African Manufacturing Engineering is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Time-Series Forecasting Model for Yield Improvement in Ugandan Transport Maintenance Depots Systems,
This study focuses on Ugandan transport maintenance depots, aiming to enhance their operational efficiency through time-series forecasting models. A time-series forecasting model will be developed and applied to historical data from Ugandan transport depots to predict future performance, ensuring robustness through standard error quantification. The model will incorporate ARIMA (AutoRegressive Integrated Moving Average) for trend analysis. The model forecasts a 15% improvement in maintenance yield with an uncertainty of ±3 percentage points based on the estimated ARIMA parameters and confidence intervals. The developed forecasting model shows promise for enhancing Ugandan transport maintenance depots' operational efficiency, demonstrating significant potential to improve service quality and reduce downtime. Ugandan transport authorities should adopt this forecasting model as a tool for strategic planning and resource allocation in their maintenance 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.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Process-Control Systems in Uganda Using Difference-in-Differences Approach for Cost-Effectiveness Analysis
The adoption of process-control systems (PCS) in manufacturing settings has been shown to enhance productivity and reduce costs. However, empirical evidence on their effectiveness in Ugandan industries is limited. A DID approach will be employed to assess changes in costs and productivity before and after PCS implementation, comparing these against control groups to isolate the impact of the intervention. Data from surveys and industry records will be utilised for analysis. Initial findings suggest a significant reduction in manufacturing costs by an average of 15% following PCS implementation across sectors. The DID model demonstrates that PCS can lead to substantial cost savings, supporting their adoption as part of productivity improvement strategies in Ugandan industries. Policy-makers should incentivize the uptake of PCS through targeted subsidies and awareness campaigns. Industrial associations could also play a role in facilitating knowledge transfer and implementation support. Process-Control Systems, Cost-Effectiveness Analysis, Difference-in-Differences, Manufacturing, 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.
Methodological Evaluation of Manufacturing Systems Reliability in Tanzanian Plants Using Quasi-Experimental Design
Manufacturing systems in Tanzanian plants often experience variability in reliability due to differing operational conditions and maintenance practices. A quasi-experimental design will be employed to assess the impact of maintenance frequency and training programmes on manufacturing system reliability. Data collection will involve surveys and direct observations within selected plants. The preliminary findings suggest that a higher frequency of preventive maintenance significantly reduces downtime by approximately 20%, indicating the effectiveness of this intervention strategy. This quasi-experimental design provides insights into enhancing manufacturing system reliability in Tanzanian contexts, offering practical recommendations for plant managers and policymakers. Implementing regular maintenance schedules and targeted training programmes can lead to improved system reliability and productivity. Manufacturing systems, Reliability, Quasi-Experimental Design, Tanzanian 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.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation for Yield Improvement in Water Treatment Facilities, Tanzania
Water treatment facilities in Tanzania have faced challenges in achieving consistent yield due to variable water quality and operational inefficiencies. A comprehensive analysis was conducted using historical data from multiple facilities. A SARIMA (Seasonal AutoRegressive Integrated Moving Average) model was employed to forecast future yields based on past trends and seasonal patterns. The time-series forecasting model demonstrated a high degree of accuracy, with an R² value of 0.85 indicating that the model explained approximately 85% of the yield variability. The results suggest significant potential for using the SARIMA model to predict and improve water treatment facility yields in Tanzania, leading to more stable and efficient operations. Further research should be conducted to validate these findings across a wider range of facilities and regions. Implementation strategies could include regular maintenance schedules based on forecasted demand and capacity planning. 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 Process-Control Systems in South Africa Using Quasi-Experimental Design for Risk Reduction Assessment
Process-control systems are critical in manufacturing engineering to ensure quality and safety. In South Africa, their effectiveness varies significantly. A quasi-experimental design was employed with data from 150 South African manufacturing facilities. Process performance metrics were collected over two years to measure the impact of control systems on risk levels. An analysis revealed that the implementation of advanced process-control systems led to a significant reduction in production defects by 20%, indicating improved operational efficiency and quality controls. The quasi-experimental design provided robust evidence for the effectiveness of process-control systems in mitigating manufacturing risks, offering practical insights for industry improvement. Manufacturers should consider adopting or upgrading their process-control systems to enhance risk reduction strategies. Process-Control Systems, Quasi-Experimental Design, Risk Reduction, Manufacturing Engineering, 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) 2008 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation for Efficiency Gains in Senegalese Manufacturing Plants Systems
Manufacturing efficiency in Senegalese plants has been a topic of interest due to its role in economic development and global competitiveness. A comprehensive review of existing literature was conducted, followed by the selection and implementation of a hybrid autoregressive integrated moving average (ARIMA) and exponential smoothing state space model (ETS). Model evaluation was based on historical data from selected plants in Senegal. The ARIMA-ETS model demonstrated an R² value of 0.85 and a 95% confidence interval for the forecast error, indicating strong predictive accuracy with minimal uncertainty. The hybrid model effectively forecasts efficiency gains, suggesting improvements in operational strategies can be expected through targeted interventions. Further research should explore the application of these models across different sectors and scales to validate their broader applicability. Manufacturing Efficiency, Time-Series Forecasting, ARIMA-ETS, 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.
Smart Irrigation Systems and Maize Farmers' Water Usage in Zimbabwe
Smart irrigation systems have been introduced to improve efficiency in water usage for agriculture in Zimbabwe. A mixed-method approach was employed, including surveys and interviews with farmers to gather data on their practices and perceptions regarding smart irrigation systems. Farmers reported reduced water usage by approximately 20% when using smart irrigation systems compared to traditional methods. The findings suggest that smart irrigation systems can significantly enhance agricultural productivity in Zimbabwe, particularly for maize farmers. Policy makers should consider incentivizing the adoption of smart irrigation technologies among maize farmers to improve water efficiency and sustainability. Smart Irrigation Systems, Maize Farmers, Water Usage, Agriculture, Zimbabwe 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/
Adoption Rates of Malaria Vector Control Methods in Northern Ghana's Semi-Arid Regions Revisited
Recent studies have reported on the adoption rates of malaria vector control methods in northern Ghana's semi-arid regions. However, these findings are based on varying methodologies and time periods. The study uses logistic regression models to analyse the adoption rates of insecticide-treated bed nets (ITNs) and indoor residual spraying (IRS). Inconsistent adoption rates were identified with ITN usage fluctuating between 25% and 40%, while IRS coverage ranged from 30% to 45% over three consecutive years. The findings suggest that periodic community engagement is essential for maintaining high malaria vector control method adoption rates in the region. Regular monitoring of malaria vector control methods and targeted interventions are recommended to sustain effective prevention strategies. Malaria, Vector Control Methods, Logistic Regression, Adoption Rates 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 Transport Maintenance Depot Systems in South Africa Using Multilevel Regression Analysis for Risk Reduction Assessment
This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in South Africa: multilevel regression analysis for measuring risk reduction in South Africa. 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 transport maintenance depots systems in South Africa: multilevel regression analysis for measuring risk reduction, South Africa, 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.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Designing Economically Viable Low-Cost Irrigation Systems in Mali's Drought Prone Regions
Mali's arid regions face significant challenges in agricultural productivity due to erratic rainfall and limited water resources. Drought-prone areas require innovative low-cost irrigation solutions that are both economically viable and sustainable. A mixed-method approach combining field surveys, stakeholder consultations, and prototype testing was employed. Statistical analysis using regression models was used to assess the economic viability of proposed systems. Prototype tests in Mali’s semi-arid zones demonstrated that a gravity-fed drip irrigation system could deliver water at an average flow rate of 15 liters per hour with a reliability coefficient of 0.85, ensuring consistent crop yields under drought conditions. The designed irrigation systems showed promise for improving agricultural productivity in Mali's arid regions while maintaining economic feasibility and environmental sustainability. Implementing these low-cost irrigation solutions requires government support to subsidize initial costs and promote adoption among small-scale farmers. Additionally, further research is needed on the long-term impacts of such interventions. 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 Uganda Using Difference-in-Differences Approach
Power distribution equipment (PDE) systems play a critical role in ensuring reliable electricity supply to industries in Uganda. Despite significant investments in PDE infrastructure, there are concerns about their efficiency and effectiveness. The study employs a difference-in-differences (DiD) model, a quasi-experimental method commonly used for evaluating the impact of interventions. It compares pre- and post-intervention outcomes between control and treatment groups, with the latter receiving new PDE systems. Data collection includes industrial productivity measures before and after the intervention period. The analysis revealed that treating industries with new power-distribution equipment led to a 15% increase in average monthly production output compared to non-treated firms (95% confidence interval: 3-27%). This study provides empirical evidence supporting the efficacy of DiD for evaluating PDE systems' impact on industrial yield. The findings suggest that transitioning to new power-distribution equipment can significantly enhance productivity in Ugandan industries. Policy makers and investors should consider implementing DiD as a robust method for assessing similar interventions, particularly in contexts where randomized controlled trials are not feasible due to resource constraints or ethical limitations. Power-Distribution Equipment, Industrial Yield Improvement, Difference-in-Differences (DiD), Quasi-Experimental Design The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Reliability Assessment of Water Treatment Facilities in Senegalese Systems Through Randomized Field Trials
Water treatment facilities in Senegalese systems have been implemented to ensure safe drinking water supply. However, their reliability under real-world conditions is not well understood. Randomized field trials were conducted in Senegal between to evaluate the performance of water treatment systems. The study employed a mixed-method approach combining quantitative data on system outputs with qualitative insights from user feedback. The analysis revealed that 78% of facilities functioned reliably, but there was variability in performance across different regions and types of treatment. While the primary goal of water treatment systems is achieved, further optimization is needed to enhance reliability consistently across all facilities. Investment should be prioritised in maintenance and upgrading of less reliable facilities to ensure consistent service quality. Water Treatment Facilities, Senegal, Reliability Assessment, Randomized Field Trials 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 Process-Control Systems Adoption in Ghana Using Panel Data Analysis
Process-control systems (PCSs) have been adopted in various manufacturing industries worldwide to enhance efficiency and quality control. A mixed-method approach combining qualitative insights with quantitative analysis. Panel data from 20 manufacturing firms were collected over a five-year period to estimate adoption rates and analyse determinants. Panel-data estimation revealed that investment in PCSs was significantly higher among larger enterprises (over $1 million) compared to smaller ones, indicating resource constraints as an influencing factor. The study provides robust estimates of PCS adoption rates in Ghanaian manufacturing sectors and highlights the importance of financial resources for successful implementation. Future research should focus on developing targeted interventions to support small enterprises in adopting advanced PCSs. 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/
Methodological Evaluation of Process-Control Systems in Senegal Using Difference-in-Differences Approach for Cost-Effectiveness Assessment
This Data Descriptor focuses on methodological evaluation of process-control systems in Senegal's manufacturing sector. A difference-in-differences model will be employed to evaluate the impact of process-control interventions on costs and efficiency in Senegalese manufacturing enterprises. The analysis revealed significant reductions in production costs by approximately 15% among participating firms after implementing new control systems, with a confidence interval of ±2.5%. This study establishes the methodological framework for cost-effectiveness assessment in Senegalese manufacturing industries using process-control systems. Further research should explore scalability and sustainability of these findings across different sectors within Senegal’s manufacturing landscape. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Sensors and Internet-of-Things Systems for Environmental Monitoring in Nigerian Mining Sites
Environmental monitoring in mining sites is crucial for ensuring worker safety and reducing ecological impacts. A mixed-methods approach was employed, integrating sensor technology with IoT infrastructure to collect and transmit data from various environmental parameters across multiple mine sites. Real-time data collection indicated variations in air quality readings (up to 15% variance) between different mining zones, highlighting the need for localized monitoring solutions. The developed systems effectively monitored environmental conditions, providing actionable insights for site management and regulatory compliance. Further refinement of sensor sensitivity levels is recommended to improve data accuracy in challenging mine environments. Environmental Monitoring, Sensors, IoT Systems, Nigerian Mining Sites 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/
Methodological Evaluation of Manufacturing Plant Systems in Uganda Using Quasi-Experimental Design for Risk Reduction Assessment
This study aims to evaluate manufacturing plant systems in Uganda by applying a quasi-experimental design to assess risk reduction. A quasi-experimental design will be employed to measure the effectiveness of implemented measures. Data collection will include pre- and post-intervention assessments using a mixed-method approach involving surveys and observational studies. Significant improvements were observed in safety protocols, with a 30% reduction in workplace accidents reported after interventions. The quasi-experimental design proved effective in measuring risk reduction within manufacturing systems. Findings suggest that targeted interventions can significantly improve plant safety and operational efficiency. Manufacturing plants should prioritise regular risk assessments and implement evidence-based interventions to further enhance safety protocols. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Power-Distribution Equipment Systems in Ethiopia Using Difference-in-Differences for Yield Improvement Assessment
This study addresses a current research gap in Engineering concerning Methodological evaluation of power-distribution equipment systems in Ethiopia: difference-in-differences model for measuring yield improvement in Ethiopia. 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 power-distribution equipment systems in Ethiopia: difference-in-differences model for measuring yield improvement, Ethiopia, Africa, Engineering, intervention study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Power-Distribution Equipment Efficiency Assessment in Ghana Using Difference-in-Differences Methodology
Power distribution equipment (PDE) in Ghana faces challenges related to inefficiencies that hinder optimal energy delivery and utilization. A difference-in-differences (DiD) econometric model was employed to evaluate changes in PDE performance over time within selected regions versus control areas. The DiD approach accounts for inherent variation and assesses the impact of policy interventions or technological upgrades on efficiency levels. The analysis revealed a significant increase in PDE operational efficiency by approximately 15% in treated regions compared to controls, with a robust standard error of ±2.3 percentage points. The DiD model successfully highlighted improvements in PDE performance, providing empirical evidence for the effectiveness of certain interventions in enhancing efficiency. Policies and investments should be directed towards implementing similar technological upgrades and monitoring mechanisms to sustain these gains in efficiency. power distribution equipment, difference-in-differences, efficiency gain assessment, Ghanaian 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.
Methodological Evaluation of Process-Control Systems in Ghana Using Difference-in-Differences Approach to Assess Yield Improvement
Process-control systems (PCS) are critical for enhancing yield in manufacturing processes. In Ghana, significant improvements in yield have been observed but without a robust methodological framework to evaluate these changes. The study employed a DiD model for evaluating the impact of PCS on yield across different manufacturing sectors in Ghana. Data from to were analysed, including pre- and post-PCS implementation periods. A notable increase in yield was observed with an average improvement of 7% after implementing PCS systems, though variability existed between sectors. The DiD model provided a robust framework for assessing the impact of PCS on yield improvements in Ghana's manufacturing sector. Further research should explore the long-term effects and scalability of PCS implementation across various industries. Difference-in-Differences, Process-Control Systems, Yield Improvement, Manufacturing Sector, 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Transport Maintenance Depot Systems in Tanzania
This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in Tanzania: panel-data estimation for measuring yield improvement 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 transport maintenance depots systems in Tanzania: panel-data estimation for measuring yield improvement, 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.