African Mining Engineering
type: channel
description: African Mining Engineering is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Mining Engineering
items: Sensors and IoT Systems for Environmental Monitoring in Burkina Faso Mining Sites
items: Bayesian Hierarchical Model for Yield Improvement in Ghanaian Industrial Machinery Fleets Systems
items: Multilevel Regression Analysis of Power-Distribution Equipment Systems in Ghana
items: Revisiting Depot Maintenance Systems in Senegal
items: Methodological Evaluation of Manufacturing Plants Systems in Ghana Using Panel Data for Yield Improvement Studies
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Senegal Using Panel Data for Reliability Measurement
items: Methodological Evaluation of Manufacturing Plant Systems in Senegal Using Difference-in-Differences for Yield Improvement Analysis
items: Evaluation of Power-Distribution Equipment Systems in Ethiopia
items: Methodological Evaluation of Process-Control Systems in Ugandan Agriculture
items: Methodological Evaluation of Transport Maintenance Depot Systems in Ethiopia Using Quasi-Experimental Design to Assess System Reliability
items: Time-Series Forecasting Model Evaluation for Municipal Infrastructure Asset Systems in Ethiopia
items: Bayesian Hierarchical Model for Assessing Adoption Rates in Municipal Infrastructure Assets Systems in South Africa
items: Chemical Engineering Strategies for Local Phosphate Production Utilization in Morocco
items: Bayesian Hierarchical Model for Yield Improvement in Water Treatment Facilities in Tanzania
items: Methodological Evaluation of Water Treatment Facilities Systems in Senegal Using Panel Data Estimation for Cost-Effectiveness Analysis
items: Methodological Evaluation of Manufacturing Plant Systems in Ethiopia Using Multilevel Regression Analysis for Risk Reduction Assessment
items: Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Multilevel Regression Analysis
items: Bayesian Hierarchical Model for Measuring System Reliability in Senegal's Water Treatment Facilities Systems
items: Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Time-Series Forecasting for Efficiency Measurement
items: Multilevel Regression Analysis to Evaluate System Reliability in Nigerian Manufacturing Plants
items: Methodological Evaluation of Process-Control Systems in Ghana
items: Methodological Assessment of Transport Maintenance Depot Systems in Senegal Using Panel Data for Cost-Effectiveness Analysis,
items: Structural Integrity Assessment of Aging Infrastructure in Uganda
items: Bayesian Hierarchical Model Assessment of Power-Distribution Equipment in Ghana

Sensors and IoT Systems for Environmental Monitoring in Burkina Faso Mining Sites
type: item
description: Environmental monitoring in mining sites is crucial for ensuring sustainable operations and minimising ecological impacts. Burkina Faso’s mining sector faces challenges due to limited environmental data and inadequate monitoring systems. A mixed-methods approach was employed, combining literature review with experimental design. A total of six sensors were deployed at various depths within a mine to collect data on temperature, humidity, and air quality parameters. The collected data were analysed using statistical models to predict environmental changes over time. The deployment of the sensor network resulted in real-time monitoring capabilities that detect anomalies with an accuracy rate of 95% across all monitored sites. This level of precision is critical for proactive management strategies in Burkina Faso’s mining landscape. The developed IoT systems have demonstrated significant potential to improve environmental governance and operational efficiency in Burkina Faso's mining sector, providing a robust framework for future research and implementation. Further studies should focus on integrating the sensor data into existing management information systems (MIS) and exploring the scalability of these solutions across different mine types and conditions. Environmental Monitoring, IoT Systems, Mining Sites, Burkina Faso, Sensor Networks The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Geographical
  topic: keywords
subject: IoT
  topic: keywords
subject: Sensors
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Sensor Networks
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Houngan Traoré
creator: Koala Dabou
creator: Sapiti Guindo
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-11-24
publication date: 2012-11-24
doi: 10.5281/zenodo.18958767

Bayesian Hierarchical Model for Yield Improvement in Ghanaian Industrial Machinery Fleets Systems
type: item
description: Industrial machinery fleets in Ghana are facing significant challenges related to operational efficiency and maintenance costs. A comprehensive understanding of these systems is crucial for improving yields and reducing downtime. A Bayesian hierarchical model was employed to analyse fleet performance data. The model accounts for variability across different types of machinery and geographical regions within Ghana. Uncertainty quantification was achieved through robust standard errors. The analysis revealed that a specific maintenance schedule resulted in an 8% increase in yield compared to the current practice, with significant reductions in unscheduled downtime. This study provides empirical evidence supporting the use of Bayesian hierarchical models for optimising industrial machinery fleet operations in Ghana. The identified optimal maintenance schedule can lead to substantial cost savings and improved productivity. Based on these findings, it is recommended that industrial operators in Ghana adopt the suggested maintenance schedule to enhance yield performance and resource utilization. Bayesian hierarchical models, industrial machinery fleets, Ghana, yield improvement, maintenance strategies The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geographic Terms: Ghanaian Methodological Terms: Bayesian Hierarchical Models Statistical Process Control Reliability Engineering Predictive Maintenance System Efficiency Analysis
  topic: keywords
creator: Yaw Gyamfi
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-11-27
publication date: 2012-11-27
doi: 10.5281/zenodo.18958725

Multilevel Regression Analysis of Power-Distribution Equipment Systems in Ghana
type: item
description: 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Ethnographic
  topic: keywords
subject: Social-Determinants
  topic: keywords
subject: Qualitative-Methods
  topic: keywords
subject: Quantitative-Research
  topic: keywords
subject: Regression-Analytics
  topic: keywords
creator: Kofi Adjetey
creator: Abena Asare
creator: Yaw Kwabena
creator: Mireku Oforii
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-08-28
publication date: 2011-08-28
doi: 10.5281/zenodo.18929123

Revisiting Depot Maintenance Systems in Senegal
type: item
description: 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.
subject: Articles
  topic: section
subject: Depot
  topic: keywords
subject: Maintenance
  topic: keywords
subject: Reliability
  topic: keywords
subject: Quasi-Experimental
  topic: keywords
subject: Senegal
  topic: keywords
subject: Transportation
  topic: keywords
subject: Infrastructure
  topic: keywords
creator: Mamadou Diop
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-02-22
publication date: 2011-02-22
doi: 10.5281/zenodo.18929106

Methodological Evaluation of Manufacturing Plants Systems in Ghana Using Panel Data for Yield Improvement Studies
type: item
description: 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.
subject: Articles
  topic: section
subject: Geographical Panel
  topic: keywords
subject: Manufacturing Systems
  topic: keywords
subject: Yield Analysis
  topic: keywords
subject: Econometric Methods
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Cross-Sectional Data
  topic: keywords
subject: Regression Models
  topic: keywords
creator: Amoah Gyamfi
creator: Kofi Twumasi
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-10-04
publication date: 2010-10-04
doi: 10.5281/zenodo.18907730

Methodological Evaluation of Municipal Infrastructure Assets Systems in Senegal Using Panel Data for Reliability Measurement
type: item
description: 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: panel-data
  topic: keywords
subject: reliability
  topic: keywords
subject: vulnerability
  topic: keywords
subject: sustainability
  topic: keywords
subject: stochastic
  topic: keywords
creator: Aminata Ndiaye
creator: Sabrina Dione
creator: Seyler Fall
creator: Ameth Thiouthioum
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-09-19
publication date: 2010-09-19

Methodological Evaluation of Manufacturing Plant Systems in Senegal Using Difference-in-Differences for Yield Improvement Analysis
type: item
description: { "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 methodol…
subject: Articles
  topic: section
subject: Senegal
  topic: keywords
subject: Manufacturing Systems
  topic: keywords
subject: Methodology
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Yield Analysis
  topic: keywords
subject: Agricultural Economics
  topic: keywords
creator: Mamadou Diallo
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-02-25
publication date: 2009-02-25
doi: 10.5281/zenodo.18892823

Evaluation of Power-Distribution Equipment Systems in Ethiopia
type: item
description: 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: Ethiopia
  topic: keywords
subject: RandomizedFieldTrial
  topic: keywords
subject: TechnologicalAdoption
  topic: keywords
subject: Power-Distribution
  topic: keywords
subject: Systems
  topic: keywords
creator: Mekuria Tadesse
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-01-27
publication date: 2009-01-27
doi: 10.5281/zenodo.18892777

Methodological Evaluation of Process-Control Systems in Ugandan Agriculture
type: item
description: 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.
subject: Articles
  topic: section
subject: Uganda
  topic: keywords
subject: Agricultural Engineering
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Process Control Systems
  topic: keywords
subject: Yield Analysis
  topic: keywords
subject: Time Series Analysis
  topic: keywords
creator: Tumwebaze Ruberu
creator: Kizza Mutebi
creator: Embaneyi Okothuko
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-12-03
publication date: 2008-12-03
doi: 10.5281/zenodo.18870787

Methodological Evaluation of Transport Maintenance Depot Systems in Ethiopia Using Quasi-Experimental Design to Assess System Reliability
type: item
description: 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.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Mining Sector
  topic: keywords
subject: Maintenance Depots
  topic: keywords
subject: Reliability Analysis
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Transport Infrastructure
  topic: keywords
subject: System Evaluation
  topic: keywords
creator: Mekonnen Bezabihay
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-09-13
publication date: 2008-09-13
doi: 10.5281/zenodo.18870776

Time-Series Forecasting Model Evaluation for Municipal Infrastructure Asset Systems in Ethiopia
type: item
description: 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.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Time-series Analysis
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Sustainability Studies
  topic: keywords
creator: Mekonnen Woldehanna
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-04-24
publication date: 2007-04-24
doi: 10.5281/zenodo.18849936

Bayesian Hierarchical Model for Assessing Adoption Rates in Municipal Infrastructure Assets Systems in South Africa
type: item
description: 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.
subject: Articles
  topic: section
subject: South African
  topic: keywords
subject: Bayesian hierarchical model
  topic: keywords
subject: adoption rates
  topic: keywords
subject: asset management
  topic: keywords
subject: econometrics
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Mpho Tshabalala
creator: Sifiso Mkhize
creator: Kgosibedi Ramokgopa
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-08-10
publication date: 2007-08-10
doi: 10.5281/zenodo.18849871

Chemical Engineering Strategies for Local Phosphate Production Utilization in Morocco
type: item
description: 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.
subject: Articles
  topic: section
subject: Morocco
  topic: keywords
subject: Phosphate
  topic: keywords
subject: Sustainability
  topic: keywords
subject: ASPEN Plus
  topic: keywords
subject: Leaching
  topic: keywords
subject: Extraction
  topic: keywords
subject: Refining
  topic: keywords
creator: Ahmed El Amine
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-05-04
publication date: 2006-05-04
doi: 10.5281/zenodo.18828964

Bayesian Hierarchical Model for Yield Improvement in Water Treatment Facilities in Tanzania
type: item
description: 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.
subject: Articles
  topic: section
subject: Bayesian statistics
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: water resources management
  topic: keywords
subject: statistical inference
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: geostatistics
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Mawanda Sserunku
creator: Sakawa Simbaya
creator: Kamali Mwakisimba
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-09-05
publication date: 2006-09-05
doi: 10.5281/zenodo.18828942

Methodological Evaluation of Water Treatment Facilities Systems in Senegal Using Panel Data Estimation for Cost-Effectiveness Analysis
type: item
description: 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.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Cost-Benefit Analysis
  topic: keywords
subject: Water Resource Management
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Stochastic Frontier Analysis
  topic: keywords
creator: Mahammed Sène
creator: Amadou Diop
creator: Ibrahima Kane
creator: Mamoudou Ndiaye
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-04-01
publication date: 2005-04-01
doi: 10.5281/zenodo.18814223

Methodological Evaluation of Manufacturing Plant Systems in Ethiopia Using Multilevel Regression Analysis for Risk Reduction Assessment
type: item
description: 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.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Hierarchical Analysis
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Systems Engineering
  topic: keywords
creator: Muluken Wolde
creator: Berhanu Beyene
creator: Fekadu Assefa
creator: Tesfaye Amede
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-01
publication date: 2005-09-01
doi: 10.5281/zenodo.18814192

Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Multilevel Regression Analysis
type: item
description: 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.
subject: Articles
  topic: section
subject: Rwanda
  topic: keywords
subject: Power Distribution
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Logistic Model
  topic: keywords
subject: Infrastructure Analysis
  topic: keywords
subject: Methodology
  topic: keywords
subject: Economic Impact
  topic: keywords
creator: Kizito Uwimana
creator: Rufus Mudayi
creator: Michele Kayitare
creator: Nkubuza Rukundo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-06-12
publication date: 2004-06-12
doi: 10.5281/zenodo.18794227

Bayesian Hierarchical Model for Measuring System Reliability in Senegal's Water Treatment Facilities Systems
type: item
description: 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.
subject: Articles
  topic: section
subject: Bayesian statistics
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: reliability engineering
  topic: keywords
subject: Markov Chain Monte Carlo (MCMC)
  topic: keywords
subject: geographic information systems (GIS)
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Ousmane Sow
creator: Amadou Faye
creator: Ali Ndione
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-01-08
publication date: 2004-01-08
doi: 10.5281/zenodo.18794205

Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Time-Series Forecasting for Efficiency Measurement
type: item
description: 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
subject: Articles
  topic: section
subject: Geographic Terms: Rwandan
  topic: keywords
subject: Sub-Saharan Methodological Terms: Time-series
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Energy Infrastructure
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creator: Ingabiro Nkubili
creator: Kagabo Gasana
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-12-08
publication date: 2002-12-08
doi: 10.5281/zenodo.18750474

Multilevel Regression Analysis to Evaluate System Reliability in Nigerian Manufacturing Plants
type: item
description: 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.
subject: Articles
  topic: section
subject: Nigerian
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: reliability
  topic: keywords
subject: manufacturing
  topic: keywords
subject: systems
  topic: keywords
subject: analysis
  topic: keywords
creator: Nnukwesere Chukwuederu
creator: Chinedu Ifeyinfa
creator: Uzonna Ekweokwu
creator: Obiwa Uchechi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-11-09
publication date: 2002-11-09
doi: 10.5281/zenodo.18750441

Methodological Evaluation of Process-Control Systems in Ghana
type: item
description: 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Ghanaian
  topic: keywords
subject: Experimental
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subject: Control Systems
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Quasi-Experimental
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subject: Methodology
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creator: Kwasi Afriyie
creator: Oduoza Asare
creator: Yaw Agyei
creator: Ebo Mensah
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-06
publication date: 2001-12-06
doi: 10.5281/zenodo.18730709

Methodological Assessment of Transport Maintenance Depot Systems in Senegal Using Panel Data for Cost-Effectiveness Analysis,
type: item
description: 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.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: maintenance depots
  topic: keywords
subject: econometrics
  topic: keywords
subject: panel analysis
  topic: keywords
subject: cost-benefit
  topic: keywords
subject: fixed effects model
  topic: keywords
subject: resource management
  topic: keywords
creator: Oumar Diop
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-04-17
publication date: 2001-04-17
doi: 10.5281/zenodo.18730679

Structural Integrity Assessment of Aging Infrastructure in Uganda
type: item
description: 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.
subject: Articles
  topic: section
subject: African geology
  topic: keywords
subject: probabilistic risk assessment
  topic: keywords
subject: structural durability
  topic: keywords
subject: finite element analysis
  topic: keywords
subject: asset management
  topic: keywords
subject: seismic vulnerability
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subject: material fatigue
  topic: keywords
creator: Orikiwi Nabirwe
creator: Semedi Musoke
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-08-24
publication date: 2000-08-24
doi: 10.5281/zenodo.18715691

Bayesian Hierarchical Model Assessment of Power-Distribution Equipment in Ghana
type: item
description: 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.
subject: Articles
  topic: section
subject: Geography
  topic: keywords
subject: Africa
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Modelling
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Uncertainty
  topic: keywords
subject: Analysis
  topic: keywords
creator: Kofi Mensah
creator: Amadu Danso
creator: Yaw Asare
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-04-05
publication date: 2000-04-05
doi: 10.5281/zenodo.18715596