Development of Maintenance Management Model for Improving Scanner Availability Performance at Tanzania Ports Authority: A Case of Dar es Salaam Port

This study aimed to identify the most critical factors affecting scanner availability and develop a robust model to enhance operational performance. Data were systematically collected from 50 scanner maintenance and operation records at the Tanzania Ports Authority. SPSS software was used to analyse the data through multiple regression and ranking techniques to ensure accuracy and reliability. A detailed Relative Importance Index (RII) analysis revealed that Preventive Maintenance Compliance was the most influential factor (RII = 0.932; 93.2%), followed closely by Environmental Factors (dust, humidity, and temperature) and Software/Control System Reliability (both RII = 0.920; 92.0%). Other highly ranked factors included Detector Module Degradation (RII = 0.904), Modulator Performance/High Voltage Stability, Spare Parts Availability and Quality (both RII = 0.900), and Conveyor System/Mechanical Component Wear (RII = 0.896). Conversely, factors such as X-Ray Head Component Failures, Water Cabin Cooling System Effectiveness, and Sensor Calibration Drift were found to have lower impacts, with RII values below 35%. The developed regression model demonstrated excellent statistical performance, with an R-squared of 0.980 indicating a strong positive correlation between the identified factors and scanner availability. The model explains 96% of the variance in scanner availability (R² = 0.960) and remains robust when adjusted for the number of predictors (Adjusted R² = 0.954). A low standard error (2.847) and a high F-statistic (159.42) further confirm the model’s reliability and significance. In conclusion, this research provides a data-driven maintenance management model tailored to the operational context of the Tanzania Ports Authority. The Authority can significantly reduce scanner downtime and enhance equipment availability by prioritising critical factors such as preventive maintenance compliance and environmental control. These findings provide practical guidance for maintenance managers and policymakers seeking to implement targeted strategies that ensure continuous and reliable scanning operations.