Underground Mining Critical Article Review and Annotated Bibliography

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“Mining is a capital intensive business, so a small increase in mining productivity will often result in savings of millions of dollars” (Topal & Ramazan, 2010). For this reason, many researchers are focused on developing and improving mathematical models to optimize different mining process. Aiming to increase the Net Present Value of underground mines Nehring, Topal, Kizil and Knights in Integrated short- and medium-term underground mine production scheduling present a new mathematical formulation, based on mixed integer programming, for mine planning scheduling that shows to able not only to increase NPV but also to add feasibility for mining production when compared with current used models, which are already considered optimal; despite presenting strong arguments, a clear formulation and organized information, it is possible to note some limitations, such as: a trial case study instead of real data to demonstrate model’s efficiency and fixed mining parameters. The current mining planning scheduling issue is to find a way to conciliate both short- and medium- term objective, minimize deviation from target mill feed grade and maximize NPV, respectively, since both are really important to a mining plant as a whole . Nowadays, most mining companies use a model to find an optimal medium- or long- term schedule and then use this data to schedule short- term production (Martinez & Newman, 2011). The authors argue that in the current way it is only possible to achieve a local optimum that results in a short- term schedule with large variation in mill feed supply, which is prejudicial to mining processing system. So, they proposed a model formulation based in mixed integer programming that considers the two phases (short- and medium- term) simultaneously, making it possible to achieve a global optimum: an optimized schedule (high NPV) that allows a consistent mill feed grade (low deviation). The paper is divided in 2 main parts: model formulation and case study. In the first part, the model formulation based on mixed integer programming is described in detail. The model is constituted by an objective function that aims to optimize the mining schedule and applies a cash penalty for feed grade deviation above or below to target. Moreover, many regular mining constraints are considered, for example, resource, sequencing and timing (both short- and medium- term), and an integration constraint that plays an important part in the model formulation is introduced. In the second part, the author use both integrated and segregated model to generate a 18 month schedule for a conceptual underground mine that comprises a total of 30 stopes in different stages of production, in order to compare its efficiencies. The article assumes the task of improving a model that is well-known to be optimal not only by increasing NPV but also by ensuring feasibility between the two schedules. It is evident when the authors state that “even if the results of a globally optimal integrated schedule do not differ to that of the locally optimal segregated schedule, use of the integrated process ensures that an activity in one horizon must also occur in the corresponding horizon. This cross-referencing process thus ensures feasibility between the two scheduling horizons”, so this is an important contribution to the topic because it can avoid mine production stopping, which is money and time costing. In addition, since a mathematical model is theoretical, a good way to show its efficiency is providing a numerical example. So the authors were successful in choosing this strategy, a numerical case study, to demonstrate the model’s quality. Furthermore, both case study’s information and results are really well organized through the use of figures and tables, which make it easy to understand and help the reader to come to a conclusion. Despite of being well-structured, the case study is much simpler than a real mine situation. Using...
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