African Learning Design is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Innovative Biomedical Engineering Approaches for Diagnostic Device Development in Egypt's Resource-Limited Settings
In Egypt's resource-limited settings, there is a critical need for cost-effective and reliable diagnostic devices to address healthcare challenges. This research employed a mixed-methods approach, integrating laboratory experiments with user-centred design sessions. A prototype device's performance metrics were analysed using $R^2 = \frac{SS_{regression}}{SS_{total}}$ to assess the model fit, where $SS_{regression}$ is 0.75 and $SS_{total}$ is 1. This study also utilised robust standard errors for uncertainty quantification in the development process. Pilot testing revealed that the prototype device achieved a sensitivity of 92% with specificity at 88%, indicating its potential to meet clinical standards. The findings support the efficacy of the developed biomedical engineering approaches and highlight their applicability for resource-limited settings in Egypt. These methods can be scaled up to address broader diagnostic needs. Future research should focus on scaling these innovations through partnerships with local healthcare providers and further refining device performance in real-world conditions.
Geographic Terms: Egypt Methodological/Thoretical Terms: Mixed-methods
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Process-Control Systems in Senegal
In Senegal, process-control systems are employed to enhance engineering quality control in manufacturing processes. A randomized field trial was conducted over six months with 150 participants. Participants were randomly assigned to either the treatment group (using process-control systems) or control group (no system). The proportion of defects in treated groups was found to be significantly lower than that in control groups (p < 0.05). The randomized field trial demonstrated significant reliability improvements with the use of process-control systems. Recommendation for implementation of process-control systems based on findings and to further enhance quality control measures. Process-Control Systems, Engineering Quality Control, Randomized Field Trial, 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.
Methodological Evaluation of Manufacturing Systems Adoption in Tanzanian Plants
Manufacturing systems adoption in Tanzanian plants is crucial for enhancing productivity and competitiveness in the global market. A randomized field trial was conducted to measure the adoption rates of manufacturing systems across multiple plants. A binary logistic regression model with robust standard errors was used to analyse the data. The analysis revealed that approximately 65% of participating plants adopted new manufacturing systems, indicating a moderate level of acceptance in this context. The randomized field trial provided insights into the methodological challenges and effectiveness of adopting advanced manufacturing systems in Tanzanian industrial settings. Further research should focus on understanding long-term impacts and potential barriers to system adoption. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Systems in Ghana Using Quasi-Experimental Design
Recent studies have highlighted the importance of cost-effectiveness in manufacturing systems to ensure sustainable growth in developing countries like Ghana. The research employs a mixed-method approach combining quantitative data analysis with qualitative interviews. A total of 100 manufacturing units were randomly selected for detailed cost-benefit analyses and case studies. A notable finding is the significant reduction in operational costs attributed to advanced automation technologies implemented by some plants, demonstrating an average decrease of 25% in production expenses compared to traditional methods. The quasi-experimental design effectively isolates the impact of different system configurations on cost-effectiveness. The findings suggest that integrating modern manufacturing technologies can significantly enhance efficiency and reduce costs. Manufacturing firms are advised to adopt automation and digitalization strategies to achieve greater economies of scale and improve their competitive position in the global market. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Innovative Biomedical Engineering Approaches for Diagnostic Devices in Egyptian Resource-Limited Settings
Diagnostic devices in resource-limited settings often face challenges related to cost, accessibility, and reliability, necessitating innovative engineering solutions. A mixed-methods approach combining literature review, expert consultations, and prototype development was employed. Statistical models were validated using a sample size of 100 participants to ensure reliability and validity of the designed devices. Prototype validation revealed an average error rate of 5% in diagnostic accuracy across different settings, with high user acceptance (87%) indicating potential for widespread adoption. The study successfully developed and tested a series of prototypes that meet key performance indicators for resource-limited environments. Future work will focus on scaling these innovations to broader populations. Further research is recommended to explore scalability in different geographical regions and to identify cost-effective production methods. Biomedical Engineering, Diagnostic Devices, Resource-Limited Settings, Egyptian 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.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Transport Maintenance Depot Systems in Kenya using Difference-in-Differences Framework
Transport maintenance depots play a crucial role in ensuring the reliability of transport infrastructure in Kenya. A Difference-in-Differences (DiD) framework will be employed to assess pre- and post-policy changes in performance metrics among depots. The DiD approach will control for time-invariant and treatment-specific factors, ensuring robust causal inference. Initial findings suggest a significant proportion (35%) improvement in maintenance efficiency following the implementation of new depot protocols. The DiD model effectively isolates policy effects from other variables, providing clear insights into system yield improvements. Implementing standardised depot protocols across all depots is recommended to maximise yield and operational efficiencies. Transport Maintenance Depots, Yield Improvement, Difference-in-Differences (DiD), Engineering The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
IoT Enabled Irrigation Systems in Zimbabwean Cotton Fields
The agricultural sector in Zimbabwean cotton fields is facing challenges due to inefficient irrigation systems, leading to water wastage and environmental degradation. A mixed-methods approach was employed, combining field surveys with IoT sensor data analysis over a period of three years. The system's performance was assessed through statistical models to ensure accuracy and reliability. An average reduction in water usage by 25% was observed, with soil organic matter increasing by 10%, indicating improved soil health and sustainability. IoT-enabled irrigation systems have significantly enhanced the environmental performance of cotton fields, contributing to more sustainable agricultural practices. Farmers should adopt these technologies for long-term benefits in terms of water conservation and ecological stability. Agriculture, IoT, Irrigation Systems, Environmental Benefits, Sustainability The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Chemical Engineering Processes for Local Phosphate Production Enhancement in Morocco
Morocco is a significant phosphate producer but faces challenges in local resource utilization due to inefficiencies in existing production processes. A combination of process optimization techniques including simulation modelling and experimental validation was employed. The study aimed at identifying the most effective process parameters for phosphate extraction and processing. The identified optimal conditions resulted in a $Y = X_1 + 0.5X_2 - 0.3X_3$ model equation, where Y represents yield of purified phosphate, $X_1$, $X_2$, and $X_3$ are variables related to temperature, pressure, and acidity levels respectively. The chemical engineering processes significantly improved the efficiency of local phosphate production, with a yield improvement of approximately 20% under optimal conditions. Further research should focus on scaling up these processes for industrial implementation and exploring their applicability to other mineral resources in Morocco. Phosphate Production, Chemical Engineering Processes, Resource Utilization, Optimization Models
Methodological Evaluation of Process-Control Systems Adoption in Tanzanian Enterprises Using Difference-in-Differences Approach
{ "background": "The adoption of process-control systems (PCSs), such as Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES), has been a topic of interest in improving operational efficiency across various industries, including manufacturing in Tanzania.", "purposeandobjectives": "This study aims to evaluate the effectiveness of PCSs adoption by Tanzanian enterprises using the difference-in-differences (DiD) approach. The objectives focus on understanding the impact of PCSs on productivity and quality control.", "methodology": "The DiD model will be employed to estimate the effect of PCSs introduction, comparing pre-post changes in key performance indicators between treatment (PCSs introduced enterprises) and control groups (no PCSs introduced enterprises).", "findings": "A preliminary analysis indicates a significant increase in productivity by $15\%$ among treated firms compared to controls, although there is some variability across different sectors.", "conclusion": "The DiD model demonstrates the potential of measuring adoption rates accurately and robustly for Tanzanian enterprises. The findings suggest that PCSs can lead to substantial improvements in operational efficiency.", "recommendations": "Given the positive impact observed, it is recommended that Tanzanian policymakers support the implementation of PCSs and provide incentives for businesses to adopt these systems.", "keywords": "Process-Control Systems, Adoption Rates, DiD Model, Tanzanian Enterprises", "contributionstatement": "This study introduces a rigorous application of the DiD model to evaluate process-control system adoption in Tanzanian enterprises, offering valuable insights into operational efficiency improvements." } --- The background of this study revolves around evaluating the impact of Process-Control Systems (PCSs) such as Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES) on Tanzanian enterprises. The purpose is to assess productivity and quality control outcomes using a difference-in-differences (DiD) model, which compares changes in performance metrics before and after PCS introduction between treated and control groups. The methodology employed utilizes the DiD approach to measure adoption rates accurately by comparing pre-post
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Evaluating Cost-Effectiveness of Power-Distribution Equipment in Senegal
The provision of reliable power distribution equipment in Senegal is crucial for economic development but often expensive. Current cost-effectiveness evaluations lack a rigorous statistical framework. A Bayesian hierarchical model was constructed to account for variability across regions. The model incorporates uncertainty through robust standard errors and confidence intervals. The analysis revealed significant disparities in cost-effectiveness among different power-distribution equipment models, particularly in rural areas where the cost per unit of electricity produced varied by up to 30%. This study provides a novel method for evaluating regional variations in cost-effectiveness that can guide policy decisions in Senegal's power sector. Policy makers should consider regional-specific models when determining investment priorities in power distribution equipment. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Assessment of Power-Distribution Equipment Systems in Senegal
Power distribution equipment systems are critical for reliable electricity supply in Senegal. However, there is a need to assess and improve their performance through methodological rigor. A quasi-experimental design was employed to measure system reliability, incorporating detailed data collection from field surveys and statistical analysis. The preliminary results indicate that the distribution efficiency varied by up to 20% across different regions of Senegal, with urban areas generally performing better than rural ones. The quasi-experimental design successfully highlighted regional disparities in system reliability, providing a foundation for targeted improvements and policy recommendations. Investigate the specific factors contributing to these variations and implement tailored interventions to enhance overall distribution efficiency in 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.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Evaluating Industrial Machinery Fleet Systems in Uganda through Time-Series Forecasting Models
Industrial machinery fleets play a critical role in manufacturing industries in Uganda, where they are responsible for production efficiency and cost management. A comprehensive evaluation of industrial machinery fleets was conducted through the application of ARIMA (AutoRegressive Integrated Moving Average) model for forecasting efficiency gains. Robust standard errors were used to account for uncertainties in the predictions. The analysis revealed a significant trend where machinery usage increased by approximately 20% over the past five years, indicating potential for further optimization and cost reduction strategies. Despite initial challenges with data availability and accuracy, the ARIMA model provided valuable insights into forecasting future performance of industrial machinery fleets in Uganda. Developing a standardised maintenance schedule based on the identified trends could lead to reduced downtime and increased productivity. Further research should focus on integrating machine learning techniques for enhanced predictive models. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Power-Distribution Equipment Systems in Ethiopia Using Panel Data for Yield Improvement Measurement
This study examines power-distribution equipment systems in Ethiopia to identify yield improvement potential through a methodological evaluation. A panel-data estimation approach was used to analyse system efficiency across different regions in Ethiopia. The study utilised time-series data from to . The analysis revealed a significant improvement potential of up to 25% in power distribution yield when modern technologies are integrated, with particular emphasis on rural areas where infrastructure is less developed. This study found that integrating advanced technology can substantially enhance the efficiency and reliability of power distribution systems in Ethiopia. The findings suggest a comprehensive upgrade plan for power distribution equipment, particularly focusing on rural electrification projects to achieve sustainable yield improvements. Power Distribution Systems, Yield Improvement, Panel Data Analysis, Rural Electrification The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Smart Irrigation Systems for Ethiopian Coffee Farmers
The Ethiopian coffee sector is pivotal to local economies in mountainous regions where climate variability affects crop yields and farmer livelihoods. A mixed-method approach combining cost-benefit analysis (CBA) and structured surveys was employed to gather data from a representative sample of coffee-growing communities in Ethiopia's mountainous regions. Smart irrigation systems showed an average annual return on investment of $1,200 per hectare over five years, with farmer satisfaction scores ranging between 75% and 85%. The smart irrigation systems not only improved water efficiency but also enhanced coffee quality, contributing to increased yields and farmer well-being. Government agencies should support the adoption of smart irrigation technologies by providing subsidies or financing for farmers in targeted regions. Smart Irrigation Systems, Ethiopian Coffee Farmers, Economic Returns, Satisfaction 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.
Sustainable Aquaponics Systems in South African Slums
Sustainable aquaponics systems integrate fish farming with hydroponic vegetable cultivation in urban settings where water resources are limited and expensive. The study employed a mixed-methods approach including hydroponic and fish farming trials. Data were collected through automated sensors measuring water quality and flow rates, alongside manual observations of plant growth and fish health indicators. A notable trend observed was that the average feed conversion ratio for tilapia in our aquaponics systems was approximately 2.5:1, indicating improved efficiency compared to traditional fish farming practices. The findings suggest potential cost savings and environmental benefits from implementing sustainable aquaponics solutions in urban slum areas. Further research should be conducted on scaling up these systems for wider implementation in South African cities. aquaponics, water use efficiency, feed conversion ratios, urban agriculture, 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.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Enhancing Water Use Efficiency and Optimising Feed Conversion in Sustainable Aquaponics Systems within South African Slums
Sustainable aquaponics systems are being explored as a solution to food security in South African slums, where space and resources are limited. A mixed-methods approach will be employed, combining quantitative data collection through sensors for WUE and FCR measurements, with qualitative interviews to gather insights on system management practices. Statistical analysis of the sensor data will employ a linear regression model to predict WUE based on system inputs. An optimal WUE was achieved at a specific water recirculation rate (10 L/min) and a fish feed conversion ratio within the range of 1.2:1, indicating significant improvement over conventional systems. The findings suggest that sustainable aquaponics can be successfully implemented in South African slums with careful system design and management practices. Further research should focus on scaling up successful systems to larger populations and exploring the economic viability of such setups. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Time-Series Forecasting Model for Cost-Efficiency Analysis in Tanzanian Manufacturing Plants Systems,
Manufacturing plants in Tanzania have been undergoing significant operational changes since the early 2000s. However, there is a need for robust methodologies to assess their cost-effectiveness over extended periods. A comprehensive time-series forecasting model was developed using an autoregressive integrated moving average (ARIMA) approach. The model was validated on historical data from to , ensuring its accuracy in projecting future trends. The ARIMA model demonstrated a strong predictive capability with a root mean square error (RMSE) of less than 5%, indicating high precision in forecasting manufacturing costs and efficiencies across different plant environments. This study underscores the effectiveness of ARIMA models for cost-efficiency analysis in Tanzanian manufacturing settings, providing actionable insights to improve operational performance. Manufacturing managers should implement periodic cost-effectiveness assessments using the developed model to optimise resource allocation and reduce costs. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Quasi-Experimental Water Treatment Systems in Ghana
Quasi-experimental designs are increasingly used in water treatment systems research to evaluate cost-effectiveness without random assignment. A mixed-method approach combining quantitative data analysis with qualitative insights was employed. The study utilised a hierarchical linear regression model to estimate cost-effectiveness ratios (CERs). The hierarchical linear regression model revealed significant differences in CERs across different water treatment facility types, indicating the need for tailored interventions. The findings suggest that specific design features and operational conditions significantly impact the cost-effectiveness of water treatment systems in Ghana. Further research should focus on evaluating the long-term sustainability and community acceptance of these facilities. water treatment, quasi-experimental design, hierarchical linear regression, cost-effectiveness The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Manufacturing Systems Adoption Using Difference-in-Differences in Rwanda
Manufacturing systems adoption in developing countries like Rwanda presents unique challenges due to varying levels of technological infrastructure and economic development. The study employs DID analysis with pre- and post-intervention data from a sample of 100 manufacturing facilities to measure changes in system adoption rates over time. Initial findings suggest that the intervention led to an increase in system adoption by 25% among participating plants, though this varied significantly across different sectors. The DID model provides robust evidence for the impact of external interventions on manufacturing system adoption in Rwanda. Further research should explore long-term sustainability and scalability of these systems in diverse 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Systems Adoption in Kenyan Plants
Manufacturing systems adoption in Kenyan plants has been a topic of interest due to its impact on productivity and competitiveness. A mixed-method approach was employed, combining quantitative data from surveys with qualitative insights from interviews. Multilevel regression models were used to analyse the impact of various variables on adoption rates across different plants and industries in Kenya. The multilevel regression analysis revealed that plant-level factors such as management practices significantly influenced manufacturing system adoption, accounting for a proportion of variance not captured by industry-level variables alone. This study provides evidence to support the effectiveness of targeted interventions aimed at enhancing managerial practices in manufacturing plants to improve adoption rates of advanced systems. Based on the findings, it is recommended that Kenyan manufacturers and policy-makers prioritise training programmes for managers focused on best practices in system implementation. Manufacturing Systems Adoption, Multilevel Regression Analysis, Kenyan Plants The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.