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This study examines the integration of Industry 4.0 technologies, lean manufacturing, and data science to develop a predictive model for Overall Equipment Effectiveness (OEE) in an industrial manufacturing setting. Two statistical models are developed, utilizing traditional and machine learning techniques, to dynamically forecast based on production planning variables. Results show that both models over perform the static historical average model. However, the similar accuracy obtained by the two dynamic models raises questions about over-engineering production planning and control by investing in overly advanced technologies. Further insights are offered on the synergy between contextual-specific knowledge, intuition, and data-driven decision-making approaches.

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Lean Production Planning and Control 4.0: A Dynamic Forecasting Model for the OEE

  • 会议论文

  • 发表日期：

    2025年

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  • R. Colombari

摘要

This study examines the integration of Industry 4.0 technologies, lean manufacturing, and data science to develop a predictive model for Overall Equipment Effectiveness (OEE) in an industrial manufacturing setting. Two statistical models are developed, utilizing traditional and machine learning techniques, to dynamically forecast based on production planning variables. Results show that both models over perform the static historical average model. However, the similar accuracy obtained by the two dynamic models raises questions about over-engineering production planning and control by investing in overly advanced technologies. Further insights are offered on the synergy between contextual-specific knowledge, intuition, and data-driven decision-making approaches.