African Industrial Engineering
type: channel
description: African Industrial 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 Industrial Engineering
items: Methodological Evaluation of Manufacturing Systems in Rwanda Through Cost-Effectiveness Analysis
items: Methodological Assessment of Manufacturing Systems Reliability in Ugandan Enterprises
items: Evaluating Transport Maintenance Depot Systems in Rwanda through Quasi-Experimental Design
items: Multilevel Regression Analysis of Manufacturing System Reliability in Nigerian Plants
items: Methodological Assessment and Panel Data Estimation of Manufacturing Plant Systems in South Africa
items: Bayesian Hierarchical Model for Evaluating Efficiency Gains in Power-Distribution Equipment Systems in Ghana
items: Biomedical Innovations in Diagnostic Devices for Resource-Limited Settings in Uganda, 2009
items: Methodological Assessment of Process-Control Systems in Nigerian Industries Using Quasi-Experimental Design
items: Methodological Assessment of Power-Distribution Equipment Systems in Ghana Using Panel Data for Yield Improvement Analysis
items: Methodological Evaluation of Process-Control Systems for Yield Improvement in Senegal Using Time-Series Forecasting Models
items: Bayesian Hierarchical Model Assessment of Water Treatment Efficiency in Rwanda,
items: Multilevel Regression Analysis of Power-Distribution Equipment Adoption in Ghana
items: Environmental Engineering Strategies for Industrial Pollution Control in Zambia 2006
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Tanzania
items: Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Angola
items: Climate-Resilient Design Strategies for Urban Drainage in Coastal Ghana
items: Bayesian Hierarchical Model for Evaluating System Reliability in Ghanaian Manufacturing Plants
items: Methodological Assessment of Industrial Machinery Fleet Systems in Ghana
items: Time-Series Forecasting Model for Evaluating System Reliability in Senegalese Industrial Machinery Fleets
items: Methodological Evaluation of Process-Control Systems in Kenya Using Difference-in-Differences Approach for Risk Reduction Measurement
items: Biomedical Engineering Innovations in Diagnostic Devices for Resource-Limited Settings in Equatorial Guinea
items: Bayesian Hierarchical Model for Risk Reduction in Senegalese Transport Maintenance Depots Systems
items: Methodological Evaluation of Process-Control Systems in Uganda Using Time-Series Forecasting for Risk Reduction Measurement
items: Methodological Evaluation of Industrial Machinery Fleets Systems in Tanzania

Methodological Evaluation of Manufacturing Systems in Rwanda Through Cost-Effectiveness Analysis
type: item
description: Manufacturing systems in Rwanda face challenges related to operational efficiency and cost-effectiveness. A randomized field trial was conducted across selected manufacturing plants. Data were collected using quantitative methods for analysis. The study identified that implementing lean management techniques reduced production costs by an average of 15% (p < 0.05). Lean management practices significantly improved cost-effectiveness in Rwanda's manufacturing sector. Manufacturers should adopt lean management strategies to enhance efficiency and reduce expenses. manufacturing systems, cost-effectiveness analysis, randomized field trial, lean management, 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: Manufacturing Systems
  topic: keywords
subject: Cost-Effectiveness Analysis
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: African Development Studies
  topic: keywords
subject: Lean Manufacturing
  topic: keywords
subject: Statistical Process Control
  topic: keywords
creator: Ingabirongo Kizito
creator: Kabuye Haryline
creator: Rakoto Remy
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-06-10
publication date: 2012-06-10
doi: 10.5281/zenodo.18959527

Methodological Assessment of Manufacturing Systems Reliability in Ugandan Enterprises
type: item
description: Manufacturing systems in Ugandan enterprises are critical for economic growth but often face reliability challenges. A mixed-method approach was employed with quantitative data analysis and qualitative interviews to assess system performance and identify improvement strategies. The analysis revealed that 75% of systems exhibited moderate to high reliability levels, indicating potential for further enhancement through targeted interventions. This study underscores the need for tailored support programmes in Ugandan manufacturing sectors to improve system reliability and productivity. Ugandan enterprises should prioritise investment in maintenance and training to maintain optimal system performance. manufacturing systems, reliability, quasi-experimental design, Ugandan enterprises 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: reliability
  topic: keywords
subject: assessment
  topic: keywords
subject: methodology
  topic: keywords
subject: ergonomics
  topic: keywords
subject: analytics
  topic: keywords
creator: Kizza Kivebe
creator: Opinya Opalakai
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-08-20
publication date: 2012-08-20
doi: 10.5281/zenodo.18959468

Evaluating Transport Maintenance Depot Systems in Rwanda through Quasi-Experimental Design
type: item
description: Rwanda's transport system faces challenges in maintaining vehicles efficiently, leading to potential inefficiencies in logistics and service delivery. A mixed-method approach combining quantitative data analysis with qualitative insights was employed. The study utilised a difference-in-differences (DID) model to measure the impact and efficiency of TMDs over time. The DID model revealed that the average cost per vehicle maintenance at depots decreased by approximately 15% compared to pre-deployment levels, indicating improved operational efficiencies. This study provides robust evidence on the effectiveness of TMDs in reducing maintenance costs and enhancing service delivery in Rwanda's transport sector. The findings suggest that further investments should be directed towards optimising depot operations and expanding coverage to serve a wider geographic area. 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: Maintenance
  topic: keywords
subject: Quasi-Experimental
  topic: keywords
subject: Logistics
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Resource Allocation
  topic: keywords
subject: Performance Measurement
  topic: keywords
creator: Nyaruka Masiko
creator: Kizito Nkubi
creator: Kabagwirwa Mushimbi
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-05-25
publication date: 2011-05-25
doi: 10.5281/zenodo.18929440

Multilevel Regression Analysis of Manufacturing System Reliability in Nigerian Plants
type: item
description: Manufacturing systems in Nigerian plants are critical for economic development, yet their reliability is often underexplored. A multilevel logistic regression model was applied to data from 100 plants across Nigeria. The model accounts for both plant-level and industry-level factors affecting system reliability. The estimated odds ratio for one unit increase in the number of maintenance personnel per machine is 1.2 (95% CI: 1.0, 1.4), indicating a moderate positive effect on reliability. Multilevel regression analysis provides robust insights into factors influencing manufacturing system reliability in Nigerian plants. Future studies should consider the application of this methodological approach to other industrial sectors and contexts. multilevel regression, manufacturing systems, reliability, Nigeria 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: manufacturing systems
  topic: keywords
subject: multilevel models
  topic: keywords
subject: reliability analysis
  topic: keywords
subject: statistical methods
  topic: keywords
subject: logistic regression
  topic: keywords
subject: hierarchical data analysis
  topic: keywords
creator: Sunday Oluwasanobi
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-10-22
publication date: 2011-10-22
doi: 10.5281/zenodo.18929408

Methodological Assessment and Panel Data Estimation of Manufacturing Plant Systems in South Africa
type: item
description: Manufacturing plants in South Africa face significant operational challenges that affect productivity and competitiveness. The study employs mixed-methods including econometric analysis with the Fixed Effects (FE) model. Uncertainty is addressed through robust standard errors. Panel-data estimation revealed a moderate adoption rate of advanced manufacturing technologies in South African plants, indicating potential for further technological integration. This research provides foundational insights into methodological approaches for assessing and enhancing manufacturing systems in South Africa. Further studies should explore the specific factors influencing technology adoption among different sectors and regions within South Africa. Manufacturing, Panel data, Econometrics, 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: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Panel-Data
  topic: keywords
subject: Methodology
  topic: keywords
subject: Productivity
  topic: keywords
subject: Fixed-effects
  topic: keywords
creator: Sipho Mkhize
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-01-21
publication date: 2010-01-21
doi: 10.5281/zenodo.18907953

Bayesian Hierarchical Model for Evaluating Efficiency Gains in Power-Distribution Equipment Systems in Ghana
type: item
description: Power distribution systems in Ghana face challenges related to efficiency, reliability, and cost-effectiveness. A Bayesian hierarchical model was employed to analyse data from multiple sites across Ghana, accounting for variability in system performance due to geographical and operational differences. The analysis revealed significant efficiency gains ranging between 10% and 25%, with notable improvements observed in rural areas where the initial inefficiencies were highest. Bayesian hierarchical modelling provided a nuanced understanding of efficiency across different regions, highlighting specific equipment types that require further optimization. Targeted interventions should focus on upgrading certain equipment models and improving maintenance practices in high-inefficiency zones. Power distribution systems, Bayesian hierarchical model, efficiency gains, 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: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Monte Carlo
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Optimization
  topic: keywords
subject: Africa
  topic: keywords
creator: Abena Kwasi
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-06-04
publication date: 2010-06-04
doi: 10.5281/zenodo.18907943

Biomedical Innovations in Diagnostic Devices for Resource-Limited Settings in Uganda, 2009
type: item
description: Uganda faces challenges in accessing affordable and reliable diagnostic devices for healthcare providers in resource-limited settings. In-depth interviews with researchers involved in the development of diagnostic devices were conducted. Data collection focused on qualitative insights into innovation processes and outcomes. Participants reported that the new diagnostic device reduced healthcare costs by $5 per test, achieving a success rate of 90% in field trials compared to traditional methods. The study underscores the importance of local biomedical engineering expertise for developing cost-effective solutions to global health challenges. Further research should explore scalability and sustainability of these innovations in diverse settings across Africa. biomedical engineering, diagnostic devices, resource-limited settings, 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: Biomedical Engineering
  topic: keywords
subject: Diagnostic Devices
  topic: keywords
subject: Microfluidics
  topic: keywords
subject: Resource Allocation
  topic: keywords
subject: Sustainability Models
  topic: keywords
subject: Third-World Health Systems
  topic: keywords
creator: Omar Kizza
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-01-03
publication date: 2009-01-03
doi: 10.5281/zenodo.18893520

Methodological Assessment of Process-Control Systems in Nigerian Industries Using Quasi-Experimental Design
type: item
description: Process-control systems (PCSs) are essential for improving efficiency in industrial settings across Nigeria. However, their effectiveness varies widely and is often influenced by contextual factors such as industry type, technological infrastructure, and management practices. A mixed-method approach was employed, combining quantitative analysis (using a difference-in-differences regression model) with qualitative insights from interviews and surveys. Data were collected from a sample of 50 industrial plants randomly selected to represent various industries in Nigeria. The difference-in-differences regression revealed an average increase of 18% in process efficiency post-PCS implementation, though these gains varied significantly across sectors (e.g., manufacturing vs. services). This study provides empirical evidence that PCSs can lead to substantial improvements in industrial processes in Nigeria, although sector-specific adaptations are required. Industrial policymakers and managers should prioritise the adoption of PCSs alongside targeted interventions tailored to specific industry needs for optimal efficiency gains. Process-Control Systems, Quasi-Experimental Design, Industrial Efficiency, Nigeria 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 Africa
  topic: keywords
subject: Methodology
  topic: keywords
subject: Process-Control Systems
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Efficiency Measurement
  topic: keywords
subject: Industrial Engineering
  topic: keywords
subject: Evaluation Techniques
  topic: keywords
creator: Obioma Idahan
creator: Uche Ikemba
creator: Chinedu Nwosu
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-08-01
publication date: 2009-08-01
doi: 10.5281/zenodo.18893494

Methodological Assessment of Power-Distribution Equipment Systems in Ghana Using Panel Data for Yield Improvement Analysis
type: item
description: Power distribution equipment (PDE) systems in Ghana are critical for ensuring reliable electricity supply to industrial and commercial sectors. Panel data analysis was employed using econometric techniques to model the relationship between PDE system performance and industrial output. Robust standard errors were used for inference. The analysis revealed that optimising PDE systems can lead to an average increase of 15% in industrial productivity, with significant variability across different sectors. This study provides a robust framework for evaluating PDE system performance and offers actionable insights for enhancing yield in Ghanaian industries. Investment in upgrading and modernizing PDE systems is recommended to achieve sustained yield improvements. Sector-specific interventions are also suggested based on sectoral productivity data. 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: Sub-Saharan
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Distribution Systems
  topic: keywords
subject: Energy Policies
  topic: keywords
creator: Logah Agyeiwa
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-02-12
publication date: 2008-02-12
doi: 10.5281/zenodo.18870979

Methodological Evaluation of Process-Control Systems for Yield Improvement in Senegal Using Time-Series Forecasting Models
type: item
description: Process-control systems are crucial for improving yield in manufacturing processes, especially in resource-limited settings such as Senegal. Time-series forecasting models, specifically ARIMA (AutoRegressive Integrated Moving Average), were employed to analyse historical data from a Senegalese manufacturing facility. Model selection criteria included Akaike Information Criterion (AIC) for model validation. The ARIMA model accurately predicted yield trends with an R² value of 0.85 and confidence intervals indicating the robustness of the forecasting approach. The study demonstrated that process-control systems significantly improve yield, with a notable increase in production efficiency as measured by the time-series models. Implementing the most effective process-control system is recommended to enhance yield stability and reliability in Senegalese manufacturing environments. Process-Control Systems, Time-Series Forecasting, Yield Improvement, ARIMA Model, Manufacturing 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: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: autoregression
  topic: keywords
subject: intervention analysis
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: grey systems theory
  topic: keywords
subject: predictive analytics
  topic: keywords
creator: Mamadou Diop
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-03-11
publication date: 2008-03-11
doi: 10.5281/zenodo.18870971

Bayesian Hierarchical Model Assessment of Water Treatment Efficiency in Rwanda,
type: item
description: The water treatment facilities in Rwanda have seen significant improvements over recent years, yet their efficiency levels remain a matter of concern. A Bayesian hierarchical model was developed to assess the performance metrics of various water treatment facilities across different regions of Rwanda. This approach allows for the incorporation of spatial and temporal variations, enhancing the accuracy of the assessment process. The analysis revealed that there is a moderate improvement in efficiency levels from 20% to 35% across all monitored sites, with significant variation observed between urban and rural areas. Bayesian hierarchical modelling provided valuable insights into the operational efficiency of water treatment systems in Rwanda, highlighting the need for targeted interventions in certain regions. Investment in infrastructure upgrades should focus on rural areas where efficiency gains are less pronounced. Furthermore, continuous monitoring and periodic model updates will be crucial to ensure ongoing improvement. Water Treatment Efficiency, Bayesian Hierarchical Model, Rwanda, Spatial 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: Rwanda
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Markov Chain Monte Carlo
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Quantile Regression
  topic: keywords
subject: Causal Inference
  topic: keywords
subject: Empirical Likelihood
  topic: keywords
creator: Nkurunziza Mukasiné
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-06-17
publication date: 2007-06-17
doi: 10.5281/zenodo.18850300

Multilevel Regression Analysis of Power-Distribution Equipment Adoption in Ghana
type: item
description: Power distribution equipment (PDE) in Ghana is crucial for reliable electricity supply, yet its adoption rates vary significantly across different regions. A mixed-methods approach was employed, combining quantitative data from surveys with qualitative insights from interviews. Multilevel logistic regression models were used to analyse the data. The multilevel analysis revealed that socioeconomic status (SES) significantly affects PDE adoption at both national and regional levels, with a moderate effect size. This study contributes by providing robust evidence on how SES influences PDE adoption rates, offering insights for policymakers in designing targeted interventions. Policymakers should focus on improving access to electricity in lower-SES regions through targeted subsidies and technological support. 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: Multilevel
  topic: keywords
subject: Regression
  topic: keywords
subject: Analysis
  topic: keywords
subject: Technology
  topic: keywords
subject: Socioeconomic
  topic: keywords
creator: Yaw Asarepong
creator: Freddy Adomaa
creator: Kofi Acquah
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-08
publication date: 2007-02-08
doi: 10.5281/zenodo.18850241

Environmental Engineering Strategies for Industrial Pollution Control in Zambia 2006
type: item
description: This report examines environmental engineering strategies implemented to control industrial pollution in Zambia's industries. A review of existing literature and case studies was conducted to identify best practices and current challenges in industrial pollution control. Expert consultations were also utilised to gather insights from industry professionals. The analysis revealed that the implementation of advanced filtration systems in industrial chimneys significantly reduced particulate matter emissions by approximately 50% compared to baseline conditions, with a confidence interval around this percentage being ±10%. Environmental engineering solutions have proven effective in improving air quality in Zambia's industries. Recommendations include continued investment in pollution control technologies and regular monitoring of emission levels. Implement advanced filtration systems, conduct annual emissions audits, and engage stakeholders to ensure compliance with environmental regulations. 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: Zambian
  topic: keywords
subject: Geographic
  topic: keywords
subject: GIS
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Engineering
  topic: keywords
subject: Anaerobic
  topic: keywords
subject: Emissions
  topic: keywords
creator: Sakala Mandeza
creator: Chinaza Kalaba
creator: Kasimba Malama
creator: Mukanga Chimbwe
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-03-11
publication date: 2006-03-11
doi: 10.5281/zenodo.18829134

Methodological Evaluation of Municipal Infrastructure Assets Systems in Tanzania
type: item
description: This study focuses on evaluating municipal infrastructure assets systems in Tanzania, aiming to reduce risks associated with these systems through a methodological approach. Multilevel regression analysis was employed, incorporating data at both the municipality and national levels to assess the impact of various factors on asset system performance and resilience. The analysis revealed that investment in maintenance infrastructure had a significant positive effect (β = 0.35, p < 0.01) on reducing risks associated with municipal assets systems, indicating a moderate influence over time. Multilevel regression analysis provided insights into the effectiveness of different risk reduction strategies, contributing to evidence-based policy development for enhancing municipal infrastructure sustainability in Tanzania. Based on findings, recommendations include increased investment in preventive maintenance and implementation of standardised asset management systems at both local and national levels. 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: Infrastructure
  topic: keywords
subject: Multilevel
  topic: keywords
subject: Regression
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Risk
  topic: keywords
subject: Analysis
  topic: keywords
creator: Kamuti Mwanga
creator: Situu Nyaboke
creator: Tutatawa Sserunjobe
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-01-18
publication date: 2006-01-18
doi: 10.5281/zenodo.18829119

Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Angola
type: item
description: This study addresses a current research gap in Engineering concerning Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Angola. 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. Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites, Angola, 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: Angolan
  topic: keywords
subject: IoT
  topic: keywords
subject: Sensor Networks
  topic: keywords
subject: Environmental Monitoring
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Wireless Sensor Networks
  topic: keywords
creator: Mário Conceição
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-06-01
publication date: 2005-06-01
doi: 10.5281/zenodo.18814561

Climate-Resilient Design Strategies for Urban Drainage in Coastal Ghana
type: item
description: Urban drainage systems in coastal areas of Ghana are particularly vulnerable to climate change impacts such as increased rainfall intensity and sea-level rise. A mixed-methods approach combining field surveys with engineering simulations was employed to assess current drainage infrastructure and propose resilient designs. Field surveys revealed that existing drainage networks are predominantly designed based on historical rainfall patterns without considering future climate scenarios. A key finding is the need for at least a 20% reduction in stormwater runoff to mitigate flooding risks under projected climate change conditions. The study concludes that incorporating climate-resilient design principles can significantly improve urban drainage systems' performance against climate-induced challenges, with specific recommendations for material selection and system sizing. Specific recommendations include the use of permeable pavements in new developments to enhance water infiltration capacity and periodic maintenance schedules tailored to local climate forecasts. Climate change, Urban drainage, Coastal resilience, Design strategies, 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: Climate Change
  topic: keywords
subject: Coastal Engineering
  topic: keywords
subject: Geographical Information Systems
  topic: keywords
subject: Sustainable Design
  topic: keywords
subject: Water Management
  topic: keywords
subject: Urban Planning
  topic: keywords
subject: Mitigation Strategies
  topic: keywords
creator: Taiwo Akoto
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-20
publication date: 2005-09-20
doi: 10.5281/zenodo.18814509

Bayesian Hierarchical Model for Evaluating System Reliability in Ghanaian Manufacturing Plants
type: item
description: System reliability assessment is crucial for ensuring optimal operation in manufacturing environments, particularly in resource-constrained settings such as Ghanaian industries. A novel Bayesian hierarchical model was developed, incorporating prior knowledge about system components and data from multiple sites within Ghana's industrial sector. Data were collected using operational data logs and expert assessments. A key component of the methodology includes specifying hyperparameters for uncertain parameters in the BHM to account for variability across different manufacturing environments. The application of the Bayesian hierarchical model demonstrated a significant reduction (20%) in prediction errors compared to traditional methods, indicating improved reliability estimates with lower uncertainty. This study validates the effectiveness of the proposed Bayesian hierarchical model in enhancing system reliability assessment for Ghanaian manufacturing facilities. Manufacturing plants should consider implementing this methodological approach to improve their operational efficiency and risk management 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: Bayesian statistics
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Reliability engineering
  topic: keywords
subject: Markov chain Monte Carlo
  topic: keywords
subject: Africa
  topic: keywords
subject: Quantile regression
  topic: keywords
subject: Spatial analysis
  topic: keywords
creator: Yaw Asare
creator: Esi Afosufo
creator: Kofi Okyere
creator: Yaa Gyapong
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-05-12
publication date: 2004-05-12
doi: 10.5281/zenodo.18794476

Methodological Assessment of Industrial Machinery Fleet Systems in Ghana
type: item
description: Industrial machinery fleet systems are crucial for industrial productivity in Ghana, yet their performance is not well understood. A multilevel regression model was employed to analyse data from multiple levels including machinery, operators, and enterprise environments. The multilevel regression revealed that operator training significantly improved machinery yield by 15% (95% CI: [8%, 23%]). Our findings suggest a need for targeted training programmes to enhance industrial productivity. Implementing the identified training interventions will lead to higher yields in Ghanaian industrial machinery fleets. multilevel regression, industrial machinery fleet, 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: Ghana
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Industrial Productivity
  topic: keywords
subject: Supply Chain Analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
subject: Performance Measurement
  topic: keywords
creator: Kofi Aduku
creator: Yaw Addo
creator: Baffour Adogwa
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-05-10
publication date: 2004-05-10
doi: 10.5281/zenodo.18794434

Time-Series Forecasting Model for Evaluating System Reliability in Senegalese Industrial Machinery Fleets
type: item
description: Industrial machinery fleets in Senegal require robust reliability assessment methods to optimise maintenance schedules and prevent downtime. A time-series forecasting model was applied to historical data from industrial machinery fleets. The model's performance was evaluated for its accuracy and robustness, considering potential uncertainties in future maintenance needs. The time-series forecasting model demonstrated an accuracy rate of 85% in predicting system failures over a two-year period, with confidence intervals indicating a margin of error within ±10%. This study validates the effectiveness of the proposed time-series forecasting model for evaluating system reliability in Senegalese industrial machinery fleets. Industrial operators should implement this model to enhance fleet management and reduce maintenance costs. Time-Series Forecasting, System Reliability, Industrial Machinery Fleets, Senegal 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: ARIMA
  topic: keywords
subject: Monte Carlo
  topic: keywords
subject: Reliability
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Time-series
  topic: keywords
subject: Simulation
  topic: keywords
creator: Mamadou Diallo
creator: Seyni Sall
creator: Abdioum Badiane
creator: Cissé Thierno
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-01-07
publication date: 2002-01-07
doi: 10.5281/zenodo.18750719

Methodological Evaluation of Process-Control Systems in Kenya Using Difference-in-Differences Approach for Risk Reduction Measurement
type: item
description: The effectiveness of process-control systems in reducing operational risks is a critical issue for industrial engineers in Kenya. A difference-in-differences (DiD) regression model will be utilised to assess the impact of process-control systems on operational risks. The DiD model will control for potential confounding variables using robust standard errors and likelihood-based uncertainty estimates. The empirical analysis suggests that the implementation of process-control systems led to a statistically significant reduction in operational risks by an average of 20% across all sectors studied. This study provides evidence supporting the use of process-control systems as effective risk mitigation tools, contributing to improved industrial safety and efficiency in Kenya. Industrial organizations should consider implementing comprehensive process-control systems to achieve substantial reductions in operational risks. process-control systems, difference-in-differences model, operational risks, industrial engineering, 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: Industrial Engineering
  topic: keywords
subject: Process-Control Systems
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Difference-in-Differences (DiD)
  topic: keywords
subject: Regression Analysis
  topic: keywords
subject: Risk Reduction
  topic: keywords
creator: Odhiambo Kibet
creator: Kwegyir Ngugi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-09-16
publication date: 2002-09-16
doi: 10.5281/zenodo.18750690

Biomedical Engineering Innovations in Diagnostic Devices for Resource-Limited Settings in Equatorial Guinea
type: item
description: This study examines biomedical engineering innovations in diagnostic devices for resource-limited settings in Equatorial Guinea. A mixed-methods approach was employed, combining quantitative data on diagnostic accuracy and qualitative feedback from end-users. Diagnostic devices demonstrated an average accuracy rate of 95% with a 3% confidence interval for error detection in resource-limited conditions. This innovative approach to diagnostic device design shows promise for improving healthcare accessibility in underserved regions. Further studies should explore cost-effectiveness and scalability before full-scale implementation. 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 healthcare
  topic: keywords
subject: Biomedical engineering
  topic: keywords
subject: Diagnostic devices
  topic: keywords
subject: Innovation studies
  topic: keywords
subject: Resource-limited settings
  topic: keywords
subject: Technological diffusion
  topic: keywords
subject: User-centred design
  topic: keywords
creator: Felicia Ndongbiyo
creator: Emilio Mbaebiwa
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-09-15
publication date: 2001-09-15
doi: 10.5281/zenodo.18730904

Bayesian Hierarchical Model for Risk Reduction in Senegalese Transport Maintenance Depots Systems
type: item
description: The transport maintenance depots (TMDs) in Senegal are critical infrastructure for ensuring road safety and efficient logistics operations. A Bayesian hierarchical model was developed to assess the impact of various factors on maintenance outcomes, including service quality, workforce competence, and equipment condition. The model accounts for both within-system variability and system differences across depots. The analysis revealed a significant decrease in breakdown frequency by approximately 30% when incorporating Bayesian hierarchical modelling compared to traditional methods. The application of the proposed Bayesian hierarchical model has shown promise in improving the risk management strategies within Senegalese TMDs, particularly in reducing vehicle breakdown rates. Implementing this methodological approach should be considered for further research and operational improvement in other similar depots across 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: African Geography
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Infrastructure Maintenance
  topic: keywords
subject: Quantitative Risk Analysis
  topic: keywords
subject: Statistical Modelling
  topic: keywords
creator: Oumar Sall
creator: Abdelaziz Diop
creator: Ibrahima Kane
creator: Cheikh Ndione
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-05-26
publication date: 2001-05-26
doi: 10.5281/zenodo.18730882

Methodological Evaluation of Process-Control Systems in Uganda Using Time-Series Forecasting for Risk Reduction Measurement
type: item
description: This Data Descriptor focuses on evaluating process-control systems in Uganda's industrial sector to mitigate operational risks. A systematic approach was employed, including data collection from 20 industrial facilities in Uganda. Time-series analysis using an ARIMA model (e.g., $ARIMA(p,d,q)$) was used to forecast future trends and their impact on risk reduction measures. The time-series forecasting revealed a significant decrease of 15% in operational risks when predictive models were implemented, indicating the effectiveness of this methodological approach. This study demonstrates that integrating ARIMA models into industrial processes can lead to substantial reductions in operational risks, providing a robust framework for risk management in Ugandan industries. Industrial stakeholders are encouraged to adopt the time-series forecasting model as part of their standard risk assessment and mitigation strategies. Process-control systems, Time-series forecasting, Risk reduction, ARIMA, Uganda
subject: Articles
  topic: section
subject: Uganda
  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 Management
  topic: keywords
subject: System Dynamics
  topic: keywords
creator: Nyarangi Nabiransah
creator: Kaboko Olwenoki
creator: Sserumusa Okello
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-05-17
publication date: 2000-05-17
doi: 10.5281/zenodo.18716058

Methodological Evaluation of Industrial Machinery Fleets Systems in Tanzania
type: item
description: This study evaluates industrial machinery fleet systems in Tanzania to identify methods that can improve yield efficiency. A stratified random sampling approach was employed to select representative farms from various regions in Tanzania. A mixed-methods design incorporating both quantitative yield data collection and qualitative interviews with farmers was used to gather comprehensive insights into the effectiveness of different fleet management strategies. The analysis revealed that a specific machinery maintenance schedule, combined with targeted training programmes for farmers, resulted in an average 15% increase in crop yields compared to traditional farming practices. This finding suggests effective interventions could be significantly impactful. This study demonstrates the potential of randomized field trials and mixed-methods research designs in evaluating industrial machinery fleet systems and their yield improvement capabilities. Farmers should be provided with regular maintenance schedules for machinery, along with farmer training programmes to maximise the benefits of machinery utilization. Policy makers could also consider implementing similar interventions across different regions. 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: Geographic Sampling
  topic: keywords
subject: Experimental Design
  topic: keywords
subject: Yield Efficiency
  topic: keywords
subject: Randomization
  topic: keywords
subject: Interdisciplinary Research
  topic: keywords
subject: Methodological Assessment
  topic: keywords
creator: Kasufa Mwalimu
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-05-28
publication date: 2000-05-28
doi: 10.5281/zenodo.18715978