The demand chain is the customer-oriented value chain element of a company. Rather than driving for the best product that can be produced out of what is mined, it is customer focussed and seeks to exploit the resource to best meet the requirements of the customer with the least amount of expense. To optimise the demand chain, mining operations require a holistic understanding and integration of their entire value chain so it becomes demand-driven rather than supply-driven. This is often difficult as the mining material chain is often fragmented between business groups and conflicting KPIs. Mining operations need an automated decision support tool that allows for rapid consideration of different scenarios with consideration of the entire value chain, from mine to the end customer.
Optimising the value chain is challenging when you take a piecemeal approach or only consider the supply side. Unlike other economies of scale industries such as oil and gas, mining does not have a predictable and continuous flow from the source to the end consumer. This lack of consistency and predictability is further exacerbated in bulk commodities where material isn’t being fed continuously through a process plant to continuously produce a standard product, but instead is built as a set of discrete cargos, where there is a fixed quantity at an overall quality specification. In this sense, bulk commodity demand chain bears similarities to manufacturing supply chain, though the principles that drive the manufacturing supply chain don’t necessarily apply in mining due to the variability of each cargo and the mining operation.
These considerations means that demand chain optimisation has distinctive challenges. For example, as the final product isn’t fixed nor constant and the end order can change frequently, it can be very difficult to fulfill a target-driven order where each build can be unique based on varying specification requirements, variable size, and heavily impacted by the date of completion due to shipping constraints and the penalties incurred with delays and off-specification builds. To manage the demand chain effectively, mining operations require an optimisation solution that can not only manage the variability of the entire process but also extend further than the run of mine (ROM) given ROM is where many mine planning solutions tend to stop, and spreadsheet work starts.
Demand Chain Optimiser (DCO) is a mining solution that optimises the flow of materials needed to satisfy customer orders all the way back to the miner for bulk commodity operations. DCO provides optimisation across the entire value chain by determining the ideal utilisation of in pit and stockpiled ore in the development of a targeted size build at specific grade by a specified time. This approach is unique in that it considers the availability of material over time while also focusing on the completion date. One of the significant benefits of DCO is the optimised usage of all materials, including low spec material that could otherwise be discounted or moved to long-term dead piles. This holistic, demand-driven approach differs from standard optimisation tools and uniquely provides the agility needed to respond rapidly to changing circumstances. Discussed below are the three key benefits of optimising the demand chain of mining operations.
Within DCO, the state of each stockpile is determined by the underlying algorithm. Each stockpile has variable constraint and objective parameters applied to manage stockpile behaviour driven by material classification and quality attributes. Stockpile states determine whether stockpile inventory can be increased or depleted at any time, maximising the use of stockpile space. DCO ensures material is taken in practical quantities, severely reducing the occurrence of “cherry-picking” and “remnants”— common outcomes from typical optimisation engines. This flexibility ensures that DCO is empowered to decide when to build and deplete stockpiles to best meet the shipping requirements, giving planners a degree of automation to assess blending options for the best outcome.
Product shipments are configured in DCO to define specific product builds which are typically named by shipment or ship. There is a nominated target date associated with the shipment, and each product build has its unique definition. This enables users to manage custom builds for one-off products or even off-spec products and align an existing shipping schedule with the mine plan. By considering target dates as part of the optimisation algorithm, DCO can consider options that would escape other optimisation engines.
DCO targets the completion of individual shipments, unlike other optimisers, which seek to achieve a target grade over a period. The difference between these approaches is significant. A period average grade provides false confidence in the ability of an operation to deliver by providing unachievable product outcomes. This may be seen where requisite higher grade material is applied too late in a cycle to correct a shipment, or blending early and late-arriving materials requires more stockyard capacity than is available at the port. Standard optimisers lack the deep domain mining knowledge to optimise a practical schedule in a mining environment. A standard optimiser may deliver a mathematically correct solution but impractical in the mining context, such as a directive to reclaim a specific parcel of material from a stockpile without considering the accessibility of that parcel, buried in the middle of the heap. Other examples of the impractical solutions from standard optimisers include frequent movements of small amounts of material from multiple sources, and the cost and delays associated with transitioning a stockpile from stacking to reclaiming. DCO is designed with mining domain knowledge from the beginning, instead of trying to bend a manufacturing solution to fix a mining problem.
Although mining organisations have historically been set up to act as individualised and siloed operations within departments, this is changing and organisations are now far more integrated than ever before. While demand chain optimisation is complex and has historically been challenging to achieve, this improved integration does provide the opportunity for significant benefit by reducing the cost of sales and increasing margins when the individual departments consider the overall value chain.