Traditionally, mining companies have run the various functions of their supply chain as separate “businesses,” each acting independently to maximize its own performance. Extraction operations run separately from processing operations, which in turn are discrete from refining, which is separate from logistics, and so on down the line. The different functions all use disparate systems to plan and schedule their activities, with different priorities driven by often conflicting key performance indicators (KPIs). Decision-making occurs within a partial vacuum. The lack of collaboration and coordination in this “silo” approach means that planners don’t have visibility into the repercussions of their decisions further up or down the supply chain. Small upfront changes can lead to greater inefficiencies, higher costs, and potential quality impact on downstream operations.
This situation has been due in large part to the complexity of the mining supply chain. Time horizons range from short-term event scheduling to long-term life-of-mine planning. Mining infrastructure comprises many moving parts — diggers, trucks, delivery routes, material destinations, beneficiation options — that are in a constant state of flux. The number of interdependent variables inherent in multiple supply sources, ore attributes, complex processing and transport functions, and various loading and distribution points makes it difficult for planners to understand what the “best” decision is.
Most of today’s planning systems are ill-equipped to handle such a level of complexity and degree of variability. Conventional technologies capable of modeling geological variables do not have the functionality to manage downstream supply chain activities, and traditional supply chain planning and scheduling tools perpetuate the “silo” approach and fall short of fully incorporating engineering aspects.
But new tools now exist to harmonize planning and scheduling across the mining supply chain functions and time horizons. These tools realize more business value (greater efficiency, reduced costs, higher profit margins) by integrating information from various systems across the operation. Dynamically updated information shared among all supply chain functions arms key personnel with the intelligence to make better decisions faster. These new tools still allow for each unique function to be modeled accurately and used as the basis for optimized overall business performance. Decisions made at the mine planning stage may now be tracked all the way through the supply chain to determine the impact of the fulfillment of shipments or demand.
For example, a shipment impacted by a change in the mine extraction sequence may be 10 days away, but the decision on what block to extract needs to be made within the next 24 hours. Previously, these planning and scheduling horizons would have been managed by two separate teams in a vacuum — possibly leading to a situation where the wrong product arrives at the right place at the wrong time. Even getting two out of three right would still result in waste and inefficiency. With an integrated system, both teams are looking at the same information in a single application. As soon as a variable changes in the model, downstream effects are mirrored in the system. Optimization algorithms map the different time horizons so that planners can see the impact of certain decisions on other processes. Different scenarios can be modeled and analyzed to determine the best decision(s) to make for each supply chain function.