Legal – not supplying product to the quality as specified by the contract.
Cost – penalties applied as a result of demurrage and off specification product will impact the bottom line.
Reputational – customers may decide to purchase product elsewhere.
An integrated Mine to Port discrete event model was built in an attempt to identify why the mine plan did not produce the correct specifications. It was thought grade variability (amongst others) was a possible cause of the problems, but could not be proven with the existing model.
The discrete event model was enhanced to further accurately model the entire mine to port supply chain, also taking into account maintenance and downtime, weather and other variables. An optimization engine was created to perform two important tasks:
1) Decision logic to determine when to order ships such that sufficient ore of the appropriate quality will be ready in time.
2) Selectively using the available ore using known grade information across the entire supply chain, in order to produce ore shipments that best meet the customer’s requirements while avoiding penalties for delays and ore quality.
By allowing grade to be modelled across the entire supply chain as well as tonnes the client was able to see where the issues in their supply chain lay and take appropriate action.
By ensuring the mine plan was constructed to limit product variability and ensure on specification delivery to their customers, the client was able to mitigate legal, cost and reputational risks. The combined discrete event and optimization approach, allowed the business to compare and evaluate different mine plans by quantitatively assessing the inherent risk in each mine plan. Finally ships were able to be ordered in such a way as to align them with the product that would be delivered as part of the current mine plan.
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