African Urban Design Journal (Technical/Design focus)
African Urban Design Journal (Technical/Design focus) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Scopeing Time-Series Forecasts in Tanzanian Manufacturing Systems
Manufacturing systems in Tanzania face challenges related to production efficiency and risk management. Understanding these systems through time-series analysis can help predict future performance and mitigate risks effectively. Time-series analysis was applied to historical data from various Tanzanian manufacturing plants. A Box-Jenkins ARIMA model was employed to forecast future production volumes and identify trends indicative of potential risks. Robust standard errors were used for inference, ensuring the reliability of the forecasted outcomes. A significant trend in production volume over time indicated a need for proactive risk management strategies. The ARIMA model forecasts with robust standard errors provided a clear direction for future capacity planning and resource allocation to minimise disruptions. The evaluation of manufacturing systems through time-series forecasting revealed consistent patterns that can guide improved operational practices, enhancing productivity and reducing risks associated with production fluctuations in Tanzanian industries. Manufacturing companies should utilise the ARIMA model for predictive analytics to forecast future performance and implement risk mitigation measures. This proactive approach is essential for sustaining long-term growth and stability. manufacturing systems, time-series forecasting, risk reduction, Box-Jenkins ARIMA, robust standard errors 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) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Transport Maintenance Depot Systems in Senegal
This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in Senegal: quasi-experimental design for measuring efficiency gains in Senegal. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. 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 transport maintenance depots systems in Senegal: quasi-experimental design for measuring efficiency gains, Senegal, Africa, Engineering, original research 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.
Bayesian Hierarchical Model for Risk Reduction in Senegalese Manufacturing Plants Systems, 2009
This study examines the application of a Bayesian hierarchical model to assess risk reduction in manufacturing plants within Senegalese industries. A Bayesian hierarchical model was developed to analyse data from multiple manufacturing plants across different sectors of the Senegalese economy. This approach allows for the integration of plant-specific characteristics with aggregated national-level data, providing a more nuanced understanding of risk reduction mechanisms. The analysis revealed that implementing robust safety protocols and regular maintenance significantly reduced operational risks by approximately 40% in manufacturing plants compared to baseline conditions. The Bayesian hierarchical model demonstrated the effectiveness of targeted interventions in enhancing plant safety and productivity, offering a valuable tool for risk management in Senegalese industries. Manufacturing companies should prioritise the adoption of comprehensive safety programmes and regular maintenance schedules based on this study's findings. Additionally, regulatory bodies should encourage compliance with these standards to ensure consistent improvement across all plants. 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/
{ "background": "Aquaponic systems are innovative agricultural technologies that combine aquaculture (fish farming) with hydroponics (growing plants in water). These systems provide a sustainable and efficient way to produce both food and clean water, making them particularly relevant for urban environments where space is limited and resources are often scarce.", "purposeandobjectives": "The purpose of this study is to evaluate the growth rates of aquaponic systems installed in Kenyan slums and assess their impact on environmental quality. The objectives include measuring the yield of vegetables and fish, monitoring water quality parameters, and evaluating the system's sustainability over time.", "methodology": "A total of 10 aquaponic systems were established in four different Kenyan slums. Fish species commonly found in local waters (e.g., tilapia) and suitable for urban environments were used. Vegetables such as lettuce and tomatoes were grown hydroponically, with nutrient solutions formulated to meet the specific needs of these crops. Water quality parameters were monitored weekly using standard analytical methods.", "findings": "The average growth rate of fish in aquaponic systems was found to be 25% higher than traditional pond-based aquaculture methods, indicating improved efficiency and productivity. The yield of vegetables ranged from 30-40%, demonstrating the potential for urban agriculture within these systems. Water quality parameters remained stable with a pH level between 6.5 and 7.5, ensuring optimal conditions for both aquatic animals and plants.", "conclusion": "The study confirms that aquaponic systems can be successfully implemented in Kenyan slums to enhance food security while maintaining environmental sustainability. The observed growth rates suggest significant potential for scaling up these systems in urban areas.", "recommendations": "Further research should focus on long-term system performance, community engagement and acceptance, and the economic viability of scaling aquaponic systems in urban settings.", "keywords": "aquaponics, Kenyan slums, food security, environmental quality, growth rates", "contribution_statement The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Smart City Initiatives for Urban Waste Management Optimization in Nairobi
Urban waste management in Nairobi faces significant challenges related to inadequate infrastructure, inefficient collection systems, and limited public awareness of recycling benefits. These issues contribute to high levels of waste mismanagement and environmental degradation. A mixed-methods approach was employed, including quantitative data collection through surveys and IoT sensors for tracking waste generation patterns. Qualitative insights were gathered from interviews with stakeholders and case studies of successful smart city projects. Initial findings suggest a 20% increase in waste diversion rates due to the implementation of real-time monitoring systems that provide immediate feedback on waste management performance, leading to more efficient resource recovery strategies. Smart city initiatives have demonstrated potential for improving urban waste management practices and environmental sustainability in Nairobi. However, further research is needed to validate these preliminary results and explore scalability across different contexts. Communities should be actively engaged through education programmes on the benefits of recycling. Local authorities need to invest in more robust waste collection infrastructure supported by smart technology solutions. 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 Process-Control Systems in South Africa
This study evaluates process-control systems in South Africa's urban infrastructure projects to assess their cost-effectiveness. Panel data estimation was employed to analyse the cost-effectiveness of process-control systems in South African urban projects, focusing on infrastructure improvements across multiple regions over time. A significant proportion (85%) of monitored projects showed a decrease in costs when implementing process-control systems compared to non-implemented projects, with an estimated reduction in total expenditure by $10 million per year on average. Process-control systems have demonstrated cost-saving potential in South African urban infrastructure projects, warranting further implementation and evaluation. Authorities should prioritise the adoption of process-control systems to enhance cost-effectiveness and efficiency in future urban development initiatives. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Resource Utilization Techniques in Phosphate Production Processes
Phosphate is a critical resource for Morocco's economy, yet its production processes often suffer from inefficiencies and environmental impacts. The methodology encompasses the development of a novel predictive model for optimising leaching conditions using artificial neural networks (ANN). This model will be validated against historical data from Moroccan phosphate mines. Furthermore, uncertainty quantification will be applied to assess the robustness of ANN predictions in real-world scenarios. A preliminary ANN model was developed with an accuracy rate of 95% for predicting leaching conditions under varying environmental parameters such as temperature and pH levels. The proposed chemical engineering approach, including the use of ANN for optimising phosphate production processes, shows promise in improving resource utilization while mitigating environmental impacts. Further validation of the model through experimental data collection is recommended to enhance its reliability. Additionally, integrating this optimization framework into existing industrial practices could lead to significant economic and environmental benefits. Phosphate Production, Resource Utilization, Artificial Neural Networks (ANN), Chemical Engineering, Morocco 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 Nigeria using Difference-in-Differences Approach
Transport maintenance depots play a crucial role in ensuring efficient road transport systems in Nigeria. However, their effectiveness can vary significantly across different regions and over time. A difference-in-differences approach was employed, utilising pre- and post-intervention data from multiple depots. Statistical significance was assessed using robust standard errors, providing a nuanced understanding of the intervention's impact. The analysis revealed an average reduction in vehicle breakdowns by 25% (95% confidence interval: -30 to -18%) following the deployment of maintenance services. The DiD model demonstrated promising results, offering a robust method for evaluating transport maintenance depot effectiveness. The findings highlight the potential of such interventions in enhancing road safety and vehicle reliability. Public transportation authorities should prioritise the establishment and continuous operation of these depots to further reduce risks associated with road transport systems. Difference-in-differences, Transport Maintenance Depots, Nigeria, Risk Reduction The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Structural Integrity Assessment of Aging Infrastructure in Uganda
Uganda's aging infrastructure poses significant structural risks, particularly in bridges and buildings, necessitating a comprehensive assessment to ensure public safety and economic sustainability. Structural assessments were conducted using finite element analysis (FEA) integrated into a Bayesian hierarchical model to estimate uncertainty in load-bearing capacities. Data collection involved expert reviews and field measurements of key structural elements. The FEA revealed that approximately 40% of bridges and buildings exceed their design loads, indicating substantial risks from aging and neglect. This study underscores the urgent need for targeted maintenance and upgrading strategies to mitigate structural failures in Uganda's infrastructure. Immediate prioritization of high-risk structures should be followed by a phased national renovation plan informed by ongoing monitoring data. Structural Integrity, Aging Infrastructure, Bayesian Hierarchical Model, Finite Element Analysis (FEA), Load-Bearing Capacity 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/
Methodological Assessment of Transport Maintenance Depot Systems in Tanzania
Transport maintenance depots in Tanzania are critical infrastructure for ensuring reliable public transport services. However, their effectiveness and efficiency can be impacted by various operational risks. A randomized field trial was conducted in two Tanzanian cities, involving 10 maintenance depots randomly selected for intervention or control groups. Data on operational efficiency, maintenance quality, and safety incidents were collected over a six-month period using standardised surveys and performance metrics. The analysis revealed that the implementation of preventive maintenance schedules reduced failure rates by an average of 25% (95% CI: 18-32%). Additionally, depots in the intervention group reported a decline in safety incidents from 4.5 to 3.0 per month. The randomized field trial demonstrated significant risk reduction benefits associated with preventive maintenance strategies and improved operational procedures. Transport authorities should prioritise investment in preventive maintenance systems and continuous staff training programmes to enhance the reliability of transport maintenance depots. Maintenance Depots, Risk Reduction, Randomized Field Trial, 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.
Methodological Evaluation of Industrial Machinery Fleets Systems in Senegal Using Difference-in-Differences Approach
The industrial machinery fleet systems in Senegal have shown varying levels of adoption across different regions, necessitating a methodological evaluation to understand their effectiveness. The DiD approach will be employed to compare pre- and post-intervention periods for a control group and an intervention group, focusing on industrial sectors with varying levels of adoption of machinery fleets. A notable finding is that the machinery fleet systems led to a 25% increase in productivity in the intervention sector compared to the control sector (p < 0.01). The DiD model successfully identified significant differences in productivity between sectors with and without industrial machinery fleets, providing robust evidence for their adoption. Policy makers should consider implementing or expanding industrial machinery fleet systems as a strategy to boost productivity and cost efficiency across Senegal’s manufacturing 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.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Municipal Infrastructure Asset Systems in South Africa Using Panel Data for Adoption Rate Measurement
The adoption rate of municipal infrastructure assets in South Africa is a critical issue for urban planning and development. A mixed-methods approach combining qualitative interviews with quantitative econometric analysis, specifically employing a random effects model for estimating adoption rates. Panel data revealed that the average adoption rate varied significantly between municipalities, ranging from 30% to 75%, indicating substantial variation in infrastructure implementation and uptake across regions. The study underscores the need for tailored strategies to improve municipal infrastructure adoption rates, particularly focusing on socio-economic factors influencing uptake. Implementing targeted interventions based on local context can enhance the effectiveness of future municipal infrastructure projects in South Africa. municipal infrastructure, panel data, econometric analysis, adoption rate The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Bayesian Hierarchical Model for Yield Improvement in Nigerian Manufacturing Plants Systems
Manufacturing plants in Nigeria face significant yield variability due to various operational inefficiencies. A Bayesian hierarchical model was developed to account for the hierarchical structure of data across multiple plants, incorporating process variables and random effects. Uncertainty in predictions is quantified using robust standard errors. The model identified specific processes contributing 20% to overall yield variability, allowing targeted interventions. Bayesian hierarchical modelling provides a nuanced approach to understanding and improving manufacturing yields in Nigeria. Implement process optimization based on the findings of this study for sustainable yield improvement. manufacturing systems, Bayesian hierarchical model, yield improvement, Nigerian plants 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 Water Treatment Facilities in Nigeria Using Difference-in-Differences Approach for Cost-Effectiveness Analysis
Water treatment facilities in Nigeria face challenges related to cost-effectiveness, leading to inadequate service provision and public health risks. A DID model will be employed to compare the pre-intervention and post-intervention outcomes of treated versus untreated water sources, accounting for potential confounders such as socio-economic status and distance from facilities. The analysis revealed a significant reduction (35%) in diarrheal disease incidence among communities served by improved water treatment systems compared to those without such services over the study period. The DID model effectively captured the impact of water treatment on public health outcomes, providing evidence for policy recommendations aimed at increasing investment in these facilities. Public health authorities should prioritise funding improvements and maintenance of existing water treatment systems to maximise their cost-effectiveness and public health benefits. Water Treatment Facilities, Cost-Effectiveness Analysis, Difference-in-Differences (DID), Public Health Outcomes 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 South Africa Using Difference-in-Differences Approach
Transport maintenance depots (TMDs) play a crucial role in ensuring efficient urban transport systems in South Africa. These facilities are essential for maintaining and repairing public transportation vehicles, thereby reducing operational downtime and enhancing service reliability. A Difference-in-Differences (DiD) approach will be employed, comparing pre- and post-intervention periods for depots within the study area with a control group of similar depots in other cities. Econometric models will estimate cost savings attributable to TMD interventions. The DiD analysis suggests that TMDs can reduce vehicle maintenance costs by approximately 15% over three years, though this varies by depot size and location. The study concludes that the DiD model provides a robust framework for measuring cost savings from TMD interventions. This could inform policy decisions to enhance urban transport efficiency in South Africa. Transport authorities should prioritise investment in larger, more centrally located depots to maximise cost savings and service reliability. Difference-in-Differences, Transport Maintenance Depots, Cost-Effectiveness Analysis, Urban Infrastructure 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/
Bayesian Hierarchical Model for Yield Improvement in Industrial Machinery Fleets of Rwanda
Industrial machinery fleets in Rwanda face inefficiencies due to varying maintenance schedules and parts availability. A Bayesian hierarchical model was developed incorporating data from multiple industrial sectors in Rwanda. The model accounts for variability in machine performance across different conditions and contexts. The model estimated an average yield improvement of 5% with a 95% confidence interval ranging from 3 to 7%, indicating significant potential gains in operational efficiency. Bayesian hierarchical modelling provides a robust framework for measuring yield improvements in industrial machinery fleets, enhancing maintenance strategies and part supply chain management. Implement the proposed model across all major sectors of Rwanda’s industrial economy to maximise overall fleet performance and resource utilization. Industrial Machinery Fleets, Yield Improvement, Bayesian Hierarchical Model, 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.
Methodological Evaluation of Municipal Infrastructure Assets Systems in Uganda using Difference-in-Differences Approach
Uganda's municipal infrastructure assets systems are critical for urban development but their adoption rates vary. A difference-in-differences model will be applied to assess the impact of policy interventions on the adoption of municipal infrastructure assets in Ugandan cities. The analysis indicates an increase of 15% in the adoption rate of smart city technologies after a new policy was implemented. The difference-in-differences approach effectively measures the effect of policy changes on asset systems' adoption rates. Policymakers should consider replicating this model to monitor and enhance municipal infrastructure development across Uganda. Uganda, Municipal Infrastructure, Adoption Rates, Difference-in-Differences (DID) 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 Power-Distribution Equipment Systems in Rwanda Using Quasi-Experimental Design
Rwanda aims to increase access to reliable power distribution systems through various infrastructure projects. The study employs a quasi-experimental design, including pre-post comparisons and control groups to assess system performance and identify areas for enhancement. A notable finding is that the distribution efficiency improved by approximately 15% after implementing targeted upgrades in certain regions, though variance exists across different sectors. The quasi-experimental design demonstrated a significant potential to measure and enhance power-system efficiency, offering practical insights for policymakers and practitioners. Policymakers should prioritise standardised maintenance schedules and encourage the adoption of proven technological solutions to further improve system reliability. Power Distribution, Efficiency Gains, 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.
Methodological Evaluation of Transport Maintenance Depots Systems in Uganda
Transport maintenance depots (TMDs) play a critical role in ensuring the reliability of public transport systems in urban areas. In Uganda, TMDs are essential for maintaining and repairing buses to meet operational standards. A randomized controlled trial approach was employed to assess the effectiveness of different maintenance strategies. Data collection involved monitoring operational activities at randomly selected depots over a six-month period. The analysis revealed that depots implementing proactive maintenance schedules experienced an average reduction in downtime by 20% compared to those relying on reactive approaches, with specific patterns indicating significant improvements in system reliability. This study provides empirical evidence supporting the adoption of proactive maintenance strategies over reactive ones for enhancing TMD performance and overall transport service reliability. Based on these findings, it is recommended that Ugandan public transportation authorities consider implementing more proactive maintenance programmes to improve service quality and efficiency. 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/
Multilevel Regression Analysis for Measuring Adoption Rates in Process-Control Systems in South Africa
Process-control systems (PCSs) are critical in managing complex industrial processes to ensure efficiency and safety. In South Africa, these systems are implemented across various sectors but their adoption rates vary significantly. We employed multilevel logistic regression models to assess the impact of factors such as industry type, geographical location, and organisational size on PCS adoption. Data from a survey conducted across multiple sectors was used for this analysis. Our findings indicate that industries in urban areas with larger organizations have higher adoption rates of PCSs (urban industrial sector: 70%, large organizations: 85%). The multilevel regression approach provides a nuanced understanding of the factors influencing PCS adoption, offering insights for policymakers and industry leaders. Policymakers should prioritise urban areas with larger organizations to maximise the benefits of process-control systems in South Africa's industrial sectors. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.