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Development of Maintenance Management Model for Enhancing the Maintainability Performance of Irrigation Scheme Infrastructure: A Case Study in Iringa District Council

Emmanuel Simon,Antony Thomas

2025 · DOI: 10.37284/eaje.8.1.3626
East African Journal of Engineering · 0 Citations

Abstract

Maintenance management is critical to the sustainability and performance of irrigation infrastructure, especially in developing countries where resource constraints significantly impact agricultural productivity and food security. This study developed a maintenance management model to enhance the maintainability performance of irrigation scheme infrastructure in Iringa District Council, Tanzania. Using a mixed-methods research design, data were collected through field analyses, stakeholder interviews, and review of current maintenance practices from 90 respondents across five irrigation schemes. The study identified twelve maintenance factors using the Relative Importance Index (RII) analysis, revealing a clear dichotomy between highly important operational factors and less critical technical factors. The top-ranked factors were Regular Preventive Maintenance Scheduling (94.2%), Training and Capacity Building Programs (93.3%), Spare Parts and Equipment Availability (92.4%), Environmental Factors Management (92.0%), Stakeholder Coordination and Communication (91.6%), and Adequate Maintenance Budget Allocation (91.1%). Conversely, technical factors such as Maintenance Documentation (30.0%), Quality of Construction Materials (29.8%), and Availability of Skilled Personnel (29.1%) received significantly lower ratings. A multiple regression model was developed explaining 76% of the variance in maintenance performance (R² = 0.76, R = 0.87). The model equation: Maintenance Performance = 0.04 + 0.02(Scheduling) + 0.04(Spare Parts) + 0.02(Training) + 0.03(Environmental) + 0.02(Stakeholder) + 0.02(Budget) + 0.01(Technology), demonstrated high statistical significance (F = 485.76, p < 0.001). Validation testing across different implementation scenarios showed performance ranges from 20% (Very Low) to 84% (Very Severe), confirming the model's discriminatory capability and practical utility. The findings suggest that a contextualised maintenance management model combining preventive maintenance strategies, stakeholder involvement, and capacity building mechanisms can significantly enhance infrastructure reliability, minimise system downtime, and ensure sustainability. The study concludes that organisational excellence, systematic approaches, adequate resource allocation, and effective stakeholder partnerships are the primary predictors of maintenance effectiveness in irrigation infrastructure management.