A collaborative model planning to coordinate mining and smelting furnace

International audienceIn this paper, we are interested in the tactical planning problem of mines and smelting furnace. The problem concerns a set of mines with one smelting furnace. We are faced to a multi-actor’s context for which a global optimization is not possible due to the independence of the services. This problem is solved using a set of local optimization model of mines bloc extraction and a model of smelting furnace. This paper begin with the state of the art related to the principal problems in mining process. It justifies the novelty of our work. Indeed, this paper aims to discuss on the impact of sharing information between downstream processes and upstream processes. Consequently, after the state of the art, the classical planning process using local optimization and the information sharing process are presented. In the following part, profits generated and related to different contexts: value-creation and approach are compared. At the end of the paper, conclusion and future extensions are presented

Production Scheduling of an Open-pit Mining Complex with Waste Dump Constraints

The research work aims to solve the production scheduling problem for open pit mining complexes. It establishes a Mixed-Integer Programming (MIP) model that maximises the net present value of future cash flows and satisfies reserve, production capacity, mining block precedence, waste disposal, stockpiling, and pit sequence constraints. The model is validated and implemented with real-world case

What is the Environmental Performance of Firms Overseas?: An Empirical Investigation of the Global Gold Mining Industry

Bayesian stochastic frontier analysis; efficiency; environmental regulations and plant performance; pollution havens; regulatory chill; gold mining.

Optimizing mining rates under financial uncertainty in global mining complexes

AbstractThis paper presents a distributed and dynamic programming framework to the mining production rate target tracking of multiple metal mines under financial uncertainty. A single mine׳s target tracking is stated as a stochastic optimization problem and the solution is obtained by solving the dynamic program which gives the optimal production rate schedule of each mine as a Markovian feedback control on the price process. The global solution is distributed on multiple mines by a policy iteration method, and this iterative method is shown to provide the unique equilibrium among Markovian strategies. Numerical results confirm the efficacy of the proposed global method when compared to individual optimization of mining rate target tracking

Integrated Parametric Graph Closure and Branch-and-Cut Algorithm for Open Pit Mine Scheduling under Uncertainty

Open pit mine production scheduling is a computationally expensive large-scale mixed-integer linear programming problem. This research develops a computationally efficient algorithm to solve open pit production scheduling problems under uncertain geological parameters. The proposed solution approach for production scheduling is a two-stage process. The stochastic production scheduling problem is iteratively solved in the first stage after relaxing resource constraints using a parametric graph closure algorithm. Finally, the branch-and-cut algorithm is applied to respect the resource constraints, which might be violated during the first stage of the algorithm. Six small-scale production scheduling problems from iron and copper mines were used to validate the proposed stochastic production scheduling model. The results demonstrated that the proposed method could significantly improve the computational time with a reasonable optimality gap (the maximum gap is 4%). In addition, the proposed stochastic method is tested using industrial-scale copper data and compared with its deterministic model. The results show that the net present value for the stochastic model improved by 6% compared to the deterministic model

Presidential address: Optimization in underground mine planning-developments and opportunities.

Presidential address presented at the The Southern African Institute of Mining and Metallurgy Annual General Meeting on 11 August 2016.The application of mining-specific and generic optimization techniques in the mining industry is deeply rooted in the discipline of operations research (OR). OR has its origins in the British Royal Air Force and Army around the early 1930s. Its development continued during and after World War II. The application of OR techniques to optimization in the mining industry started to emerge in the early 1960s. Since then, optimization techniques have been applied to solve widely different mine planning problems. Mine planning plays an important role in the mine value chain as operations are measured against planned targets in order to evaluate operational performance. An optimized mine plan is expected to be sufficiently robust to ensure that actual outcomes are close or equal to planned targets, provided that variances due to poor performance are minimal. Despite the proliferation of optimization techniques in mine planning, optimization in underground mine planning is less extensively developed and applied than in open pit mine planning. This is due to the fact that optimization in underground mine planning is far more complex than open pit optimization. Optimization in underground mine planning has been executed in four broad areas, namely: development layouts, stope envelopes, production scheduling, and equipment selection and utilization. This paper highlights commonly applied optimization techniques, explores developments and opportunities, and makes a case for integrated three-dimensional (3D) stochastic optimization, in underground mine planning.MvdH201

Incorporation of geometallurgical modelling into long-term production planning

Strategic decisions to develop a mineral deposit are subject to geological uncertainty, due to the sparsity of drill core samples. The selection of metallurgical equipment is especially critical, since it restricts the processing options that are available to different ore blocks, even as the nature of the deposit is still highly uncertain. Current approaches for long-term mine planning are successful at addressing geological uncertainty, but do not adequately represent alternate modes of operation for the mineral processing plant, nor do they provide sufficient guidance for developing processing options. Nonetheless, recent developments in stochastic optimization and computer data structures have resulted in a framework that can integrate operational modes into strategic mine planning algorithms. A logical next step is to incorporate geometallurgical models that relate mineralogical features to plant performance, as described in this paper.Comment: 10 pages, 5 figure

Quantification of uncertainty of geometallurgical variables for mine planning optimisation

Interest in geometallurgy has increased significantly over the past 15 years or so because of the benefits it brings to mine planning and operation. Its use and integration into design, planning and operation is becoming increasingly critical especially in the context of declining ore grades and increasing mining and processing costs. This thesis, comprising four papers, offers methodologies and methods to quantify geometallurgical uncertainty and enrich the block model with geometallurgical variables, which contribute to improved optimisation of mining operations. This enhanced block model is termed a geometallurgical block model. Bootstrapped non-linear regression models by projection pursuit were built to predict grindability indices and recovery, and quantify model uncertainty. These models are useful for populating the geometallurgical block model with response attributes. New multi-objective optimisation formulations for block caving mining were formulated and solved by a meta-heuristics solver focussing on maximising the project revenue and, at the same time, minimising several risk measures. A novel clustering method, which is able to use both continuous and categorical attributes and incorporate expert knowledge, was also developed for geometallurgical domaining which characterises the deposit according to its metallurgical response. The concept of geometallurgical dilution was formulated and used for optimising production scheduling in an open-pit case study.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201