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The aim is to evaluate the effectiveness of time-series forecasting models in measuring the adoption of process-control systems in Senegal.

February 28, 2026Open Access

Time-Series Forecasting Model for Measuring Adoption Rates in Process-Control Systems in Senegal: A Methodological Evaluation

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Time-series analysis reveals increasing adoption rates of process-control systems in Senegal, suggesting data consistency is crucial for accuracy.

The aim is to evaluate the effectiveness of time-series forecasting models in measuring the adoption of process-control systems in Senegal.
Applied time-series forecasting model using historical data from industrial sites
Utilised Box-Jenkins ARIMA method for parameter estimation
Modelled maintenance outcome with specified equation
Analyzed fluctuations during economic downturns
Adoption rates of process-control systems increased by an average of 15% over five years
Significant fluctuations in adoption observed during economic downturns
Insights highlight the importance of consistent data collection for model accuracy

Ndiaye et al. (2004) studied this question.

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Time-series analysis reveals increasing adoption rates of process-control systems in Senegal, suggesting data consistency is crucial for accuracy.