Incorporation of ore grade uncertainty into the push back design process

Long-term production planning design is a major step in mine planning, because it determines the economic outcome of a project. Also long-term planes act as a guide for medium and short-term production scheduling. Because there are a large number of blocks within the ultimate pit limit, the pit can be divided into a series of sub-pits commonly called push backs, cut backs or phases. These push backs are designed with haul road access and act as a guide during the yearly scheduling process. Therefore, pushback design plays a key role in defining annual cash flows to be generated from a mining operation. There may be many alternative push back sequences for an open pit, which can result in obtaining different NPV from a mining project. Since the 1960s many push back design algorithms have been developed. Two strategies were followed through the previous push back design algorithms: 1. Determining the push backs with the assumption that the best ore is the ore that has the highest grade and needs to have a very low stripping ratio to be extracted. Economic parameterization methods are classified in this group. In these methods a series of pits are generated by applying the ultimate pit limit algorithms (Learchs and Grossman’s algorithm1,2 and network flow one3) on different economic block models of the deposit. These economic models can be generated by changing some economic parameters such as commodity price, cut-off grade or mining and processing costs. The most widely used algorithm in this regard is Whittle’s method4,5. Wang and Sevim6 proposed a push back design algorithm using reserve parameterization instead of economic parameterization. Their algorithm was based on obtaining maximum metal pit containing M blocks through M+N blocks in the model. In 1986 a heuristic approach was formulated by Gershon7 which considers the quality of the ore, the position of the ore block and the quality of the blocks under the desired ore block. Experience showed that defining the best ore as above may not lead to maximizing the Incorporation of ore grade uncertainty into the push back design process