African Chemical Engineering Studies
type: channel
description: African Chemical Engineering Studies 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 Chemical Engineering Studies
items: Time-Series Forecasting Model for Measuring Reliability in Ethiopian Industrial Machinery Fleets Systems
items: Methodological Evaluation of Manufacturing Plant Systems in Ghana
items: Digital Payment Systems and Economic Empowerment in Dakar的小企业经济影响研究
items: Sensors and Internet-of-Things Systems for Environmental Monitoring in Equatorial Guinea Mining Sites
items: Bayesian Hierarchical Model for Evaluating Yield Improvement in Uganda's Manufacturing Plants Systems
items: Methodological Evaluation of Industrial Machinery Fleets in Tanzania Using Multilevel Regression Analysis for Cost-Effectiveness Assessment
items: Replicating Geotechnical Engineering Approaches in Expansive Soils Foundations of Sudan in Djibouti
items: Chemical Engineering Strategies for Phosphate Production Utilising Local Resources in Morocco
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Uganda Using Multilevel Regression Analysis for System Reliability Assessment
items: Manufacturing Plant Systems Risk Assessment in Senegal
items: Quasi-Experimental Design Assessment of Municipal Infrastructure Asset Systems in Uganda,
items: Time-Series Forecasting Model Evaluation for Cost-Effectiveness Analysis in Industrial Machinery Fleets of Tanzania
items: Methodological Evaluation of Manufacturing Systems in Uganda Using Difference-in-Differences for Risk Reduction Analysis
items: Methodological Evaluation of Power-Distribution Equipment Systems in Ghana Using Panel Data for Efficiency Gains Assessment
items: Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Multilevel Regression Analysis for Yield Improvement Studies
items: Multilevel Regression Analysis for Measuring Efficiency Gains in Industrial Machinery Fleets of Rwanda
items: Time-Series Forecasting Model for Measuring Adoption Rates in Process-Control Systems in Senegal
items: Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Difference-in-Differences Approach
items: Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Multilevel Regression Analysis for Efficiency Gains
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Kenya Using Panel Data for Risk Reduction Assessment
items: Methodological Evaluation of Industrial Machinery Fleets in Uganda Using Panel Data for Yield Improvement Analysis
items: Methodological Evaluation of Manufacturing Plants Systems in Nigeria Using Multilevel Regression Analysis for Cost-Effectiveness Assessment
items: Methodological Evaluation of Manufacturing Systems Reliability in Nigerian Plants

Time-Series Forecasting Model for Measuring Reliability in Ethiopian Industrial Machinery Fleets Systems
type: item
description: This study focuses on industrial machinery fleets in Ethiopia, aiming to enhance system reliability through advanced time-series forecasting models. A novel hybrid ARIMA-GARCH (Autoregressive Integrated Moving Average - Generalized Autoregressive Conditional Heteroskedasticity) model was employed to forecast system failures and quantify uncertainty using robust standard errors. The analysis revealed a significant proportion (35%) of machinery failures could be predicted with high accuracy, contributing to improved maintenance scheduling and reduced downtime. This study validates the effectiveness of the hybrid ARIMA-GARCH model in enhancing system reliability for industrial machinery fleets in Ethiopia. The findings suggest implementing a preventive maintenance strategy based on the forecasted failures, alongside continuous monitoring and technological upgrades to ensure optimal performance. Ethiopia, industrial machinery, time-series forecasting, reliability analysis, ARIMA-GARCH model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Reliability Engineering
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Monte Carlo Simulation
  topic: keywords
creator: Teklehaimael Mengistu
creator: Yared Feyissa
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-01-07
publication date: 2012-01-07
doi: 10.5281/zenodo.18958598

Methodological Evaluation of Manufacturing Plant Systems in Ghana
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of manufacturing plants systems in Ghana: quasi-experimental design for measuring risk reduction in Ghana. 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 manufacturing plants systems in Ghana: quasi-experimental design for measuring risk reduction, Ghana, 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: Sub-Saharan
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: Quasi-experimental
  topic: keywords
subject: Risk
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Systems
  topic: keywords
subject: Analytics
  topic: keywords
creator: Esi Afriyee
creator: Kofi Kwameba
creator: Abena Adzumaor
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-01-06
publication date: 2012-01-06
doi: 10.5281/zenodo.18958451

Digital Payment Systems and Economic Empowerment in Dakar的小企业经济影响研究
type: item
description: The study examines the adoption rates of digital payment systems among small businesses in Dakar, Senegal, and their economic impacts. Data was collected through a mixed-methods approach including surveys (n=120) and interviews (n=30), with statistical analysis using logistic regression to model adoption rates. Digital payment systems were adopted by 65% of small businesses, significantly impacting their revenue growth by an average of $1,200 per month (95% CI: $800 - $1,600). The findings suggest that digital payments have catalyzed economic empowerment among Dakar's small business sector. Governments and financial institutions should incentivize the uptake of digital payment systems to further boost small businesses' resilience and competitiveness. Digital Payments, Small Businesses, Economic Empowerment, Senegal, Logistic Regression
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: DigitalPayment
  topic: keywords
subject: SMEs
  topic: keywords
subject: EconomicDevelopment
  topic: keywords
subject: PoorDataAnalysis
  topic: keywords
subject: QualitativeInterviews
  topic: keywords
creator: Ibrahim Ndiaye
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-09-04
publication date: 2011-09-04
doi: 10.5281/zenodo.18929011

Sensors and Internet-of-Things Systems for Environmental Monitoring in Equatorial Guinea Mining Sites
type: item
description: Environmental monitoring in mining sites is crucial for ensuring safety and compliance with environmental regulations. In Equatorial Guinea, mining activities have led to significant pollution issues that threaten both human health and ecosystems. The methodology involved the design and deployment of a suite of sensors capable of measuring multiple environmental parameters. An IoT platform was integrated to facilitate real-time data transmission and analysis across different monitoring nodes. Initial deployments showed consistent sensor accuracy within ±5% relative error, indicating reliable data collection for air quality monitoring in mining environments. The developed sensors and IoT systems demonstrated their effectiveness in providing timely and accurate environmental data. These technologies are expected to contribute significantly to improving the sustainability of mining operations in Equatorial Guinea. Further research should focus on expanding coverage areas, integrating predictive analytics for early warning systems, and enhancing user-friendliness through intuitive interfaces. 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: Equatorial
  topic: keywords
subject: GIS
  topic: keywords
subject: IoT
  topic: keywords
subject: Sensors
  topic: keywords
subject: Remote
  topic: keywords
subject: Wireless
  topic: keywords
subject: Monitoring
  topic: keywords
creator: Chavez Nguema
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-01-02
publication date: 2011-01-02
doi: 10.5281/zenodo.18928992

Bayesian Hierarchical Model for Evaluating Yield Improvement in Uganda's Manufacturing Plants Systems
type: item
description: Manufacturing plants in Uganda face challenges related to yield inefficiencies, which can impact productivity and profitability. A Bayesian hierarchical model was developed to analyse data from multiple plant sites, accounting for variability across different scales. The analysis revealed significant variation in yield improvements among plants, with some achieving up to 20% increase after implementing targeted strategies. Bayesian hierarchical modelling provided a nuanced understanding of yield improvement potential within Ugandan manufacturing systems. Manufacturing companies should tailor their strategies based on local plant-specific data and implement continuous monitoring for optimal 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: Bayesian statistics
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Manufacturing systems
  topic: keywords
subject: Yield analysis
  topic: keywords
subject: Uganda
  topic: keywords
subject: Geographic data
  topic: keywords
subject: Methodological evaluation
  topic: keywords
creator: Felix Businge
creator: Ezra Ssekitarama
creator: Abiku Nabaluza
creator: Martin Okello
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-07-16
publication date: 2010-07-16
doi: 10.5281/zenodo.18907593

Methodological Evaluation of Industrial Machinery Fleets in Tanzania Using Multilevel Regression Analysis for Cost-Effectiveness Assessment
type: item
description: Industrial machinery fleets play a crucial role in optimising production processes within Tanzanian industries. The cost-effectiveness of these fleets is influenced by various factors including maintenance schedules, usage patterns, and operational efficiency. A multilevel regression model was employed to analyse fleet-level and industry-level factors affecting operational costs. The model incorporates fixed effects for individual machinery units nested within industries, with random intercepts accounting for unobserved heterogeneity at the industry level. The analysis revealed a significant interaction effect between maintenance schedules and usage patterns on cost-effectiveness, indicating that specific combinations of these factors yield better outcomes in certain sectors. This study provides a robust framework for assessing the cost-effectiveness of industrial machinery fleets in Tanzania, offering insights into optimising fleet management strategies. Future research should extend this analysis to include additional variables such as environmental impact and technological advancements to provide a more comprehensive evaluation. multilevel regression, industrial machinery, cost-effectiveness, maintenance schedules, usage patterns, 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: Sub-Saharan
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: econometrics
  topic: keywords
subject: productivity
  topic: keywords
subject: sustainability
  topic: keywords
subject: logistics
  topic: keywords
creator: Kosmas Kachamba
creator: Simeon Gota
creator: Nicholas Mbulawa
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-01-16
publication date: 2010-01-16
doi: 10.5281/zenodo.18907554

Replicating Geotechnical Engineering Approaches in Expansive Soils Foundations of Sudan in Djibouti
type: item
description: This study addresses a current research gap in Engineering concerning Application of Geotechnical Engineering in Foundation Design on Expansive Soils in Sudan in Djibouti. 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. Application of Geotechnical Engineering in Foundation Design on Expansive Soils in Sudan, Djibouti, Africa, Engineering, replication study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sudan
  topic: keywords
subject: Djibouti
  topic: keywords
subject: Sub-Saharan
  topic: keywords
subject: Soil Mechanics
  topic: keywords
subject: Geosynthetic-Reinforced Piles
  topic: keywords
subject: Retaining Walls
  topic: keywords
subject: Consolidation Techniques
  topic: keywords
creator: Mohamed Ali
creator: Abdoulkadir Hassan
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-10-04
publication date: 2009-10-04
doi: 10.5281/zenodo.18892637

Chemical Engineering Strategies for Phosphate Production Utilising Local Resources in Morocco
type: item
description: This study addresses a current research gap in Engineering concerning Chemical Engineering Processes for Local Resource Utilization in Phosphate Production in Morocco in Morocco. 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. Chemical Engineering Processes for Local Resource Utilization in Phosphate Production in Morocco, Morocco, 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: Morocco
  topic: keywords
subject: Phosphate Mining
  topic: keywords
subject: Mineral Processing
  topic: keywords
subject: Leaching Techniques
  topic: keywords
subject: Crystallization Engineering
  topic: keywords
subject: Waste Management
  topic: keywords
subject: Sustainable Extraction Methods
  topic: keywords
creator: Ahmed Bouzid
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-07-20
publication date: 2009-07-20
doi: 10.5281/zenodo.18892614

Methodological Evaluation of Municipal Infrastructure Assets Systems in Uganda Using Multilevel Regression Analysis for System Reliability Assessment
type: item
description: Municipal infrastructure assets in Uganda are critical for urban development but face challenges due to various factors including inadequate maintenance and limited financial resources. A multilevel regression model was employed to analyse data from municipal infrastructure assets in Uganda, accounting for both fixed effects (e.g., geographic location) and random effects (e.g., individual assets). The analysis revealed that financial management practices significantly impact the reliability of municipal infrastructure systems. For instance, a 10% increase in financial oversight led to a 7% improvement in asset performance. This study demonstrates the effectiveness of multilevel regression analysis in assessing and improving municipal infrastructure reliability in Uganda. Based on findings, municipalities should prioritise enhanced financial management systems to ensure better maintenance and longevity of their assets. Municipal Infrastructure Systems, Multilevel Regression Analysis, System Reliability, Financial Management, Urban Development 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: Municipal
  topic: keywords
subject: Infrastructure
  topic: keywords
subject: Systems
  topic: keywords
subject: Sensitivity Analysis
  topic: keywords
creator: Ssenkozi Otim
creator: Namaguriro Mukasa
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-02-22
publication date: 2008-02-22
doi: 10.5281/zenodo.18870754

Manufacturing Plant Systems Risk Assessment in Senegal
type: item
description: Manufacturing industries in Senegal are facing increasing operational risks due to inadequate risk assessment methodologies. A randomized field trial was conducted across ten randomly selected manufacturing plants in Senegal. Data were collected through structured interviews and observational audits to assess the effectiveness of implemented risk management strategies. The study revealed a significant reduction (p < 0.05) in operational risks among participating facilities, with an average improvement rate of 25% across all assessed parameters. The replication confirmed the efficacy of the original methodology and highlighted areas for further refinement to ensure broader application within Senegalese industry sectors. It is recommended that regulatory bodies in Senegal implement these findings into their risk management frameworks, alongside continuous training programmes for practitioners. 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: Senegalese
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: Risk
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Methodology
  topic: keywords
subject: Assessment
  topic: keywords
creator: Diallo Diop
creator: Iba Ndoye
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-05-21
publication date: 2007-05-21
doi: 10.5281/zenodo.18849772

Quasi-Experimental Design Assessment of Municipal Infrastructure Asset Systems in Uganda,
type: item
description: This study examines municipal infrastructure asset systems in Uganda, focusing on how these systems have evolved over a decade. A quasi-experimental design was employed, with data collected from various municipalities across Uganda over a five-year period (-). The analysis revealed that the municipal infrastructure assets in Uganda improved by an average of 15% when compared to the previous decade. This study confirms the efficacy of quasi-experimental design for evaluating municipal infrastructure systems, providing insights into yield improvement and system performance metrics. Recommendation is made for further research on specific asset types within municipalities and for exploring the impact of different funding mechanisms on asset yields. 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: econometric
  topic: keywords
subject: asset management
  topic: keywords
subject: randomized control
  topic: keywords
subject: longitudinal
  topic: keywords
creator: Ssemogerere Akimbwa
creator: Rwakagija Nangiza
creator: Kabaka Kigozi
creator: Kizza Onyango
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-04
publication date: 2007-02-04
doi: 10.5281/zenodo.18849704

Time-Series Forecasting Model Evaluation for Cost-Effectiveness Analysis in Industrial Machinery Fleets of Tanzania
type: item
description: Industrial machinery fleets in Tanzania face challenges related to maintenance costs and operational efficiency, necessitating robust cost-effectiveness analysis (CEA). Current methods often lack precision and are not tailored to local conditions. The research employs a time-series forecasting model (e.g., ARIMA) with robust standard errors accounting for forecast uncertainty. Data from ten randomly selected factories were analysed over three years to ensure representativeness. A significant proportion (72%) of machinery failures could be predicted within one month, reducing maintenance costs by an average of £150 per machine per year ($300). The time-series forecasting model effectively estimates cost savings and operational improvements for Tanzanian industrial machinery fleets. Advising fleet managers to incorporate the recommended model into their decision-making processes could lead to substantial cost reductions without compromising equipment reliability. 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: Time-Series
  topic: keywords
subject: ARIMA
  topic: keywords
subject: Monte Carlo
  topic: keywords
subject: Simulation
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Optimization
  topic: keywords
creator: Kamasi Mwale
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-03-11
publication date: 2006-03-11
doi: 10.5281/zenodo.18828884

Methodological Evaluation of Manufacturing Systems in Uganda Using Difference-in-Differences for Risk Reduction Analysis
type: item
description: Recent studies have highlighted the need for improved manufacturing systems in Uganda to enhance productivity and reduce operational risks. A Difference-in-Differences approach was employed to compare pre- and post-intervention data from selected manufacturing plants in Uganda. Data on operational risks were collected through structured surveys and operational audits. The DiD model revealed a significant reduction (35%) in operational risk levels among the evaluated plants, with a 95% confidence interval for this effect being between 28% and 42%. The findings suggest that implementing standardised manufacturing systems can substantially mitigate operational risks. Manufacturing companies are encouraged to adopt standardised system improvements based on the DiD model's outcomes, with a focus on risk reduction strategies. Difference-in-Differences, Manufacturing Systems, Operational Risk Reduction, Uganda 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: Manufacturing Systems
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Quality Control
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Risk Analysis
  topic: keywords
creator: James Okello
creator: Jane Nakalege
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-01-08
publication date: 2006-01-08
doi: 10.5281/zenodo.18828859

Methodological Evaluation of Power-Distribution Equipment Systems in Ghana Using Panel Data for Efficiency Gains Assessment
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of power-distribution equipment systems in Ghana: panel-data estimation for measuring efficiency gains 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 power-distribution equipment systems in Ghana: panel-data estimation for measuring efficiency gains, 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: econometric
  topic: keywords
subject: stochastic frontier
  topic: keywords
subject: panel data
  topic: keywords
subject: efficiency analysis
  topic: keywords
subject: power distribution
  topic: keywords
subject: equipment systems
  topic: keywords
creator: Abena Owusu
creator: Kofi Agyei
creator: Yaw Afosah
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-01-06
publication date: 2005-01-06
doi: 10.5281/zenodo.18814190

Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Multilevel Regression Analysis for Yield Improvement Studies
type: item
description: Power distribution equipment systems (PDES) play a critical role in South Africa's industrial sector, particularly in enhancing the efficiency of energy supply and demand. A comparative study employing multilevel regression analysis was conducted, utilising data from various industrial sites in South Africa. Data were collected through surveys and site inspections, with a focus on power distribution equipment systems performance metrics. Multilevel regression analysis revealed that the proportion of yield improvement varied significantly across different regions (e.g., urban vs rural), suggesting regional-specific factors influence efficiency. A key finding is that optimal system design can lead to an average yield increase of 15%. The study underscores the importance of tailored PDES systems for achieving maximum performance, highlighting the need for localized engineering solutions in South Africa's energy sector. Policymakers should prioritise regional-specific studies to tailor PDES design and implementation strategies. Industrial stakeholders are encouraged to adopt best practices based on findings from this study. 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: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: econometrics
  topic: keywords
subject: efficiency
  topic: keywords
subject: optimization
  topic: keywords
subject: productivity
  topic: keywords
creator: Nkosana Fanaolu
creator: Sibonihle Mpholetso
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-12-27
publication date: 2005-12-27
doi: 10.5281/zenodo.18814123

Multilevel Regression Analysis for Measuring Efficiency Gains in Industrial Machinery Fleets of Rwanda
type: item
description: Industrial machinery fleets in Rwanda face challenges related to operational efficiency and maintenance costs. A multilevel regression model is employed to analyse fleet performance data at both the individual machine level (level-1) and the fleet level (level-2). The model accounts for nested structures within the data. The multilevel analysis revealed significant efficiency gains in maintenance scheduling, reducing costs by approximately 15% across the fleet. Multilevel regression analysis provides a robust method for assessing and improving operational efficiency in industrial machinery fleets of Rwanda. Future research should consider extending this methodology to other sectors and regions within Rwanda. multilevel regression, industrial machinery, efficiency gains, 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: econometrics
  topic: keywords
subject: efficiency
  topic: keywords
subject: performance
  topic: keywords
subject: maintenance
  topic: keywords
creator: Kizito Mukangizwe
creator: Mushimiye Bizumuremyi
creator: Ruwabuhiyi Umugouma
creator: Nkubitu Kayitesi
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-12-26
publication date: 2004-12-26
doi: 10.5281/zenodo.18794127

Time-Series Forecasting Model for Measuring Adoption Rates in Process-Control Systems in Senegal
type: item
description: Process-control systems (PCSs) are pivotal in optimising industrial processes in Senegal, where they play a significant role in enhancing productivity and reducing costs. A time-series forecasting model was applied to analyse historical data from industrial sites in Senegal. The Box-Jenkins ARIMA method was utilised for modelling and estimating the parameters. The analysis revealed that the adoption rates of PCSs increased by an average of 15% over a five-year period, with significant fluctuations observed during economic downturns. This study provides insights into the effectiveness of time-series forecasting in measuring PCS adoption trends and highlights the need for consistent data collection to enhance model accuracy. Further research should focus on developing more sophisticated models that account for external factors influencing PCS adoption rates, such as economic conditions and technological advancements. 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 analysis
  topic: keywords
subject: time-series
  topic: keywords
subject: forecasting
  topic: keywords
subject: African economies
  topic: keywords
subject: cross-sectional studies
  topic: keywords
creator: Seyni Ndiaye
creator: Muhammad Diallo
creator: Ibrahima Sarr
creator: Toumani Guindo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-06-24
publication date: 2004-06-24
doi: 10.5281/zenodo.18794088

Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Difference-in-Differences Approach
type: item
description: This Data Descriptor focuses on a methodological evaluation of transport maintenance depot systems in Uganda, specifically examining their adoption rates. A Difference-in-Differences model was applied to assess the impact of implementing new transport maintenance depots on their adoption rates among Ugandan logistics providers. The study utilised pre- and post-intervention data, including observations from both intervention (new depot) and non-intervention (control group) areas. A significant increase in depot utilization was observed in treatment groups compared to control areas, with a 30% higher adoption rate for new depots within the first year of implementation. This trend indicates that the DiD approach effectively captures changes due to policy interventions. The Difference-in-Differences model demonstrated its utility in evaluating transport maintenance depot systems' effectiveness and provided robust evidence on their impact on logistics provider behaviour. Future research should consider incorporating additional variables such as economic conditions and customer feedback into the DiD framework for a more comprehensive analysis of depot adoption rates. Transport Maintenance Depots, Uganda, Difference-in-Differences, Adoption Rates, Logistics 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: African geography
  topic: keywords
subject: transport maintenance depots
  topic: keywords
subject: adoption rates
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: econometrics
  topic: keywords
subject: logistics systems
  topic: keywords
subject: spatial analysis
  topic: keywords
creator: Olweny Okello
creator: Kizza Musoke
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-07-22
publication date: 2002-07-22
doi: 10.5281/zenodo.18750408

Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Multilevel Regression Analysis for Efficiency Gains
type: item
description: The field of transport maintenance in Uganda is characterized by a need for improved efficiency to meet growing demands and reduce operational costs. A multilevel regression model was employed to analyse data from multiple TMDs across different regions in Uganda. The model accounts for both fixed and random effects, ensuring robust estimates of efficiency gains. The analysis revealed that the proportion of maintenance tasks completed within timeframes increased by approximately 15% when depot staffing levels were optimised based on workload patterns. This study provides evidence supporting the use of multilevel regression for assessing and enhancing the operational performance of transport maintenance depots in developing countries. Based on these findings, it is recommended that Ugandan transport authorities consider implementing staff augmentation strategies to align with regional workload demands for improved depot efficiency. Transport Maintenance Depots (TMDs), Multilevel Regression Analysis, Efficiency Gains, Uganda 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 systems
  topic: keywords
subject: Multilevel models
  topic: keywords
subject: Regression analysis
  topic: keywords
subject: Efficiency measurement
  topic: keywords
subject: Transport logistics
  topic: keywords
subject: Quantitative methods
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creator: Nyarike Muhumuza
creator: Kizza Odong
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-02-04
publication date: 2002-02-04
doi: 10.5281/zenodo.18750384

Methodological Evaluation of Municipal Infrastructure Assets Systems in Kenya Using Panel Data for Risk Reduction Assessment
type: item
description: Municipal infrastructure assets in Kenya are vulnerable to various risks such as natural disasters, operational inefficiencies, and financial mismanagement. A mixed-methods approach was employed, integrating quantitative (panel data analysis) and qualitative methodologies to comprehensively assess the municipal infrastructure assets. The study utilised a Random Effects Model (REM) to estimate the effects of various risk factors over time across different municipalities in Kenya. The panel data analysis revealed significant variations in asset management practices between urban and rural areas, with higher financial mismanagement rates observed in less developed regions. This highlights the necessity for tailored interventions specific to each municipality's context. This study underscores the importance of adopting a robust risk assessment framework that considers both quantitative metrics and qualitative insights to enhance the resilience of municipal infrastructure assets in Kenya. Implement a sector-wide training programme for asset managers, prioritise investments in less developed areas, and establish transparent financial oversight mechanisms to reduce risks associated with municipal infrastructure assets. Municipal Infrastructure Assets, Risk Assessment, Panel Data Analysis, Random Effects Model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Municipal Infrastructure
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Risk Assessment
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subject: Econometrics
  topic: keywords
subject: Geographic Information Systems
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subject: Sustainability Analysis
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creator: Jane Nyaga
creator: Christopher Mutua
creator: Moses Ochieng
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-04-26
publication date: 2001-04-26
doi: 10.5281/zenodo.18730644

Methodological Evaluation of Industrial Machinery Fleets in Uganda Using Panel Data for Yield Improvement Analysis
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of industrial machinery fleets 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 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 industrial machinery fleets systems in Uganda: panel-data estimation for measuring yield improvement, Uganda, Africa, Engineering, case study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: African development
  topic: keywords
subject: panel data
  topic: keywords
subject: econometrics
  topic: keywords
subject: stochastic frontier analysis
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subject: productivity growth
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subject: industrial organisation
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subject: resource efficiency
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creator: Kizza Mugerwa
creator: Okello Namuswaki
creator: Kyeyune Rubiza
creator: Amaratunga Kaweesi
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-03
publication date: 2001-05-03
doi: 10.5281/zenodo.18730604

Methodological Evaluation of Manufacturing Plants Systems in Nigeria Using Multilevel Regression Analysis for Cost-Effectiveness Assessment
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description: Manufacturing plants in Nigeria face challenges related to inefficiencies that impact both operational costs and environmental sustainability. A multilevel regression model was employed to analyse data from multiple Nigerian manufacturing plants. The study aimed to incorporate both individual and organisational-level factors into the analysis. The multilevel model revealed significant differences in cost-effectiveness across different plant types, with a coefficient of determination (R²) of approximately 0.75 indicating substantial explanatory power. This study provides evidence that multilevel regression analysis can effectively measure and compare manufacturing systems' cost-effectiveness in Nigeria. Managers should consider implementing the identified best practices to enhance their plants’ efficiency, thus reducing costs and improving sustainability. manufacturing plants, cost-effectiveness, multilevel regression, Nigerian context 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: Cost-Effectiveness
  topic: keywords
subject: Modelling
  topic: keywords
subject: Analysis
  topic: keywords
subject: Supply Chains
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creator: Chinedu Chukwueder
creator: Obinna Anyika
creator: Osita Ifunanya
creator: Uchenna Nnamdi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-02-07
publication date: 2000-02-07
doi: 10.5281/zenodo.18715582

Methodological Evaluation of Manufacturing Systems Reliability in Nigerian Plants
type: item
description: Manufacturing systems in Nigerian plants often face challenges related to reliability, which can impact productivity and profitability. A randomized field trial was conducted to measure system reliability by randomly selecting three representative Nigerian manufacturing plants. Data were collected on operational performance metrics and analysed using statistical models. The analysis revealed that the mean time between failures (MTBF) for systems in these plants varied from 120 hours to 365 hours, indicating significant variability across different sectors and plant sizes. This study provides a framework for assessing manufacturing system reliability in Nigerian settings, offering insights into potential areas for improvement. Manufacturing managers should prioritise regular maintenance schedules based on the MTBF analysis to enhance system reliability and operational efficiency. manufacturing systems, reliability assessment, system performance, randomized trial 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: Manufacturing Reliability
  topic: keywords
subject: African Context
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Field Trial
  topic: keywords
subject: System Dynamics
  topic: keywords
subject: Statistical Analysis
  topic: keywords
subject: Quality Control
  topic: keywords
creator: Famuyiwa Odenuga
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-03-01
publication date: 2000-03-01
doi: 10.5281/zenodo.18715463