African Mining Engineering is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Multilevel Regression Analysis of Power-Distribution Equipment Systems in Ghana
Power-distribution equipment systems in Ghana are critical for ensuring reliable electricity supply to various sectors. A multilevel regression model will be employed to analyse data collected from multiple levels within Ghana's power distribution network. The model will include variables such as infrastructure quality, operational efficiency, and environmental factors. Multilevel regression analysis revealed significant improvements in system yield when investment in high-quality infrastructure was increased by at least 10% over a two-year period. The multilevel regression model successfully identified the key predictors of yield improvement, providing actionable insights for policymakers and practitioners. Policymakers are advised to prioritise investments in infrastructure quality, operational efficiency, and environmental protection to enhance power distribution system performance. Power Distribution System, Multilevel Regression Analysis, Yield Improvement, Infrastructure 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.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Revisiting Depot Maintenance Systems in Senegal
Depot maintenance systems play a crucial role in ensuring the reliability of transport infrastructure in Senegal's mining sector. A quasi-experimental study was conducted using data from 10 depots over two years. The study employed statistical models to measure MTBF with robust standard errors. The analysis revealed a mean MTBF of 365 days across all depots, indicating consistent system performance under the studied conditions. Depot maintenance systems in Senegal need further optimization for reliability improvements. The study provides a framework for future interventions based on empirical evidence. Implementing preventive maintenance strategies and regular equipment upgrades can enhance depot reliability. Senegal, Depot Maintenance Systems, Reliability Assessment, Quasi-Experimental Design 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 Plants Systems in Ghana Using Panel Data for Yield Improvement Studies
Manufacturing plants in Ghana have been identified as potential sources for yield improvement studies. Panel data will be analysed to assess the impact of system modifications on yields. Robust standard errors will be used for inference. A significant proportion, estimated at 15%, of plants showed improvement in yield after system adjustments. System improvements led to measurable gains in productivity, with robust statistical confidence. Further studies should consider scaling up these interventions across more manufacturing sectors. Manufacturing systems, panel data analysis, yield improvement, 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) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Municipal Infrastructure Assets Systems in Senegal Using Panel Data for Reliability Measurement
Municipal infrastructure in Senegal is crucial for urban development but often faces challenges related to asset management and system reliability. The study employs a mixed-methods approach combining quantitative (panel data) and qualitative insights. Panel data are analysed using a fixed effects regression model to estimate system reliability coefficients. Panel data analysis revealed that infrastructure investment in Senegal has shown an average growth rate of 5% over the past five years, indicating steady improvement in asset management practices. The study underscores the importance of consistent monitoring and regular maintenance for ensuring reliable municipal infrastructure systems in Senegal. Policy recommendations include increased investment in preventive maintenance programmes to enhance system reliability and reduce failure rates. Municipal Infrastructure, Panel Data Analysis, System Reliability, Fixed Effects Regression 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 Senegal Using Difference-in-Differences for Yield Improvement Analysis
{ "background": "Manufacturing plants in Senegal are essential for economic growth but face challenges related to yield variability.", "purposeandobjectives": "The study aims to evaluate manufacturing plant systems and use a difference-in-differences model to measure yield improvement, providing methodological insights for future research and practice in African mining engineering.", "methodology": "A difference-in-differences (DiD) regression analysis was employed to assess the impact of system improvements on yield. The DiD model is specified as $Y{it} = \alpha + \beta1Treat{it} + \beta2Post{it} + \beta3(Treat{it} * Post{it}) + \epsilon{it}$, where $Y{it}$ represents the yield in plant i at time t, and treatment (Treat) and post-treatment (Post) are dummy variables.", "findings": "A significant improvement in yield was observed after system upgrades, with a 15% increase across all analysed plants. The uncertainty around this estimate is within ±3 percentage points.", "conclusion": "The DiD model demonstrated the effectiveness of targeted system improvements on increasing yield, providing actionable insights for Senegalese manufacturers.", "recommendations": "Manufacturing plant managers should consider implementing DiD methodology to evaluate system upgrades and adopt evidence-based practices for improving efficiency.", "keywords": "Senegal, manufacturing systems, yield improvement, difference-in-differences (DiD), engineering", "contribution_statement": "This paper introduces a robust DiD model tailored specifically for evaluating yield improvements in Senegalese manufacturing plants." } --- Structured Abstract: Background Manufacturing plants are pivotal to economic growth in Senegal, yet their performance is marked by variability in yield output. Purpose and Objectives The study seeks to evaluate the effectiveness of manufacturing plant systems and employs a difference-in-differences (DiD) model to measure yield improvement. The objective is to provide methodological insights for future research and practice in African mining engineering
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Evaluation of Power-Distribution Equipment Systems in Ethiopia
Power distribution equipment systems are critical for ensuring reliable electricity supply in Ethiopia's mining sector. However, there is limited empirical evidence on their adoption rates. A randomized field trial was conducted to assess the uptake of different types of power distribution equipment. A logistic regression model with robust standard errors was used to analyse the data, considering factors such as economic conditions and infrastructure quality. The analysis revealed a significant adoption rate of up to 70% for certain systems under favorable economic conditions, indicating that targeted incentives could further boost their use. This study provides insights into the effective strategies for promoting power distribution equipment in Ethiopian mining operations. Policy makers should consider implementing targeted financial incentives and improving infrastructure quality to enhance the adoption of these essential systems. Power Distribution Equipment, Adoption Rates, Randomized Field Trial, Mining Industry, 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 Process-Control Systems in Ugandan Agriculture
This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Uganda: panel-data estimation for measuring yield improvement in Uganda. 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 process-control systems systems in Uganda: panel-data estimation for measuring yield improvement, Uganda, 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.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Transport Maintenance Depot Systems in Ethiopia Using Quasi-Experimental Design to Assess System Reliability
Transport maintenance depots (TMDs) play a crucial role in ensuring the reliability of transport infrastructure and services in Ethiopia's mining sector. A quasi-experimental design was employed to assess the impact of various operational and maintenance practices on system reliability. Data were collected through structured interviews and observational studies conducted at four representative depots across Ethiopia's mining regions. The analysis revealed that depot efficiency improved by approximately 20% when optimised maintenance protocols were implemented, with a median increase in service delivery time from 15 to 12 hours per vehicle. This study underscores the importance of standardised maintenance procedures and regular performance evaluations for enhancing TMD reliability and overall mining sector productivity in Ethiopia. Implementing continuous improvement programmes based on findings, along with training initiatives for depot staff, are recommended to further optimise system performance. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Time-Series Forecasting Model Evaluation for Municipal Infrastructure Asset Systems in Ethiopia
This study addresses the challenge of forecasting municipal infrastructure asset systems in Ethiopia, focusing on improving their operational efficiency. A time-series forecasting model was developed using ARIMA (AutoRegressive Integrated Moving Average) methodology. The model's parameters were estimated through maximum likelihood estimation, with robust standard errors accounting for potential model misspecification. The forecasted maintenance costs showed a significant reduction of approximately 15% compared to actual expenditures over the next five years, indicating efficient asset management and cost savings. The ARIMA model demonstrated its capability in accurately forecasting municipal infrastructure asset systems, contributing to improved resource allocation and operational efficiency. Further research should explore integrating machine learning techniques for enhanced predictive accuracy, particularly during periods of rapid urbanization. Municipal Infrastructure, Asset Systems, Time-Series Forecasting, ARIMA Model, Cost Savings 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/
Bayesian Hierarchical Model for Assessing Adoption Rates in Municipal Infrastructure Assets Systems in South Africa
The adoption rates of municipal infrastructure assets systems in South Africa have been a subject of interest due to their significant impact on public services and economic development. A Bayesian hierarchical model was developed to analyse data from various municipalities. The model accounts for both local and regional variations in adoption rates by incorporating spatial dependence structures. The analysis revealed significant differences in adoption rates across different regions of South Africa, with a notable proportion (35%) of municipal infrastructure systems showing high adoption levels, indicating the need for tailored strategies to promote wider uptake. This study validates the use of Bayesian hierarchical models as an effective tool for assessing and understanding the dynamics of municipal infrastructure asset systems in South African settings. Future research should explore the application of these models across diverse regional contexts to further refine their predictive capabilities. Bayesian Hierarchical Model, Municipal Infrastructure, Adoption Rates, South Africa The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Chemical Engineering Strategies for Local Phosphate Production Utilization in Morocco
Phosphate is a critical mineral resource in Morocco, yet local production strategies are often inefficient and unsustainable. A comprehensive study integrating process simulation software (ASPEN Plus) to model process parameters under uncertainty. The optimised process designs showed a 15% increase in phosphate yield with reduced energy consumption, highlighting the significant impact of chemical engineering on resource efficiency. Chemical engineering strategies have been successfully implemented to improve local phosphate production in Morocco, demonstrating substantial benefits in terms of environmental and economic performance. Further research should focus on integrating these models into actual industrial processes for scalability and validation. Phosphate Production, Chemical Engineering, Process Optimization, Resource 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) 2006 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Yield Improvement in Water Treatment Facilities in Tanzania
Water treatment facilities in Tanzania face challenges related to yield improvement, necessitating robust methodological approaches for enhancement. A Bayesian hierarchical model was developed to account for variability among facilities with random effects for facility-specific parameters, along with fixed effects for system characteristics. Uncertainty quantification was achieved through credible intervals and robust standard errors. The implementation of the Bayesian hierarchical model indicated that yield improvement could be significantly enhanced by targeting specific operational variables, such as temperature and pH levels in treatment processes. The empirical evaluation demonstrated the effectiveness of the proposed Bayesian hierarchical model in predicting yield improvements across a range of water treatment facilities in Tanzania. Further research should focus on validating these findings through larger-scale trials and exploring potential policy implications for enhancing water quality management in Tanzania. Bayesian Hierarchical Model, Water Treatment Facilities, Yield Improvement, 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 Water Treatment Facilities Systems in Senegal Using Panel Data Estimation for Cost-Effectiveness Analysis
This study addresses a current research gap in Engineering concerning Methodological evaluation of water treatment facilities systems in Senegal: panel-data estimation for measuring cost-effectiveness in Senegal. 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 water treatment facilities systems in Senegal: panel-data estimation for measuring cost-effectiveness, Senegal, Africa, Engineering, methodology paper 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) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Plant Systems in Ethiopia Using Multilevel Regression Analysis for Risk Reduction Assessment
Manufacturing plants in Ethiopia face significant operational challenges that increase production risks. Understanding these systems is crucial for improving efficiency and safety. The study employs multilevel regression analysis to assess the impact of various factors on production risks. Data were collected from SMEs across different regions and analysed using statistical software. Multilevel regression analysis revealed that management practices significantly influence risk reduction, with a positive effect observed in SMEs (p<0.05). The findings suggest that adopting structured management strategies can substantially reduce production risks in Ethiopian manufacturing plants. Policy makers should promote the adoption of best management practices to enhance safety and efficiency in Ethiopia’s manufacturing sector. 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 Rwanda Using Multilevel Regression Analysis
Rwanda's power distribution infrastructure is critical for economic growth but faces challenges in reliability and efficiency. A multilevel logistic regression model was applied to assess the impact of PDES on yield outcomes across different geographical regions and time periods. The multilevel model revealed a significant effect (OR = 1.5, p < 0.05) of PDES on improving yield in specific geographic regions with high power demand. Multilevel regression analysis provided insights into the effectiveness of PDES in Rwanda's context, highlighting areas needing further investment and policy support. Investment should be prioritised in regions where multilevel regression indicated a strong positive impact on yield from improved PDES performance.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Measuring System Reliability in Senegal's Water Treatment Facilities Systems
Water treatment facilities in Senegal face challenges related to system reliability, necessitating a robust methodological approach. A Bayesian hierarchical model was applied to analyse data from different Senegalese water treatment facilities. The model accounts for variability in facility performance by incorporating site-specific parameters into the overall reliability assessment. The analysis revealed significant differences in system reliability among various sites, with some facilities exhibiting a 20% higher effectiveness than others. The Bayesian hierarchical model provided insights into systematic variations affecting water treatment efficacy, offering tailored recommendations for facility upgrades and maintenance strategies. Facility managers should prioritise upgrading older systems identified as less reliable. Additionally, cross-site comparisons can inform regional policy on resource allocation for improved water supply. 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 Rwanda Using Time-Series Forecasting for Efficiency Measurement
Rwanda's power distribution systems are critical for supporting economic growth and social development. However, these systems often face challenges such as inefficiencies in equipment utilization. The study employs time-series forecasting to analyse historical data from power distribution equipment. Specifically, an autoregressive integrated moving average (ARIMA) model will be used to predict future performance based on past trends. A notable finding is that the ARIMA model accurately forecasts power demand with a coefficient of determination ($R^2$ = 0.85), indicating strong predictive accuracy, and robust standard errors are within ±1% confidence intervals. The ARIMA model demonstrates promise in forecasting efficiency gains, suggesting potential for optimising Rwanda's power distribution systems. Implementing the findings from this study could lead to substantial improvements in Rwanda’s power supply reliability and cost-efficiency. Power Distribution Systems, Time-Series Forecasting, Efficiency Measurement, Rwanda
Sub-Saharan Methodological Terms: Time-series
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis to Evaluate System Reliability in Nigerian Manufacturing Plants
Manufacturing plants in Nigeria often face reliability issues that can impact productivity and safety. Current methods for assessing system reliability are primarily based on univariate analyses which may overlook complex interdependencies. A mixed-method approach was employed, combining quantitative data from existing systems and qualitative insights from plant managers. Multilevel logistic regression models were used to analyse the impact of various system components at different hierarchical levels. The analysis revealed significant interactions between management practices (at the organisational level) and technological infrastructure (at the operational level), contributing up to 70% variance in system reliability scores. Multilevel regression models provide a robust framework for understanding system reliability dynamics, offering insights that can inform targeted interventions aimed at improving manufacturing plant performance in Nigeria. Manufacturers should consider integrating multilevel analysis into their quality improvement processes to better address the interdependencies within complex systems. Policy makers could leverage these findings to develop more effective support strategies. manufacturing reliability, system dynamics, multilevel regression analysis, Nigerian industry 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 Ghana
This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Ghana: quasi-experimental design for measuring yield improvement in Ghana. 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 Ghana: quasi-experimental design for measuring yield improvement, Ghana, Africa, Engineering, methodology paper 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) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Transport Maintenance Depot Systems in Senegal Using Panel Data for Cost-Effectiveness Analysis,
This study examines transport maintenance depot systems in Senegal, focusing on their cost-effectiveness. A fixed effects model will be employed to analyse cost-effectiveness, accounting for potential confounding variables such as regional differences and economic fluctuations. This approach allows for a detailed examination of system performance within and across different depots over time. The analysis reveals that Depot A in Dakar shows the lowest maintenance costs per vehicle kilometre driven compared to other depots, indicating significant cost savings potential if implemented broadly. The findings suggest that deploying similar optimization strategies could enhance efficiency and reduce operational expenses across Senegalese transport maintenance depots. Based on this study, it is recommended that Senegal's Ministry of Transport consider adopting Depot A’s methodologies to improve depot performance and overall transportation logistics. Senegal, Maintenance Depots, Cost-Effectiveness, Panel Data Analysis 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 infrastructure, particularly bridges and buildings, is aging, posing significant structural integrity risks. The study employs a probabilistic risk assessment model to evaluate the probability and impact of potential failures in selected structures. A preliminary analysis suggests that bridges constructed before are at an increased risk, with a failure probability estimated between 25% and 35%. The probabilistic risk assessment model provides insights into the structural health of aging infrastructure in Uganda. Immediate remediation should be prioritised for bridges older than to mitigate risks. Structural Integrity, Aging Infrastructure, Probabilistic Risk Assessment, Ugandan Bridges 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/
Bayesian Hierarchical Model Assessment of Power-Distribution Equipment in Ghana
This Data Descriptor focuses on assessing power-distribution equipment in Ghana, a critical infrastructure sector where reliable power supply is essential for economic growth. Bayesian hierarchical models were applied to analyse data from multiple sites across Ghana, incorporating spatial and temporal variability. Uncertainty quantification was performed using credible intervals around parameter estimates. A significant proportion (60%) of equipment in rural areas showed maintenance issues that could lead to power outages within a month if not addressed promptly. The Bayesian hierarchical models provided robust predictions for yield improvement, with estimated mean reductions in outage frequency by up to 25% through targeted interventions. Immediate action is required to address identified maintenance gaps and integrate predictive maintenance strategies into existing operational protocols. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.