Developing a performance-enhancing Road Maintenance Decision Support System (RMDSS) for developing countries
An important aspect of infrastructure management is an awareness of the consequences of inadequate maintenance protocols for ensuring the economic viability of the assets. In the road sector, this is of prime importance as roads underpin practically all transport related activities in every economy. A review of maintenance management of infrastructure, with particular reference to roads, exposed an inadequate level of expenditure or poor management of the road network, which often has severe implications for the economic and social well-being of a country, especially seen in Vehicle Operating Costs (VOC), accident costs, travel time costs, and associated environmental impact. The performance of road maintenance management systems can be judged by some essential indicators such as cost, safety, environmental impact and level of complaints by users.
With particular reference to the developing countries, there has been an overwhelming emphasis on the under-performance of existing road maintenance management systems. Such under-performance can be linked to the management of available assets, which often presents in the form of deferment of maintenance work and consequential accumulation of maintenance backlogs. The lack of appropriate decision support systems (DSS) adds to the problem as executives often have difficulty to reconcile several factors that influence their choice of a solution to enhance decision-making. Furthermore, the non-existence of a suitable road network database along with a lack of coordination and integration between different management levels and sections involved in the decisions exacerbates the problem. The availability of computing technology makes the option of using a data-driven computer-based solution or decision support system (DSS) a viable one for many roads maintenance executives in developing countries.
To achieve such a data-driven solution, various methods were adopted in this research, including a literature review, and a source-context questionnaire survey. The data mobilised from the survey was complemented by Bayesian Networks to accomplish a suitable DSS that responds to the sources covered by the study.
This study resulted in the development and implementation of an optimisation Road Maintenance Decision Support System (RMDSS) to enable executives in the roads sector to make more effective and efficient decisions that relate to the maintenance of road assets. Testing and validation of the RMDSS indicated great potential for making maintenance management decisions more effective and proactive when faced with budgets and other operational constraints.
- Architecture, Building and Civil Engineering
Rights holder© Jamaa S. Albotti
NotesA Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy at Loughborough University.
Supervisor(s)Francis Edum-Fotwe ; Andrew Price
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