Bing Qi

Mr. Bing Qi

School of Building Construction, University of Florida, Gainesville, FL, USA

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
30 April 2020 in Buildings
Verified
Journal Article
Open access
PDF file
Bing QiBing Qi
Bing Qi
MRMohamad Razkenari
Mohamad Razkenari
JLJiaxuan Li
Jiaxuan Li
Aaron CostinAaron Costin
Aaron Costin
CKCharles Kibert
Charles Kibert
SQShuyu Qian
Shuyu Qian
In recent years, a growing amount of research has focused on improving the performance of industrialized construction using emerging technologies. It is still necessary to have an in-depth understanding of the industry practitioners’ perspectives on the application of emerging technologies. Thus, a well-designed survey was distributed to industry practitioners who have been involved in industrialized construction projects. Then, a set of data analysis methods were utilized on the collected data to address the proposed four specific research questions. Results indicate that 3D and nD models, sensing techniques, and business information models are the technologies with the highest current utilization level. Extended reality, additive manufacturing, and advanced data analytics are the technologies with the highest development potential. Project inputs (e.g., cost, time, and labor), as well as implementation cost and software constraints (e.g., capital costs, software upgrading, and compatibility), are the main factors that affect practitioners’ decisions to adopt emerging technologies in industrialized projects. Inter-group comparison results indicate that company background has little significant influence on practitioners’ perspectives, while personal career profiles can significantly affect practitioners’ perspectives. Significantly, by uncovering the suggestions and viewpoints of practitioners, this paper aligns academic research with industry needs, ultimately providing guidance on future research directions and applications.

1 February 2023 in Buildings
Verified
Journal Article
Open access
PDF file
Bing QiBing Qi
Bing Qi
Aaron CostinAaron Costin
Aaron Costin
The integration of Design for Manufacture and Assembly (DfMA) into the design process of industrialized construction has the potential to reduce errors and changes occurring after the design has been finalized, ultimately improving overall productivity. Based on DfMA, the designers would need to consider whether their designs meet the architectural and performance requirements, as well as the manufacturing and assembly requirements from assembly and manufacturing technicians. However, some limitations present challenges for DfMA-oriented prefabricated design, such as lack of information interoperability, lack of conflict detection and management, and inefficient data processing and requirement checking. Thus, this research presents a novel BIM and ontology-based framework for DfMA of prefabricated and modular components. Various types of algorithms, plugins, and programming are also integrated to support the operation of the framework. The primary functions of this framework include: (1) collection of various stakeholder requirements in a standardized data format; (2) conflict detection and resolution between the design, manufacturing, and assembly requirements; and (3) automated compliance checking of whether the designed BIM models meet DfMA requirements. This research applies the framework on a prefabricated hotel project as a case study to validate the feasibility of the framework. Based on the results of a user experience survey, the developed framework shows promise for improving the DfMA process and stakeholder communication. Although a few limitations were encountered, such as the low computer operating speed and the limited ontology, the framework has been validated and shows great potential in advancing prefabricated component design applications

29 March 2018
Verified
Conference Paper
Closed access
Bing QiBing Qi
Bing Qi
Ke ChenKe Chen
Ke Chen
Aaron CostinAaron Costin
Aaron Costin
Prefabricated buildings have been shown to provide a new way of sustainable construction to reduce the amount of work on construction sites, reduce pollution, shorten construction time, and increase safety. However, many issues in the actual production process (e.g., quality check, storage, and installation of the prefabricated components) are mainly caused by the lack of the information being collected and shared. In order to better monitor and manage the prefabrication process efficiently, this research proposes a framework that integrates radio frequency identification (RFID) and building information modeling (BIM) technologies. The scope of this paper is the discussion of the framework and its application for prefabricated housing production. A preliminary study focused on the manufacturing process of integrating RFID tags with the prefabrication of the components. About 200 reinforced concrete components were embedded with a passive RFID tag. Results of the experiments showed a 90% reduction of signal strength when passive RFID tags are embedded in concrete, with less than a 1.5% fail rate. Current RFID tag implanting techniques still need to be improved to meet the actual demands of the construction industry and increase the signal strength. Significantly, this research shows promising results that the framework could establish a high efficient, low cost, and easily implementable information capturing and sharing system for further planning and management of prefabrication.

24 July 2020 in Algorithms
Verified
Journal Article
Open access
PDF file
Bing QiBing Qi
Bing Qi
SQShuyu Qian
Shuyu Qian
Aaron CostinAaron Costin
Aaron Costin
Considering the increasing use of emerging technologies in industrialized construction in recent years, the primary objective of this article is to develop and validate predictive models to predict the emerging technology utilization level of industrialized construction industry practitioners. Our preliminary research results indicate that the company background and personal career profiles can significantly affect practitioners’ technology utilization level. Thus, our prediction model is based on four variables: company size, company type, working experience, and working position. The United States and China are selected as the case studies to validate the prediction model. First, a well-designed questionnaire survey is distributed to the industrialized construction industry practitioners from the two countries, which leads to 81 and 99 valid responses separately. Then, ordinal logistic regression is used to develop a set of models to predict the practitioners’ utilization level of the four main technology types. Finally, the external test dataset consisting of 16 cases indicates the prediction models have a high accuracy. The results also reflect some differences of the technology utilization status in the industrialized construction industry between the United States and China. The major contribution of this research is offering an efficient and accurate method to predict practitioners’ technology utilization level in industrialized construction. Significantly, the models are believed to have a wide application in promoting the emerging technologies in the actual industrialized construction.