Development of Maintenance Management Prioritisation Model to Enhance the Performance of Sewer System: A Case of Arusha Central Business District (CBD)

Abstract

The performance of sewer systems in developing urban areas faces significant challenges due to inadequate maintenance prioritisation frameworks. This study developed a comprehensive maintenance management prioritisation model to enhance the performance of sewer systems in Arusha Central Business District (CBD), Tanzania. Using a mixed-methods research design, the study assessed six sewer sections to identify critical factors affecting maintenance prioritisation through Relative Importance Index (RII) analysis. A multiple regression model was developed and validated to predict maintenance priority scores based on eight key factors: structural deterioration, traffic load impact, population served, pipe age, pipe depth, hydraulic capacity, pipe material, and pipe diameter. The regression model demonstrated strong predictive power with R² = 0.774, explaining 77.4% of the variance in maintenance priority scores (F = 23.480, p < 0.001). Among the factors, structural deterioration (β = 0.842), traffic load impact (β = 0.716), and population served (β = 0.499) emerged as the most significant predictors. Application of the model to six sewer sections in Arusha CBD ranked Soko-kuu as the highest priority (score = 6.028), followed by Kaloleni (4.964), Makao Mapya (4.464), Ngarenaro (3.531), Arusha Technical (2.182), and Bondeni (0.181). Validation testing showed excellent predictive accuracy with a Mean Absolute Error (MAE) of 0.47 and a Root Mean Squared Error (RMSE) of 0.6 on a priority score scale ranging from 0.181 to 6.028, confirming the model's reliability for maintenance prioritisation decisions. The study concludes that systematic, evidence-based maintenance prioritisation significantly improves sewer system performance and resource allocation efficiency. The developed model provides stakeholders with practical tools for proactive maintenance planning, ultimately reducing system failure risks and enhancing service delivery. These findings contribute valuable insights for sewer maintenance management in similar developing contexts and establish a framework for sustainable urban infrastructure management.