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This is a Quantitative Study study.

October 16, 2025ProcessesOpen Access

Towards Predictive Maintenance of SAG Mills: Developing a Data-Driven Prognostic Model

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The developed model accurately forecasts remaining useful life for sag mills, enhancing maintenance efficiency.
Using four years of operational data, feature engineering and clustering were performed to assess machine health.
A health indicator was created by scoring features on key criteria, which improved the model’s predictive capabilities.
Cross-validated selection of models ensured reliable predictions, providing actionable insights for maintenance planning.

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This study develops a prognostic model for sag mills' remaining useful life, highlighting predictive maintenance benefits.

Dehghan et al. (2025) studied this question.

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