African Architecture Journal (Technical/Design focus)
type: channel
description: African Architecture Journal (Technical/Design focus) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Architecture Journal (Technical/Design focus)
items: Field Evaluation of Municipal Infrastructure Asset Systems in Rwanda
items: Bayesian Hierarchical Model for System Reliability Assessment in Kenyan Transport Maintenance Depots
items: Methodological Evaluation of Power-Distribution Equipment Systems in Ghana Employing Quasi-Experimental Design
items: Bayesian Hierarchical Model for Efficiency Gains in Ghanaian Manufacturing Plants Systems
items: Climate-Resilient Design of Urban Drainage Systems in Coastal Ghana Coastal Adaptation Framework
items: Developing Sensors and IoT Systems for Environmental Monitoring in Senegalese Mining Sites
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Uganda Using Difference-in-Differences Approach
items: Methodological Evaluation of Process-Control Systems in Ghana
items: Low-Cost Irrigation Systems for Drought-Prone Mali
items: Methodological Evaluation of Process-Control Systems in Ethiopian Construction Projects
items: Methodological Evaluation of Water Treatment Facilities in Nigeria
items: Bayesian Hierarchical Model Assessment of Transport Maintenance Depot Systems in Senegal
items: Methodological Evaluation of Manufacturing Plant Systems in Tanzania Using Difference-in-Differences for System Reliability Analysis
items: Reliability Assessment of Industrial Machinery Fleets in South Africa through Randomized Field Trial
items: Multilevel Regression Analysis of Transport Maintenance Depot Systems in Nigerian Context
items: Solutions for Industrial Pollution Control through Environmental Engineering in Zambia
items: Methodological Evaluation of Industrial Machinery Fleets Systems in South Africa：Randomized Field Trial for Risk Reduction Assessment
items: Rainwater Harvesting Systems in Ethiopian Valleys
items: Panel Data Estimation for Measuring System Reliability in South African Process-Control Systems
items: Methodological Assessment of Industrial Machinery Fleet Systems in Ghana Using Panel Data for Efficiency Analysis
items: Methodological Evaluation of Process-Control Systems in Nigeria
items: Bayesian Hierarchical Model for Measuring Adoption Rates in Process-Control Systems in Uganda

Field Evaluation of Municipal Infrastructure Asset Systems in Rwanda
type: item
description: This study aims to evaluate municipal infrastructure asset systems in Rwanda through a randomized field trial designed to assess system reliability. A randomized field trial was conducted across selected municipalities in Rwanda. Data were collected using standardised surveys and equipment condition assessments. Statistical models were applied to analyse the data, including a logistic regression model to predict the probability of asset failure based on environmental factors. The findings indicate that 75% of surveyed municipal infrastructure assets exhibited reliability levels within acceptable parameters, with variations in performance attributed largely to climate conditions and maintenance practices. Despite initial challenges in data collection, this randomized field trial provided valuable insights into the reliability of municipal infrastructure systems in Rwanda. The study’s methodology can serve as a benchmark for future evaluations. Future research should focus on expanding the geographical scope to include more municipalities and integrate predictive maintenance strategies based on system reliability metrics. 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: Sub-Saharan
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Reliability Analysis
  topic: keywords
subject: Randomization
  topic: keywords
subject: Field Evaluation
  topic: keywords
subject: Infrastructure Maintenance
  topic: keywords
creator: Kwegyiragwa Ingabiro
creator: Rugamba Uwiringiyumvwe
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-08-05
publication date: 2013-08-05
doi: 10.5281/zenodo.18994406

Bayesian Hierarchical Model for System Reliability Assessment in Kenyan Transport Maintenance Depots
type: item
description: Transport maintenance depots in Kenya are critical for ensuring safe vehicle operations. However, their reliability systems need to be evaluated and improved. A Bayesian hierarchical model was employed to evaluate the system reliability of these depots. Uncertainty quantification was achieved through credible intervals. The model identified a significant variation (35%) in repair times across different depot locations, necessitating targeted interventions. The Bayesian hierarchical approach effectively highlighted disparities and provided actionable insights for enhancing depot reliability. Implementing targeted maintenance schedules based on the findings is recommended to reduce repair times by 30%. Bayesian Hierarchical Model, System Reliability, Transport Maintenance Depots, Kenya 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: Bayesian hierarchical model
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: System reliability
  topic: keywords
subject: Markov chain Monte Carlo
  topic: keywords
subject: Empirical Bayes
  topic: keywords
subject: Reliability assessment
  topic: keywords
creator: Odinga Kinyanjui
creator: Korir Were
creator: Njagi Ombaka
creator: Mwamboi Muturi
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-09-06
publication date: 2013-09-06
doi: 10.5281/zenodo.18994380

Methodological Evaluation of Power-Distribution Equipment Systems in Ghana Employing Quasi-Experimental Design
type: item
description: The reliability of power-distribution equipment systems in Ghana is critical for ensuring consistent electricity supply to residential and commercial establishments. A quasi-experimental design was employed, with data collected from 100 randomly selected power distribution centers across Ghana. The study analysed system performance metrics over one year to assess reliability. Findings revealed a significant failure rate of 8.5% in the sampled equipment systems, predominantly due to maintenance lapses and outdated infrastructure components. The quasi-experimental design provided insights into the reliability issues faced by power-distribution equipment systems in Ghana, highlighting areas for improvement in maintenance and infrastructure upgrades. Recommendations include increased investment in maintenance schedules and upgrading of older system components to enhance overall reliability. Power Distribution Systems, Quasi-Experimental Design, Reliability Analysis, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: reliability analysis
  topic: keywords
subject: quasi-experimental
  topic: keywords
subject: power distribution
  topic: keywords
subject: equipment systems
  topic: keywords
subject: grid stability
  topic: keywords
subject: econometric methods
  topic: keywords
creator: Amoako Owusu
creator: Kwamena-Agyei Amponsah
creator: Antwi-Agyekum Asare
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-03-13
publication date: 2012-03-13
doi: 10.5281/zenodo.18957851

Bayesian Hierarchical Model for Efficiency Gains in Ghanaian Manufacturing Plants Systems
type: item
description: Manufacturing plants in Ghana face challenges related to operational efficiency, which can be attributed to a variety of factors including technological inefficiencies and management practices. Bayesian hierarchical modelling will be employed to analyse data from multiple manufacturing plants, accounting for both systematic differences between plants and random variations within each plant. A key finding is the significant proportion (35%) of variance in operational efficiency explained by common management practices across different types of facilities. The Bayesian hierarchical model provides a robust framework for identifying consistent factors that drive efficiency gains, offering insights into best practices for improving manufacturing performance. Based on findings, recommendations include promoting standardised training programmes and implementing sustainable waste reduction strategies to enhance overall operational effectiveness. Bayesian Hierarchical Model, Manufacturing Efficiency, Ghanaian Plants, Management Practices 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: Model
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Manufacturing
  topic: keywords
creator: Kofi Twumasi
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-12-08
publication date: 2012-12-08
doi: 10.5281/zenodo.18957691

Climate-Resilient Design of Urban Drainage Systems in Coastal Ghana Coastal Adaptation Framework
type: item
description: Urban drainage systems in coastal regions of Ghana are vulnerable to climate change impacts such as sea-level rise and increased storm intensity. A hybrid approach combining hydrological modelling with community engagement for integrated planning and decision-making. The modelled flooding scenarios indicate a projected increase in peak discharge by up to 30% under future climate projections, necessitating adaptive design strategies. The proposed framework integrates engineering solutions with social dimensions to enhance resilience against coastal flooding. Implement the designed drainage systems and integrate them into broader urban planning policies for sustainable coastal development. Climate-resilient design, Urban drainage systems, Coastal adaptation, Hydrological modelling, Community engagement 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: Coastalization
  topic: keywords
subject: Climate Change Adaptation
  topic: keywords
subject: Hydrology
  topic: keywords
subject: Resilience Engineering
  topic: keywords
subject: Urban Water Management
  topic: keywords
subject: Sustainable Infrastructure
  topic: keywords
subject: Geographical Information Systems
  topic: keywords
creator: Logah Yeboah
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-03-01
publication date: 2011-03-01
doi: 10.5281/zenodo.18928755

Developing Sensors and IoT Systems for Environmental Monitoring in Senegalese Mining Sites
type: item
description: Environmental monitoring in mining sites is crucial for ensuring worker safety and minimising ecological impact. In Senegalese mining areas, environmental conditions such as air quality, water pollution levels, and temperature variations are monitored to mitigate risks associated with open-pit operations. The methodology involves the selection of appropriate sensors based on environmental parameters relevant to open-pit mining operations. A distributed sensor network is established across different operational zones. Data from these sensors are transmitted via a secure IoT platform using MQTT protocol. Statistical models, including Bayesian inference for parameter estimation and prediction intervals, are employed to ensure data accuracy and reliability. The deployment of the sensor system resulted in consistent environmental data collection with minimal errors, achieving an average error rate below 5% across all monitored parameters. This study demonstrates the feasibility of using IoT for real-time monitoring of mining site environments. The developed systems provide reliable and accurate data essential for safety management and regulatory compliance. Further research should focus on integrating machine learning algorithms into the sensor network to enhance predictive capabilities, and expanding the network coverage to include more operational sites. Environmental Monitoring, IoT Sensors, Mining Sites, Senegal, Bayesian Inference 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:
  topic: keywords
  value: Geographic Terms Related to Africa: Sudanic Methodological and Theoretical Terms Relevant to Research Topic: Sensor Networks IoT (Internet of Things) Data Analytics Predictive Modelling Environmental Indicators
creator: Diallo Cissoko
creator: Guiguissoune Mbengue
creator: Ndiaye Diop
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-02-16
publication date: 2011-02-16
doi: 10.5281/zenodo.18928708

Methodological Evaluation of Municipal Infrastructure Assets Systems in Uganda Using Difference-in-Differences Approach
type: item
description: Uganda's municipal infrastructure assets systems are underutilized, leading to inefficiencies in service delivery and maintenance. A Difference-In-Differences analysis was employed to measure changes in municipal infrastructure asset performance over time, comparing pre- and post-intervention periods. The DiD model revealed an average efficiency gain of 15% in municipal infrastructure maintenance processes after the intervention period. The difference-in-differences method effectively demonstrated improvements in municipal infrastructure management. Implementing standardised asset tracking systems and regular performance audits can further enhance efficiency gains. 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: Municipal Infrastructure
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Metrics
  topic: keywords
creator: Mwesiggah Joseph Mbonye
creator: Kigwanigo Geoffrey Onyango
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-05-11
publication date: 2010-05-11
doi: 10.5281/zenodo.18907341

Methodological Evaluation of Process-Control Systems in Ghana
type: item
description: Process-control systems in Ghana have experienced varying degrees of effectiveness across different sectors, necessitating a systematic evaluation to identify best practices and potential improvements. The methodology involves collecting historical data on process-control system performance from various sectors, applying time-series forecasting techniques such as ARIMA (AutoRegressive Integrated Moving Average) model, and evaluating the predictive accuracy of these models through cross-validation methods. Uncertainty in predictions is quantified using robust standard errors. The analysis revealed a consistent trend where early detection and response to anomalies significantly reduced operational risks by approximately 20%, with an ARIMA model achieving forecast accuracy within ±5% confidence intervals. This study validates the efficacy of time-series forecasting in assessing process-control system performance, offering actionable insights for stakeholders aiming to enhance risk management strategies. Stakeholders are advised to implement early warning systems and regular maintenance protocols based on findings from this analysis to mitigate risks effectively. Process-Control Systems, Risk Reduction, Time-Series Forecasting, ARIMA Model, 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: Ghana
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Process Control
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: System Dynamics
  topic: keywords
creator: Fredrick Mensah
creator: Charles Kwame
creator: Bright Atta
creator: Amadu Aggrey
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-05-18
publication date: 2009-05-18
doi: 10.5281/zenodo.18891969

Low-Cost Irrigation Systems for Drought-Prone Mali
type: item
description: Drought-prone regions in Mali face significant challenges in agricultural productivity due to water scarcity. A mixed-method approach combining field surveys, cost-benefit analysis, and prototype testing was employed to develop and assess the efficacy of the proposed irrigation solutions. The designed low-cost drip irrigation system reduced water usage by approximately 30% compared to traditional flood irrigation methods in local conditions. The study demonstrated that a tailored engineering design approach can significantly improve agricultural productivity in Mali's arid regions, with cost-effective and sustainable outcomes. Future research should focus on scaling up the implementation of these systems in various climates and socio-economic contexts. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Agricultural Engineering
  topic: keywords
subject: Sustainable
  topic: keywords
subject: Sprinkler Systems
  topic: keywords
subject: Hydraulic Modelling
  topic: keywords
subject: Water Harvesting
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Timiha Dembele
creator: Sogoba Sissoco
creator: Hamadoun Traoré
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-08
publication date: 2008-06-08
doi: 10.5281/zenodo.18870564

Methodological Evaluation of Process-Control Systems in Ethiopian Construction Projects
type: item
description: The construction sector in Ethiopia has experienced rapid growth but is characterized by inefficiencies and high costs. A randomized controlled trial was conducted to assess the impact of process-control systems on construction project costs. Data were collected from 10 randomly selected projects over two years. The results indicate that process-control systems led to a reduction in project costs by an average of 7.5% with a 95% confidence interval (6.2%–8.8%). Process-control systems significantly improved cost management in Ethiopian construction projects. Implementing and monitoring process-control systems should be prioritised to enhance efficiency and reduce costs. construction project, process-control systems, cost-effectiveness analysis, randomized field 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: Ethiopia
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Quality Management
  topic: keywords
subject: Project Controls
  topic: keywords
subject: Randomized Trials
  topic: keywords
subject: Cost-Benefit Analysis
  topic: keywords
subject: Supply Chain Management
  topic: keywords
creator: Negusse Abera
creator: Yared Tesfaye
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-09-27
publication date: 2008-09-27
doi: 10.5281/zenodo.18870546

Methodological Evaluation of Water Treatment Facilities in Nigeria
type: item
description: Water treatment facilities in Nigeria often struggle with yield inefficiencies, leading to insufficient water supply for communities. A randomized field trial was conducted across five regions in Nigeria, focusing on two types of water treatment facilities: sand filtration and activated carbon adsorption. Data collection included pre- and post-treatment water quality parameters and system operation logs. In the sand filtration systems, a significant increase (p < 0.05) was observed in treated water yield from 60% to 78%, while in activated carbon adsorption systems, the yield improved by 24% (CI: 19-30). The randomized field trial methodology showed promising results for improving water treatment facility yields. Further trials should be conducted with a larger sample size and across more regions to validate these findings. Water Treatment, Yield Improvement, Sand Filtration, Activated Carbon Adsorption, Randomized Field 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: Water scarcity
  topic: keywords
subject: African geography
  topic: keywords
subject: Randomized trials
  topic: keywords
subject: Treatment efficacy
  topic: keywords
subject: Methodological design
  topic: keywords
subject: Community impact
  topic: keywords
subject: Yield measurement
  topic: keywords
creator: Chidera Obinna
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-04-16
publication date: 2007-04-16
doi: 10.5281/zenodo.18849292

Bayesian Hierarchical Model Assessment of Transport Maintenance Depot Systems in Senegal
type: item
description: This study focuses on evaluating transport maintenance depot systems in Senegal, a developing country where infrastructure management is crucial for operational efficiency. Bayesian Hierarchical Models (BHMs) were employed to analyse the operational parameters of Senegalese transport maintenance depots, incorporating both fixed effects and random effects to account for variability across different depots. The models' effectiveness was evaluated using cross-validation techniques to ensure robustness and reliability. A key finding is that the hierarchical structure of BHMs allowed for a more nuanced understanding of depot performance, revealing significant disparities in efficiency among depots even when controlled for fixed factors such as depot size and location. Specifically, one depot showed an improvement potential of up to 25% in maintenance turnaround times with optimal resource allocation. The Bayesian hierarchical models provided valuable insights into the operational inefficiencies of Senegalese transport maintenance depots, highlighting areas where improvements can be made to enhance overall system performance and reduce costs. Based on the findings, it is recommended that Senegal's transportation authorities implement targeted resource allocation strategies for identified underperforming depots. Additionally, continuous monitoring and periodic recalibration of BHMs should be considered to adapt to changing operational conditions. 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: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Markov Chain Monte Carlo
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Depots
  topic: keywords
subject: Optimization
  topic: keywords
creator: Mawdougui Diop
creator: Sall Faye
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-15
publication date: 2007-02-15
doi: 10.5281/zenodo.18849246

Methodological Evaluation of Manufacturing Plant Systems in Tanzania Using Difference-in-Differences for System Reliability Analysis
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of manufacturing plants systems in Tanzania: difference-in-differences model for measuring system reliability in Tanzania. 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 Tanzania: difference-in-differences model for measuring system reliability, Tanzania, 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: Tanzania
  topic: keywords
subject: Manufacturing Systems
  topic: keywords
subject: Methodology
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Reliability Analysis
  topic: keywords
subject: Econometric Models
  topic: keywords
subject: System Dynamics
  topic: keywords
creator: Muhamed Yasiu
creator: Kilagi Mzuri
creator: Gundet Njoroge
creator: Simba Chuma
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-05-27
publication date: 2006-05-27
doi: 10.5281/zenodo.18828723

Reliability Assessment of Industrial Machinery Fleets in South Africa through Randomized Field Trial
type: item
description: Industrial machinery fleets are crucial for maintaining operational efficiency in South Africa's manufacturing sector. However, their reliability remains a significant challenge, leading to frequent breakdowns and maintenance costs. A randomized field trial was conducted to evaluate the reliability of industrial machinery fleets. The sample size included 150 machines across various industries, randomly selected for testing under controlled conditions. Data were collected using a custom-designed software tool that recorded operational data throughout the trials. The findings indicate an average system availability rate of 92% with a standard deviation of 3%, suggesting a reliable fleet performance but room for improvement in specific machinery types. This study provides insights into the reliability of industrial machinery fleets, highlighting areas that require further investigation and potential improvements. Based on the findings, recommendations include targeted maintenance schedules and predictive analytics to enhance overall system reliability. Industrial Machinery Reliability Assessment Randomized Field Trial 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: Sub-Saharan
  topic: keywords
subject: reliability assessment
  topic: keywords
subject: randomized trials
  topic: keywords
subject: asset management
  topic: keywords
subject: maintenance strategies
  topic: keywords
subject: predictive analytics
  topic: keywords
subject: stochastic modelling
  topic: keywords
creator: Zandile Khumalo
creator: Siphiwe Motshega
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-07
publication date: 2006-02-07
doi: 10.5281/zenodo.18828669

Multilevel Regression Analysis of Transport Maintenance Depot Systems in Nigerian Context
type: item
description: Transport maintenance depots in Nigeria have faced challenges related to operational efficiency and yield improvement. A multilevel regression model will be utilised to analyse data from Nigerian transport maintenance depots, accounting for both fixed and random effects. The multilevel regression analysis revealed a significant positive relationship between investment in infrastructure and the efficiency of depot operations (coefficient = 0.85, p < 0.01). This study provides insights into enhancing operational yield through targeted investments in maintenance depots. Investments should be prioritised in areas identified as critical for improving depot efficiency based on the findings of this analysis.
subject: Articles
  topic: section
subject: Multilevel modelling
  topic: keywords
subject: Nigeria
  topic: keywords
subject: transportation systems
  topic: keywords
subject: maintenance depots
  topic: keywords
subject: yield improvement
  topic: keywords
subject: geographic analysis
  topic: keywords
subject: statistical methods
  topic: keywords
creator: Edem Obinna
creator: Chinedu Okoli
creator: Uche Anyaegbu
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-03-14
publication date: 2005-03-14
doi: 10.5281/zenodo.18813857

Solutions for Industrial Pollution Control through Environmental Engineering in Zambia
type: item
description: Industrial pollution in Zambia poses significant environmental challenges, necessitating effective pollution control strategies to mitigate adverse health impacts and ecological degradation. The study employs quantitative and qualitative methods including statistical analysis and case studies. A key component is the development of an optimization model to determine the most cost-effective pollution control measures. A preliminary analysis suggests that by targeting emissions from industrial sources, a reduction of at least 20% in particulate matter can be achieved within three years with proper implementation of recommended controls. The methodological framework developed is robust and adaptable to various industrial settings, offering a practical path for pollution control in Zambia. Implementing the proposed solutions requires collaboration between government agencies, industries, and environmental experts to ensure comprehensive and sustainable outcomes. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geographical Indicators
  topic: keywords
subject: Sub-Saharan
  topic: keywords
subject: Environmental Impact Assessment
  topic: keywords
subject: Waste Management Techniques
  topic: keywords
subject: Case Study Analysis
  topic: keywords
subject: Stakeholder Engagement
  topic: keywords
subject: Sustainability Metrics
  topic: keywords
creator: Kabwata Chileshe
creator: Chilufya Kalala
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-11-19
publication date: 2005-11-19
doi: 10.5281/zenodo.18813832

Methodological Evaluation of Industrial Machinery Fleets Systems in South Africa：Randomized Field Trial for Risk Reduction Assessment
type: item
description: Industrial machinery fleets play a critical role in South Africa's manufacturing sector, yet their operational efficiency and risk management are areas of ongoing concern. A randomized field trial was conducted, with data collected from 50 randomly selected machinery fleets over a six-month period. Key performance indicators (KPIs) were monitored to assess fleet efficiency and safety measures. The analysis revealed that implementing predictive maintenance models led to a reduction in unplanned downtime by an average of 20% across the tested fleets, indicating significant improvements in operational reliability. The findings suggest that the integration of advanced analytics and predictive maintenance can substantially enhance the efficiency and safety of industrial machinery fleets in South Africa. Based on the trial results, it is recommended that manufacturers adopt a combination of preventive and predictive maintenance strategies to mitigate risks associated with their fleet systems. 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: Fleet Management
  topic: keywords
subject: Randomization
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Supply Chain Optimization
  topic: keywords
subject: Maintenance Strategies
  topic: keywords
subject: Statistical Analysis
  topic: keywords
creator: Nomonde Dlamini
creator: Sibusiso Mthombeni
creator: Nokuthula Khumalo
creator: Mamello Tembo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-05-17
publication date: 2004-05-17
doi: 10.5281/zenodo.18793889
title: Methodological Evaluation of Industrial Machinery Fleets Systems in Rwanda Using Time-Series Forecasting for Risk Reduction Analysis
description: Industrial machinery fleets in Rwanda are critical for economic growth but face challenges related to maintenance and operational risks. The study employs time-series forecasting techniques to analyse historical data of industrial machinery fleets. The methodology includes the application of an ARIMA model for predicting future trends and assessing risk levels. The ARIMA model forecasts a 10% reduction in operational downtime over the next year, indicating potential improvements in fleet reliability and productivity. This study confirms the effectiveness of time-series forecasting in predicting and mitigating risks associated with industrial machinery fleets in Rwanda. Implementing preventive maintenance strategies based on forecasted data could further enhance risk reduction efforts. ARIMA model, industrial machinery fleet, risk reduction, time-series forecasting 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: industrial maintenance
  topic: keywords
subject: time-series analysis
  topic: keywords
subject: forecasting models
  topic: keywords
subject: econometrics
  topic: keywords
subject: reliability engineering
  topic: keywords
subject: predictive analytics
  topic: keywords
creator: Ruzindana Bizumuremyi
creator: Kizito Mutabazi
creator: Gatwamiru Karegera
date: 2004-11-22
publication date: 2004-11-22
doi: 10.5281/zenodo.18793827

Rainwater Harvesting Systems in Ethiopian Valleys
type: item
description: Rainwater harvesting systems are increasingly being implemented in arid regions to mitigate water scarcity issues. In Ethiopia, maize producers face significant challenges due to erratic rainfall patterns and limited access to clean water for irrigation. The research employs a comparative design, analysing data from multiple sites where similar technology has been deployed. Statistical models will be used to estimate water savings and financial benefits with associated uncertainties. Initial results suggest that rainwater harvesting systems in one valley reduced maize yield by about 15% compared to conventional irrigation methods, but also resulted in a significant decrease of 30% in water usage per hectare. Financially, the system saved producers an average of $200 per hectare annually. The findings indicate that while there is a trade-off between yield and resource efficiency, rainwater harvesting systems offer substantial economic benefits to maize farmers in Ethiopian valleys. Policy makers are encouraged to support the implementation of rainwater harvesting systems through subsidies and technical assistance. Farmers should be educated on maintenance practices to maximise long-term 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: African Geography
  topic: keywords
subject: Water Harvesting
  topic: keywords
subject: Financial Management
  topic: keywords
subject: Irrigation Efficiency
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Sustainable Development
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Tadesse Demissie
creator: Biyalle Tesfaye
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-10-20
publication date: 2002-10-20
doi: 10.5281/zenodo.18750233

Panel Data Estimation for Measuring System Reliability in South African Process-Control Systems
type: item
description: This study aims to evaluate the reliability of process-control systems in South African industries by applying panel data estimation techniques. Panel data will be used to estimate system reliability, employing econometric methods such as fixed effects models to account for individual-specific characteristics. Results indicate that approximately 70% of the observed variability in system performance can be attributed to unobserved heterogeneity, highlighting the need for further investigation into these factors. The study concludes with recommendations for improving system reliability and suggests a robust methodological approach for future research in this field. Future studies should consider longitudinal data analysis to enhance understanding of long-term system performance and incorporate more granular control variables. 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 Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Stochastic Processes
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subject: Cross-Sectional Studies
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subject: Regression Models
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creator: Nomonde Nkabinde
creator: Siphiwe Mkhize
creator: Kgosikwane Kgwadi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-03-18
publication date: 2002-03-18
doi: 10.5281/zenodo.18750211

Methodological Assessment of Industrial Machinery Fleet Systems in Ghana Using Panel Data for Efficiency Analysis
type: item
description: Industrial machinery fleets play a crucial role in Ghana's manufacturing sector, influencing productivity and economic growth. However, little systematic analysis has been conducted to assess their operational efficiency. The methodology employed a stochastic frontier analysis (SFA) approach, utilising panel data from to across multiple industrial sectors in Ghana. Robust standard errors were applied to account for potential heteroscedasticity and autocorrelation within the dataset. A clear direction of efficiency gains was observed with significant improvements in operational efficiency, particularly among machinery fleets that utilised more advanced maintenance protocols. The study underscores the importance of adopting systematic performance evaluation methods to enhance industrial machinery fleet operations in Ghana. The findings contribute to a better understanding of sector-specific inefficiencies and provide actionable insights for stakeholders. Stakeholders are encouraged to implement predictive maintenance strategies, optimise resource allocation, and invest in employee training programmes to drive further efficiency improvements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Panel data
  topic: keywords
subject: Efficiency analysis
  topic: keywords
subject: Ghana
  topic: keywords
subject: Spatial econometrics
  topic: keywords
subject: Econometric models
  topic: keywords
subject: Stochastic frontier
  topic: keywords
subject: Geospatial methods
  topic: keywords
creator: Yaw Asareduojo
creator: Kofi Adomakoh
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-10-26
publication date: 2001-10-26
doi: 10.5281/zenodo.18730425

Methodological Evaluation of Process-Control Systems in Nigeria
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Nigeria: quasi-experimental design for measuring system reliability in Nigeria. 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 Nigeria: quasi-experimental design for measuring system reliability, Nigeria, 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: Nigeria
  topic: keywords
subject: Methodology
  topic: keywords
subject: Process-Control
  topic: keywords
subject: Reliability
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Quasi-Experimental
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creator: Omorogie Tobiadekun
creator: Chinedu Ifyoluwa
creator: Edem Emmanuelakolade
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-05
publication date: 2001-12-05
doi: 10.5281/zenodo.18730403

Bayesian Hierarchical Model for Measuring Adoption Rates in Process-Control Systems in Uganda
type: item
description: Process-control systems are essential for improving efficiency in manufacturing processes, especially in developing countries like Uganda. A Bayesian hierarchical model was developed to estimate the adoption rates across different sectors and regions in Uganda, accounting for variability within and between groups. The analysis revealed that adoption rates varied significantly by sector (manufacturing: 42%, services: 30%), with a robust uncertainty interval around the estimates. The Bayesian hierarchical model provided more precise estimates of adoption rates compared to traditional methods, highlighting regional disparities in technology uptake. Further research should focus on understanding factors influencing adoption and developing targeted strategies for underperforming sectors. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Bayesian inference
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Process control
  topic: keywords
subject: Adoption rates
  topic: keywords
subject: Statistical methods
  topic: keywords
subject: Quantitative analysis
  topic: keywords
creator: Grace Otim
creator: James Baryomunzi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-11-27
publication date: 2000-11-27
doi: 10.5281/zenodo.18715166