Abstracts – Browse Results
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Alani, Y (2023) A semantic framework for the life cycle of water assets data exchange, Unpublished PhD Thesis, , Teesside University.
Kalian, A A A (1998) Computer aided manufacturing for prefabricated concrete buildings, Unpublished PhD Thesis, , Teesside University.
Mackenzie, D I (2010) A review of project controls in the UK and methodologies to improve the processes, Unpublished PhD Thesis, School of Science and Engineering, Teesside University.
Patacas, J (2019) A framework and common data environment for the development and management of asset information models, Unpublished PhD Thesis, , Teesside University.
Potseluyko Amobi, L (2021) Improving business and technical operations within timber frame self-build housing sector by applying integrated VR/AR and BIM technologies, Unpublished PhD Thesis, , Teesside University.
Scott, D (1997) An intelligent approach to the engineering management of housing subsidence cases, Unpublished PhD Thesis, , Teesside University.
Shah, R K (2011) Innovative methodology for location-based scheduling and visualisation of earthworks in road construction projects, Unpublished PhD Thesis, School of Science and Engineering, Teesside University.
- Type: Thesis
- Keywords: case study; communication; construction project; earthworks; experiment; productivity; scheduling; s-curves; visualisation
- ISBN/ISSN:
- URL: https://research.tees.ac.uk/en/studentTheses/c1f04221-6330-4ab4-a288-56e48b20fb2d
- Abstract:
This thesis focuses on the development of an innovative location-based scheduling methodology and a computer-based model for improving earthwork operations in road construction projects. Analysis of existing planning and scheduling practices in road construction projects conducted in the course of this research concluded that planning, scheduling and resource allocation are largely dependent on subjective decisions. Also, shortcomings exist due to the distinct characteristics of earthworks, e.g. one-off projects with uncertain site conditions and soil characteristics, causing delays and cost overruns of projects. The literature review found that existing linear scheduling methods provide inaccurate location-based information about earthworks and fail to integrate different productivity rates. A survey was used to capture and analyse industrial practices and issues related to delays and cost overruns. This analysis revealed that the accurate location-based information is vital for efficient resource planning and progress monitoring. Following these findings, a theoretical framework and specification were developed to automate location-based scheduling and visualisation of information. A prototype model was developed by integrating road design data, sectional quantities, productivity rates, unit cost, site access points, and arithmetic algorithms. The algorithms underpinning the model enable the generation of time-location plans automatically as a key output of the model. Weekly progress profiles, space congestion plans, and cost S-curves are the other outputs. A cut-fill algorithm was developed to identify optimum quantities of earthwork and its associated costs. Experiments were conducted with design data provided by a road construction company to demonstrate the model?s functionality. Sensitivity analysis was used to identify the critical factors relating to earthwork scheduling. It was found that the model is capable of generating time-location plans, considering the critical factors and location aspects. Finally, the model was evaluated using a case study and validated by road construction professionals using an indirect comparison method. It was concluded that the model is a valuable tool for producing location-based scheduling, optimising resource planning and assisting in the communication of scheduling information from the location viewpoints in the earthwork projects.
Shebob, A (2012) Development of a methodology for analysing and quantifying delay factors affecting construction projects in Libya, Unpublished PhD Thesis, School of Science and Engineering, Teesside University.