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March 6, 2026Open Access

Methodological Evaluation of Manufacturing Systems in Senegal Using Time-Series Forecasting Models for Risk Reduction Analysis

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Authors

SSSékou SowICIbrahima CissokoMNMamadou Ndiaye

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Overview

Comprehensive review evaluates risk reduction using forecasting models in Senegal's manufacturing systems, suggesting improved efficiency.

Key Points

  • This research aims to analyze the operational efficiency of Senegalese manufacturing systems using time-series forecasting models.
  • Conducted a comprehensive literature search in databases like PubMed, Web of Science, and Scopus.
  • Included studies utilizing time-series forecasting models for manufacturing plant performance in Senegal.
  • Analyzed production line data from two major manufacturing plants using the ARIMA model.
  • The ARIMA model achieved up to a 20% reduction in forecast errors for production line data.
  • Highlighted the reliability of time-series forecasting models in risk assessment for manufacturing operations.
  • Recommended continuous monitoring and refinement of forecasting models based on performance data.

Cite This Study

Sow et al. (2008) studied this question.

synapsesocial.com/papers/69aa70c8531e4c4a9ff5aec0https://doi.org/10.5281/zenodo.18868216
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Also Consider

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

  1. 1Methodological Evaluation of Manufacturing Systems in Senegal Using Time-Series Forecasting for Risk Reduction Assessment2007
  2. 2Methodological Evaluation of Manufacturing Plant Systems in Senegal Using Time-Series Forecasting for Reliability Assessment2000
  3. 3Methodological Evaluation of Manufacturing Plant Systems in Senegal Using Time-Series Forecasting Models for Cost-Effectiveness Assessment2000
  4. 4Time-Series Forecasting Model for Evaluating System Reliability in Senegalese Manufacturing Plants: An Engineering Approach2005
  5. 5Methodological Evaluation of Time-Series Forecasting Models in Senegalese Manufacturing Systems for Clinical Outcome Measurement2009