Development of a Predictive Maintenance Model to Enhance Reliability in Overhead Catenary Systems at Tanzania Railways Corporation: A Case of the Standard Gauge Railway (SGR) from Dar es Salaam to Morogoro

in overhead catenary systems at Tanzania Railways Corporation's Standard Gauge Railway from Dar es Salaam to Morogoro. The research aimed to identify factors affecting OCS reliability, formulate a mathematical predictive model, and validate its performance. A mixed-methods approach involving surveys of 60 professionals, field observations, and multiple regression analysis was employed. Data collection spanned a period of twelve months (2024-2025), encompassing operational parameters, environmental conditions, maintenance records, and system performance metrics, which were analysed using SPSS software. Relative Importance Index analysis identified seven critical factors: wire wear (RII = 0.9100), voltage deviation (RII = 0.9067), low conductivity (RII = 0.8867), support strength (RII = 0.8833), wire tension (RII = 0.8733), excess span length (RII = 0.8733), and high temperature (RII = 0.8700). Five factors showed minimal influence with RII values below 0.31. The multiple regression model achieved R = 0.99 and R² = 0.98, with 98% of the variance in OCS reliability explained by selected factors. ANOVA confirmed statistical significance (F = 13.286, p < 0.05). The predictive equation: Reliability = 0.990 - 0.071X₁ - 0.043X₂ - 0.011X₃ + 0.006X₄ + 0.009X₅ - 0.003X₆ - 0.006X₇. Model validation showed 80.4% prediction accuracy compared to 82% actual reliability, demonstrating effectiveness under both optimal (99.6% vs. 100%) and degraded conditions (44.4% vs. 44%). The model provides a framework for transitioning from reactive to proactive maintenance strategies, enabling Tanzania Railways Corporation to optimise resource allocation and enhance system reliability.

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Journal
East African Journal of Engineering
Published
2025-10-08
DOI
https://doi.org/10.37284/eaje.8.2.3780
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
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article

Development of a Predictive Maintenance Model to Enhance Reliability in Overhead Catenary Systems at Tanzania Railways Corporation: A Case of the Standard Gauge Railway (SGR) from Dar es Salaam to Morogoro

Respicius Clemence Kiiza, Jamali Hudu Katakweba
East African Journal of Engineering
Infrastructure Maintenance and Monitoring
article

Development of a Predictive Maintenance Model to Enhance Reliability in Overhead Catenary Systems at Tanzania Railways Corporation: A Case of the Standard Gauge Railway (SGR) from Dar es Salaam to Morogoro

Respicius Clemence Kiiza, Jamali Hudu Katakweba
article en

Abstract

in overhead catenary systems at Tanzania Railways Corporation's Standard Gauge Railway from Dar es Salaam to Morogoro. The research aimed to identify factors affecting OCS reliability, formulate a mathematical predictive model, and validate its performance. A mixed-methods approach involving surveys of 60 professionals, field observations, and multiple regression analysis was employed. Data collection spanned a period of twelve months (2024-2025), encompassing operational parameters, environmental conditions, maintenance records, and system performance metrics, which were analysed using SPSS software. Relative Importance Index analysis identified seven critical factors: wire wear (RII = 0.9100), voltage deviation (RII = 0.9067), low conductivity (RII = 0.8867), support strength (RII = 0.8833), wire tension (RII = 0.8733), excess span length (RII = 0.8733), and high temperature (RII = 0.8700). Five factors showed minimal influence with RII values below 0.31. The multiple regression model achieved R = 0.99 and R² = 0.98, with 98% of the variance in OCS reliability explained by selected factors. ANOVA confirmed statistical significance (F = 13.286, p < 0.05). The predictive equation: Reliability = 0.990 - 0.071X₁ - 0.043X₂ - 0.011X₃ + 0.006X₄ + 0.009X₅ - 0.003X₆ - 0.006X₇. Model validation showed 80.4% prediction accuracy compared to 82% actual reliability, demonstrating effectiveness under both optimal (99.6% vs. 100%) and degraded conditions (44.4% vs. 44%). The model provides a framework for transitioning from reactive to proactive maintenance strategies, enabling Tanzania Railways Corporation to optimise resource allocation and enhance system reliability.

East African Journal of EngineeringVol. 8(2)
Dar es Salaam Institute of Technology (TZ)
Openalex Percentile: Top 71%
Infrastructure Maintenance and Monitoring
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