Figure 12 – Data clustering Once the events and project implementation dates are identified in the operational timeline, a multivariable linear regression model is developed to evaluate statistical significance and quantify the effect of each factor on SAG mill tonnage Figure 13 – Events identification The model incorporates variables such as liner condition, pressure relief actions, grinding media changes, grate configurations, neural network implementation, and the GIO Center. This regression framework allows ANOVA-based validation to confirm whether observed TPH variations are truly attributable to implemented projects rather than natural process variability. 96
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