Development of Maintenance Management Model for Enhancing Availability Performance of Water Supply Intake Infrastructures
Abstract
Water intake infrastructure are important to the reliability of water services. However, their operational availability is often compromised by inadequate maintenance, especially within developing regions. This work proposes and validates a maintenance management model for improving the availability performance of water intake infrastructures, taking the case study of Moshi Urban Water Supply and Sanitation Authority, Tanzania. A mixed-methods design that combined qualitative insights from staff interviews with quantitative data on maintenance performance was used. RII analysis highlighted the key impacting factors that determine performance as: construction quality, RII = 0.916; poor intake design, RII = 0.904; and absence of a budget for preventive maintenance, RII = 0.832. Multiple regression analysis, which quantified the contributions of these factors, has determined that construction quality and the effectiveness of screening enhance availability positively, whereas poor design, infrastructure ageing, flood and inadequacies in maintenance budgets have substantial negative impacts. In this respect, the ensuing regression model has been validated to have a high average predictive accuracy of 97.64%, hence robust enough. The study concluded that shifting from the current reactive to a proactive or data-driven maintenance strategy is imperative. It recommends institutionalising preventive maintenance, integrating the model into a Computerised Maintenance Management System, and raising construction standards to significantly enhance the availability, reliability and sustainability of water supply services within Tanzania and similar contexts
Fields of Study & Subjects
Reliability and Maintenance Optimization
Water Systems and Optimization
Power System Reliability and Maintenance
Publication details
- Journal / source
- East African Journal of Engineering
- Volume
- 9
- Issue
- 1
- Pages
- 143–157
- Publication date
- 16 February 2026
- Language
- EN