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March 7, 2026Open Access

Methodological Evaluation of Process-Control Systems for Yield Improvement in Senegal Using Time-Series Forecasting Models

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Authors

MDMamadou Diop

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Overview

This evaluation demonstrates improved yield in Senegal using time-series forecasting models, suggesting effective process-control implementation.

Key Points

  • The aim is to evaluate the effectiveness of process-control systems in enhancing yield within a Senegalese manufacturing setting using time-series forecasting.
  • Implemented ARIMA time-series forecasting models on historical production data.
  • Utilized Akaike Information Criterion for model validation.
  • Assessed yield trends through statistical parameters and confidence intervals.
  • The ARIMA model achieved an R² value of 0.85, indicating strong predictive accuracy.
  • Notable improvement in production efficiency was observed with the application of process-control systems.
  • Recommendations were made for implementing the most effective systems to ensure yield stability.

Cite This Study

Mamadou Diop (2008) studied this question.

synapsesocial.com/papers/69abc1d75af8044f7a4eae9dhttps://doi.org/10.5281/zenodo.18870971
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Time-Series Forecasting Model Evaluation for Yield Improvement in Senegalese Manufacturing Plants Systems2010
  2. 2Time-Series Forecasting Model Evaluation of Process-Control Systems in Senegal,2005
  3. 3Time-Series Forecasting Model for Evaluating Cost-Effectiveness in Process-Control Systems: A Case Study in Senegal2000
  4. 4Methodological Evaluation and Time-Series Forecasting for Yield Improvement in Senegalese Process-Control Systems2024
  5. 5Methodological Evaluation of Process-Control Systems in Senegal: Time-Series Forecasting for Efficiency Measurement2000