of catastrophic disasters are increasing as population centers grow. In recent years, destroying homes and infrastructures has resulted in a major loss of life and created countless refugees. For example, Hurricane Katrina in August 2005 damaged over 214,700 homes in New Orleans and forced over 800,000 citizens to live outside of their homes due to flooding. After disastrous events, the government agencies have to respond to post-disaster housing issues quickly and efficiently and provide sufficient resources for temporary housing for short-term disaster relief and reconstruction of destroyed and damaged housing for full rehabilitation. Modular construction is a promising solution for improving the process of post-disaster housing reconstruction because of its inherent characteristic of time-efficiency. This study aimed to evaluate the potentials and feasibility of the prefabricated/modular construction approach that can be adapted to facilitate the post-disaster recovery process. An extensive literature review has been carried out to identify the features of modular construction, which can add value to the post-disaster recovery process. To investigate the suitability and practicability of implementing modular construction for post-disaster reconstruction and to identify major barriers of its implementation, a survey has been conducted among Architecture, Engineering, and Construction (AEC) experts who have experience in prefabrication/modularization, and/or involved in post-disaster reconstruction projects. The results of the study indicate that prefabricated/modular construction is a promising approach to improve time-efficiency of post-disaster reconstruction and tackle challenges of current practices by its unique benefits such as reduced demand for on-site labor (overcome local labor pool constraints impacted by the disaster) and resources (overcome the shortage of equipment and materials), shorter schedule (due to concurrent & non-seasonal), reduced site congestion, and improved labor productivity (due to assembly line-like and controlled environment).

Planning semi-automated precast production using GA

Although fully automated production systems have been developed and used in some industry leaders, most of the precast factories have yet to be developed to that stage. Semi-automated production lines are still popularly used. As production productivity can be maximally improved within the physical constraints by applying a sound production plan, this paper tends to propose a production planning method for the semi-automated precast production line using genetic algorithm (GA). The production planning problem is formulated into a flexible job shop scheduling problem (FJSSP) model and solved using an integrated approach. Thanks to the development of new technologies such as building information modeling (BIM) platform and radio frequency identification (RFID), implementation of a just-in-time (JIT) schedule in the semi-automated precast production line becomes practicable on the grounds of risk mitigation and enhanced demand forecast capability. In this regard, the optimization objectives are minimum makespan, station idle time, and earliness and tardiness penalty. An example was applied to validate the integrated GA approach. The experimental results show that the developed GA approach is a useful and effective method for solving the problem that it can return high-quality solutions. This paper thus contributes to the body of knowledge new precast production planning method for practical usage.

Development of Automated Top-Down Construction System for Low-rise Building Structures

Automation is the best solution for achieving high productivity and quality in the construction industry at reduced cost and time. The main objective of this study is to develop an economical automated construction system (ACS) for low-rise buildings. The incremental development of the construction system and the structural system through different versions of laboratory prototypes are described in this paper. These ACS prototypes adopt a top-down construction method. This method involves the building of the structural system step by step from the top floor to the bottom floor by connecting and lifting structural modules. ACS prototype 1 consist of wooden structural modules and electric motor system. ACS prototype 2 has a highly automated custom designed hydraulic motor system to construct steel structural frame. ACS prototype 3 is a partially automated system where the steel structural modules are connected manually. These prototypes were evaluated on the basis of function, cost and efficiency of operations. Based on overall performance, ACS prototype 3 is identified as the best economical option for the construction of low-rise buildings. When the speed of construction is more important than cost, the ACS prototype 2 is the apt solution. This paper describes the challenges in developing an ACS and the criteria to evaluate its performance. It also includes a preliminary framework for the development of an automated construction monitoring system and its experimental evaluation. This machine learning-based framework is to identify the operations of ACS from sensor measurements using Support Vector Machines. Most of the operations are identified reasonably well and the best identification accuracy is 96%. The future studies are focusing on to improve the accuracy of operation identification, further development of the monitoring system and the ACS for actual implementation in construction sites.

Benchmarking and Improving Dimensional Quality on Modular Construction Projects – A Case Study

Dimensional quality plays a key role in project success for modular construction. While approaches exist for reducing rework associated with dimensional variability in traditional construction (i.e., onsite resolution), more proactive approaches must be employed during offsite production of modules. Unfortunately, the stricter dimensional quality demands in modular construction are not yet completely addressed in existing guidelines or studies. As such, contractors often must resort to use of reactive measures to reduce rework. This paper bridges this gap by demonstrating how to implement continuous benchmarking and improvement of dimensional quality by comparing as-built and nominal 3D geometric data across modular construction projects. A case study is presented for two nearly identical modular construction projects, which are carried out in succession. The first project is used to quantify and benchmark key impacts on overall dimensional quality, while strategic improvements are introduced in the second project to improve quality and reduce rework. The results of this study demonstrate how contractors can achieve adequate dimensional quality and reduce rework on successive modular construction projects.

Towards Dynamic Vertical Urbanism

Nowadays a great number of new developments are claimed in the name of “vertical city”, yet few represent this important characteristic. This paper aims to propose a novel vertical city framework, or in other words, dynamic vertical urbanism, featuring constant vertical urban transformation by applying the state-of-the-art construction technologies. First, successful and unsuccessful precedents of building complexes which inspire this novel concept will be analyzed. In addition, building technologies that are crucial for the implementation of this framework will be introduced. As a result, this vertical city concept has the ability to integrate five basic elements of a city: vertical and horizontal circulation systems as its paths, a flexible building envelope as its edges, variable mix-used functional blocks as its districts, sky bridges and roof gardens as its nodes, and the complex itself as a landmark. More importantly, it can change its size, form and function with the help of construction automation technologies, open building principles, and process information modeling. it can also responsively evolve in accordance with social, economic, and environmental shifts in a self-sufficient manner, meanwhile avoiding the risk of being homogeneous with surrounding buildings. Finally, the complex will perform as a series of interconnected components which act together to form a living organism that provides various functions such as corporate, residential, commercial, academic, medical, legal, and infrastructural. In conclusion, this paper will provide researchers, architects and urban designers with a valuable example for the future vertical city developments and beyond.