Abstracts – Browse Results
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Al-Zarrad, M A (2018) Multi-criteria decision-making model to improve linear repetitive projects time-cost trade-off in uncertain environment, Unpublished PhD Thesis, , University of Alabama.
Awolusi, I G (2017) Active construction safety leading indicator data collection and evaluation, Unpublished PhD Thesis, , University of Alabama.
Chau, A D (2018) Conceptual cost estimation decision support system in university construction projects, Unpublished PhD Thesis, , University of Alabama.
Egan, C M (1989) An evaluation of the effectiveness of the Mankato State university construction management program, Unpublished PhD Thesis, , University of Alabama.
Giron Matute, W A (2018) Sustainability analysis for construction companies under the LEED code, Unpublished PhD Thesis, , University of Alabama.
Harbin, K B (2020) A decision analysis tool for building renovations regarding adaptive reuse, Unpublished PhD Thesis, , The University of Alabama.
Hatamleh, M T (2020) Enhancing the management proficiencies in developing countries: The impact of project risk management within a project management maturity model on project performance, Unpublished PhD Thesis, , University of Alabama.
Macdonald, R N (2013) A strategy for materials price risk mitigation, Unpublished PhD Thesis, , The University of Alabama.
Mejia Aguilar, G (2013) Improving accuracy of project outcome predictions, Unpublished PhD Thesis, , University of Alabama.
Nguyen, T T (2017) Modeling of clt creep behavior and real-time hybrid simulation of a clt-lifs building, Unpublished PhD Thesis, , The University of Alabama.
Ogunrinde, O (2020) Enhancing quality management in highway construction using emerging methods, Unpublished PhD Thesis, , University of Alabama.
Okpala, I U (2022) Robotics and automation in construction: Developing foundational insight and tools to support safe implementation, Unpublished PhD Thesis, , University of Alabama.
Premraj, P (2017) Assessment of project controls for shutdowns/turnarounds/outages, Unpublished PhD Thesis, , University of Alabama.
Shen, X (2017) Location-based leading indicators in BIM for construction safety, Unpublished PhD Thesis, , University of Alabama.
- Type: Thesis
- Keywords: hazards; optimization; workforce; construction site; building information model; building information modeling; communication; construction engineering; employment; feedback; regulation; safety; visualization; employee; stakeholders
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1917681642
- Abstract:
The US construction industry continues to experience a high number of injuries and fatalities in comparison to other US industrial sectors (BLS 2013). Although the U. S. construction accounts for only 4% of total employment, the industry experiences a disproportionate 19% of the total fatalities experienced by the U. S. workforce (BLS 2014). An enhanced understanding of safety leading indicators for construction sites can be an influential factor in mitigating existing hazards and predicting future hazards (Hinze et al. 2013, Hinze 2006). Although construction companies in the U. S. are required by OSHA regulation to report all fatalities, injuries, and illnesses that occur on construction sites, a more concerted effort including research and implementation is required for safety leading indicators including near miss reporting and hazard identification. This research seeks to test the hypothesis that it is feasible to collect, analyze, and disseminate safety leading indicators through location-based information and visualization. Because one of the most impactful transitions in the construction industry in the past decade has been a transition to digitized construction documents with visualization of construction processes through Building Information Modeling (BIM), BIM provides a real-time visualization and communication platform for construction stakeholders (Azhar 2011, Eastman et al. 2011). Furthermore, the construction industry is transitioning from lagging or reactive safety data collection (i.e. , injuries, illnesses and fatalities) to pro-active or leading indicator safety data collection (i.e. , near misses and hazard identification) (Hallowell et al. 2013). This research advocates for the effective retrieval, analysis, visualization and dissemination of safety leading indicator data through created databases, algorithms and BIM functionality. Since a large majority of function components in a BIM are location-based, the outcome of this research is limited to location-based safety leading indicators (i.e. , leading indicator safety data that can be assigned to a specific location). The research approach is divided into three major components: 1) near miss reporting, 2) automatic hazardous proximity zone generation, and 3) site location optimization. The framework will be evaluation in controlled laboratory settings as well as active construction sites. Throughout the research methodology, feedback and mentorship from construction engineering and management employees will be collected and integrated. This research connects the capabilities of BIM to safety data collection, storage, analysis and visualization.
Song, S (2017) Construction equipment travel path visualization and productivity evaluation, Unpublished PhD Thesis, , University of Alabama.
Stone, M L C (2013) Development of unit cost estimating models with respect to scale economies and material price volatility for use in probabilistic life cycle cost analyses, Unpublished PhD Thesis, , University of Alabama.
Thomas, W K (2013) The impact of RFP phase project scope development on the successful outcome of construction projects using the design build project delivery method, Unpublished PhD Thesis, , University of Alabama in Huntsville.
Watson, S V (2010) Pre-disaster planning for transportation infrastructure recovery, Unpublished PhD Thesis, , The University of Alabama at Birmingham.