The process began with utilizing average weighted grade data from a table to determine the recovery rate and processing costs.  These values were then applied in the cut-off grade calculation: Cut-Off Grade = Processing Cost / ((Net Price) * Recovery). The average weighted grade and net price were sourced directly from the table. Finally, Python was employed to create graphs illustrating the cut-off grade, recovery rate, and processing cost trends.

Cut-Off Grade = Processing Cost / ((Net Price) * Recovery)

Recovery = Rmax * (1 - e^(-k * G))

Processing Cost = a + b * G


Processing Cost Formulas

1. Fixed + Grade-Dependent Cost Model  
processing cost = C0 + C1 / G

2. Regression from Real Cost Data (Realist)

Linear: C = a + b * G

Inverse or Logarithmic: C = a + b / G or C = a * log(G) + b

3. Tabulated Cost Based on Grade

Table equivalent for the given grade


Recovery Formulas

1. Empirical Linear Model

Recovery = a + b * G

2. Exponential or Logistic Model (Realist)

Recovery = Rmax * (1 - e^(-k * G))

3. Stepwise or Tabulated Recovery

Table equivalent for the given grade