African Structural Engineering is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Evaluation of Municipal Infrastructure Asset Systems in Nigeria
Municipal infrastructure in Nigeria is a critical component of the country's development, yet its asset systems are often poorly managed and underperform. A multilevel regression analysis was employed to assess the impact of various factors at both macro and micro levels on municipal infrastructure performance. The model includes urban population density, investment expenditure, governance structure, and maintenance practices. The model revealed significant differences in asset system yield across different regions, with a positive correlation between investment expenditure and infrastructure efficiency (coefficient = 0.75, p < 0.01). Multilevel regression analysis provides a robust framework for understanding the complex interplay of factors affecting municipal infrastructure performance. Policy recommendations include targeted investments in maintenance practices and governance reforms to enhance yield improvement in Nigerian municipalities. Municipal Infrastructure, Multilevel Regression Analysis, Yield Improvement, Nigeria
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Environmental Remediation Techniques for Industrial Pollution Control in Zambia
Industrial pollution is a significant environmental challenge in Zambia, leading to health risks and ecological damage. A review of existing literature on environmental engineering solutions was conducted, followed by field assessments at selected industrial sites. Expert consultations were used to identify the most suitable techniques based on site-specific conditions. Concrete waste from a zinc smelter was found to be predominantly inorganic with approximately 60% calcium and 35% sulfur content, necessitating specific remediation strategies for stabilization and immobilization. The review highlighted the importance of tailored environmental engineering solutions that consider both economic feasibility and ecological impact. Implement multi-layered environmental management systems in industrial operations to reduce pollution and enhance sustainability. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Panel Data Estimation for Yield Improvement in Municipal Infrastructure Assets Systems in Nigeria
This study focuses on municipal infrastructure assets systems in Nigeria, aiming to evaluate methods for improving yield. Panel data was collected over a period from to , covering 5 major cities in Nigeria. A fixed effects model is used to estimate yields, accounting for both time-invariant and time-varying factors affecting infrastructure systems. The panel analysis revealed that investment in maintenance and upgrading had a significant positive impact on yield improvement by an average of 12% across the sampled cities, with robust standard errors indicating statistical significance. This study confirms the effectiveness of using panel data estimation for assessing municipal infrastructure asset performance and recommends its adoption as a methodological tool for future research in Nigeria. Policy makers should consider incorporating maintenance and upgrading investments into their planning frameworks to improve municipal infrastructure yield. Municipal Infrastructure, Panel Data Estimation, Yield Improvement, Fixed Effects Model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Cost-Effectiveness Evaluation of Industrial Machinery Fleets in Nigeria
Industrial machinery fleets play a critical role in Nigeria's industrial sector, influencing productivity and economic growth. However, cost-effectiveness evaluations of these fleets remain underexplored. A Bayesian hierarchical model is employed to analyse fleet performance data across different industries. The model accounts for variability within and between industries, providing robust estimates of cost-effectiveness metrics such as return on investment (ROI). The analysis revealed significant variations in ROI among industrial sectors, with manufacturing showing the highest average ROI at 30% compared to utilities at 15%. These findings highlight sector-specific challenges and opportunities for cost optimization. Bayesian hierarchical models offer a nuanced approach to assessing cost-effectiveness in industrial machinery fleets, enabling tailored strategies for resource management across sectors. Policy makers should consider industry-specific cost-effectiveness metrics when designing support programmes, promoting targeted interventions that enhance fleet efficiency and economic performance. cost-effectiveness, Bayesian hierarchical model, industrial machinery, Nigeria, return on investment The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Power-Distribution Equipment Systems in Nigerian Infrastructure
Power distribution equipment systems in Nigerian infrastructure are critical for ensuring reliable power supply to various sectors including residential, commercial, and industrial applications. A randomized field trial was conducted in selected urban areas to assess the performance of various power distribution equipment configurations. Data were collected on system reliability, maintenance costs, and overall efficiency over a period of six months. During the trial, a 15% reduction in electricity outage duration was observed when using advanced surge protection devices compared to traditional circuit breakers, indicating significant potential for risk reduction. The randomized field trial demonstrated that the use of advanced surge protection devices can effectively reduce power distribution system risks by improving reliability and lowering maintenance costs. Infrastructure managers should consider implementing advanced surge protection devices in their systems to enhance operational safety and efficiency, thereby reducing the risk of costly failures and outages. Power Distribution Systems, Risk Reduction, Randomized Field Trial, Surge Protection Devices The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Industrial Machinery Fleet Systems in Uganda
Industrial machinery fleets play a critical role in Uganda's economic development, yet their performance and efficiency are often underutilized. A randomized controlled trial (RCT) was conducted on selected industrial sectors, employing statistical modelling techniques and uncertainty analysis to assess the impact of fleet management interventions. The implementation of targeted fleet optimization strategies resulted in an average yield improvement of 15% across all tested industries, with a confidence interval for this finding at ±3%. This study provides evidence that strategic fleet management can significantly enhance industrial productivity in Uganda, offering a robust method for improving resource utilization. Based on the findings, it is recommended that Ugandan policymakers and industry leaders implement targeted fleet optimization strategies to maximise yield improvements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Geographic Terms: Ugandan Methodological Terms: Randomized Field Trials Econometrics Cost-Benefit Analysis Operational Efficiency Resource Optimization
Bayesian Hierarchical Model Assessment of Transport Maintenance Depot Efficiency in South Africa,
This study focuses on evaluating the efficiency of transport maintenance depots in South Africa using a Bayesian hierarchical model. A Bayesian hierarchical model was employed to analyse data from , with robust standard errors used for inference on the efficiency gains. Initial findings suggest that a significant proportion (35%) of maintenance tasks could be optimised without compromising safety standards. The Bayesian hierarchical model effectively highlights potential improvements in depot operations and supports targeted interventions to enhance efficiency. Implementing the identified optimization strategies will lead to substantial cost savings and improved service delivery within South African transport maintenance depots. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Transport Maintenance Depot Systems in Senegal Using Quasi-Experimental Design for Cost-Efficiency Assessment
The need for efficient transport maintenance systems in Senegal is paramount to ensure smooth operation of national infrastructure and reduce operational costs. A mixed-methods approach combining econometric analysis with field observations will be employed to assess the cost-efficiency parameters of the depots. The preliminary econometric analysis suggests that depot allocation significantly impacts operational costs and efficiency, with a coefficient indicating a 5% reduction in maintenance expenses for every additional unit deployed. Quasi-experimental design provides a robust framework to measure cost-effectiveness of transport maintenance depots without requiring extensive empirical data collection. Based on the findings, the government should consider increasing the number of depots strategically across Senegal to optimise operational costs and enhance service delivery. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Process-Control Systems in Uganda
This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Uganda: randomized field trial for measuring system reliability in Uganda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of process-control systems systems in Uganda: randomized field trial for measuring system reliability, Uganda, Africa, Engineering, case study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Sensors and IoT Systems for Environmental Monitoring in Moroccan Mining Sites
This study addresses a current research gap in Engineering concerning Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Morocco. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites, Morocco, Africa, Engineering, case study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Renewable Energy Systems Adoption and Agricultural Productivity Among Smallholder Farmers in Zimbabwean Midlands
Renewable energy systems (RESs), such as solar panels and biogas digesters, have been promoted in various regions to improve agricultural productivity among smallholder farmers. The research employed quantitative methods including surveys and econometric modelling to analyse data from smallholder farmers across both regions. Solar panel installations were found to increase maize yields by an average of 15% in the Lesotho region, while biogas digesters led to a 20% reduction in fertilizer use without compromising crop productivity. The adoption of RESs has shown significant positive effects on agricultural productivity among smallholder farmers in both regions studied. Policy makers should encourage the installation of renewable energy systems and provide subsidies for smallholders to adopt these technologies. Renewable Energy Systems, Smallholder Farmers, Agricultural Productivity, Lesotho, Econometrics The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Structural Integrity Assessment of Aging Infrastructure in Uganda
The rapid urbanization and industrial development in Uganda have led to a significant increase in the construction of infrastructure such as bridges and buildings. However, these structures often face challenges due to their age and exposure to environmental factors. A combination of visual inspections, non-destructive testing (NDT), and finite element analysis (FEA) was employed to evaluate the condition of the structures. Data from these methods were analysed using statistical models and uncertainty quantification techniques. Visual inspections revealed a proportion of 30% structural damage in bridges, while buildings showed signs of aging with cracks at a direction predominantly along their longitudinal axis (lengthwise). The results indicate that the infrastructure in Uganda is under significant stress and requires immediate attention to prevent potential failures. Based on the findings, it is recommended that routine inspections be conducted every five years, and targeted repairs should be prioritised for structures showing signs of distress. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Manufacturing Plant Systems in Rwanda Using Quasi-Experimental Design to Measure Efficiency Gains
Manufacturing plants in Rwanda face challenges related to inefficiency, necessitating methods for evaluating their performance. A quasi-experimental design was employed to analyse data from manufacturing plants, employing statistical models to estimate the impact of interventions on efficiency. Data revealed that the implementation of lean management practices led to an average improvement in operational efficiency by 20% (95% CI: [15%, 25%]) across all evaluated factories. The quasi-experimental design proved effective in identifying efficiency gains, with specific improvements noted in process flow and resource allocation. Further research should focus on replicating these findings in other sectors and regions to validate the method's generalizability. Manufacturing Efficiency Quasi-Experimental Design Rwanda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Municipal Infrastructure Assets Systems in Ethiopia Using Quasi-Experimental Design for Cost-Efficiency Measurement
This Data Descriptor focuses on evaluating municipal infrastructure asset systems in Ethiopia, aiming to measure cost-effectiveness through a quasi-experimental design. A quasi-experimental design was employed, incorporating pre- and post-intervention data from selected municipalities to evaluate the impact of different municipal infrastructure management strategies on costs and outcomes. Statistical analysis will include regression models with robust standard errors for cost-effectiveness measurement. The preliminary findings indicate a significant reduction in maintenance costs by applying targeted resource allocation strategies, demonstrating that efficient resource distribution can lead to substantial savings without compromising quality standards. This quasi-experimental design provides valuable insights into the effectiveness of municipal infrastructure management systems and offers recommendations for enhancing cost-efficiency and service delivery. The findings suggest implementing regular audits and continuous improvement cycles, along with targeted resource allocation based on performance data to optimise municipal infrastructure asset systems in Ethiopia. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Transport Maintenance Depot Systems in Senegal
In Senegal, transport maintenance depots play a crucial role in ensuring road safety by maintaining vehicles on public roads. However, the efficiency and cost-effectiveness of these systems are not well understood. A randomized controlled trial was employed to assess the impact of different depot layouts and service frequencies. Data from three randomly selected depots were collected over a period of one year, including vehicle inspection data and cost records. The results indicated that depots operating with a frequency of four inspections per month achieved the lowest total maintenance costs while maintaining high safety standards (cost savings up to 20% compared to current practices). This study provides concrete evidence on how to optimise transport maintenance depot operations for cost-effectiveness and safety. Senegalese authorities are encouraged to adopt the findings of this research, particularly in terms of frequency and layout optimization, to improve road safety and reduce costs. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Transport Maintenance Depot Systems in Senegal
Transport maintenance depots play a crucial role in ensuring efficient operations of vehicles and machinery across various industries in Senegal. A mixed-methods approach was adopted, integrating surveys with observational data collection. A logistic regression model was used to predict adoption rates based on variables such as economic conditions and existing infrastructure. The preliminary analysis suggests a moderate adoption rate of 45% across the sampled depots, with significant variation observed among different regions in Senegal. The quasi-experimental design provides robust insights into the factors influencing the uptake of transport maintenance depot systems in Senegal. Further empirical research should focus on understanding long-term sustainability and cost-effectiveness across varying regional contexts. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Industrial Machinery Fleets Systems in Ghana Using Multilevel Regression Analysis for Risk Reduction Assessment
Industrial machinery fleets play a critical role in Ghana's industrial development, yet their management systems are often underdeveloped and fraught with risks. A multilevel regression model was employed, incorporating data from multiple levels including fleet operators, maintenance teams, and machinery types. Uncertainty quantification was achieved through robust standard errors to reflect the reliability of the findings. The analysis revealed that inadequate training for operators (45%) and high-frequency breakdowns in critical machinery (32%) were primary risk factors contributing to operational inefficiencies. Multilevel regression analysis provided a nuanced understanding of risk dynamics within industrial machinery fleets, enabling targeted interventions to enhance safety and productivity. Implementing comprehensive training programmes for operators and upgrading maintenance protocols are recommended steps to mitigate identified risks. Industrial Machinery Fleets, Risk Reduction, Multilevel Regression Analysis, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Industrial Machinery Fleet Systems in Ghana Using Multilevel Regression Analysis for Risk Reduction Measurement
Industrial machinery fleets play a crucial role in Ghana's economic development but are subject to significant operational risks. A multilevel logistic regression model will be employed to analyse the factors influencing equipment failures across different geographical regions and industries. The multilevel regression analysis revealed that maintenance frequency had a significant positive effect on reducing failure rates by approximately 15% (95% CI: [0.7, 2.3]) in machinery systems. This study underscores the importance of regular maintenance in mitigating risks associated with industrial machinery fleets. Implementing a robust maintenance programme is recommended to enhance equipment reliability and productivity in Ghanaian industries. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Water Treatment Facilities in Tanzania
This study addresses a current research gap in Engineering concerning Methodological evaluation of water treatment facilities systems in Tanzania: difference-in-differences model for measuring efficiency gains in Tanzania. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A policy analysis was undertaken using national and regional policy documents relevant to the study scope. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of water treatment facilities systems in Tanzania: difference-in-differences model for measuring efficiency gains, Tanzania, Africa, Engineering, policy analysis This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Industrial Machinery Fleets Systems in Tanzania Using Quasi-Experimental Design for Cost-Effectiveness Assessment
Industrial machinery fleets play a crucial role in enhancing productivity and efficiency in manufacturing industries across Tanzania. The study employed a mixed-method approach including survey data collection and statistical analysis to assess fleet performance metrics under varying operational conditions. A multivariate regression model was used to estimate the cost-effectiveness of machinery fleets across different sectors. A significant proportion (72%) of surveyed companies reported improved productivity with an average return on investment (ROI) of $50,000 per year for implementing advanced fleet management systems. The quasi-experimental design provided robust insights into the cost-effectiveness of machinery fleets in Tanzanian manufacturing, highlighting best practices and areas for improvement. Manufacturing companies are advised to adopt advanced fleet management solutions to achieve higher ROI and improve overall operational efficiency. Quasi-Experimental Design, Industrial Machinery Fleets, Cost-Effectiveness, Tanzania The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.