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Traditional ore-waste discrimination schemes often do not take into consideration the impact of fluctuations of the head grade, which have on the performance of mineral processing facilities. This research introduces the use of target grades for processing destinations as an alternative to cut off grade-based methods and models, in each processing destination, the losses due to deviation from targets via the Taguchi loss function. Three unsupervised learning algorithms, k-means clustering, CLARA and k-mean-based approximate spectral clustering, are presented to group mine planning blocks into clusters of similar grades with different processing destinations. In addition, a technique considering uncertainties associated with block grades is proposed to generate new sequences that reduce variation in processing capacities across the life of mine (LoM). The case study in this paper involves the treatment of a realistically large mining dataset. The results showed that clustering methods outperform cutoff grade-based method when divergence from target grades is penalized and that reclassification of blocks based on data from geostatistical simulations could achieve smoother capacities for processing streams across the LoM.

Sublevel stoping is a commonly used underground mining method in which the profit can be increased by optimizing the layout plan. The complexity of the sublevel stope layout problem is demonstrated...

This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry. Latent variable modeling, which is a statistical model that relates observable and latent variables, could be used to facilitate researchers’ understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system. This enhanced understanding, in turn, can help emphasize the important factors to improve mine safety. The most commonly used techniques include the exploratory factor analysis (EFA), the confirmatory factor analysis (CFA) and the structural equation model with latent variables (SEM). A critical comparison of the three techniques regarding mine safety is provided. Possible applications of latent variable modeling in mining engineering are explored. In this scope, relevant research papers were reviewed. They suggest that the application of such methods could prove useful in mine accident and safety research. Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations. Keywords: Latent variables, Exploratory factor analysis, Confirmatory factor analysis, Structural equation modeling, Occupational health and safety, Mine safety

A widely used unsupported underground mining technique is sublevel stoping, in which portions of ore-body within certain size constraints are extracted. In this article, a sequential approach is pr...

SYNOPSIS Underground mining operations tend to have higher operating costs than surface mines. When metal prices decrease, profitability is jeopardized due to the high costs. Therefore, mining management harnesses new practices that increase operational efficiency. One way to manage this challenge is to invest in new mine planning practices. Stope layout optimization as a part of underground mine planning aims to identify a portion of the orebody in the form of production volumes (stopes) to maximize profit under roadway and stope dimension constraints. In this paper we propose a novel approach based on identifying ore-rich areas of the deposit and prioritizing their extraction through an iterative heuristic clustering approach. The proposed approach is compared with and validated by an exact method through a small mining example. The heuristics produced nearly identical results in a very short time. Finally, a case study was carried out using a larger data-set. The cluster-based iterative approach generated near-optimal stope layouts in a computationally effective manner. Keywords: underground mining, iterative optimization, stope layout planning, sublevel stoping.

As mineral resources exhausted in near-surface deposits of the earth crust, mining operations focus on going more in-depth. Increasing environmental concerns make underground mining more preferable because it is less harmful than surface mining. On the other hand, high operating costs of underground mining bring significant challenges to mining companies. To deal with the challenges associated with high operating costs of underground mining, the mining companies put their efforts to reduce cost and increase the efficacy of mining practices. In current practice, the problem is divided into three sub-problems: stope layout optimization, access road and network, and stope sequencing. Effects of this division on the optimality and computational efficiency are discussed. This paper also analyses recent developments in underground mining planning in such a way as to enhance the efficacy of the operations. New research avenues are proposed.

Surface mining operations extract a large quantity of waste material, which is generally disposed into a dump area. This waste can cause a series of environmental problems ranging from landscape deterioration to acidic water generation and water pollution. Therefore, mine waste management is a significant task in mining operations. As known, in strip mining, the overburden is not transported to waste dumps but disposed directly into adjacent strip which was mined out. This concept can be adapted for mine planning of relatively horizontal deposits through a mixed integer programming (MIP) model. The main idea behind this work is that, in one pit, production voids created in early year of mining are used for waste landfilling in late years of production. In other words, in addition to external dumping, a landfilling option within the same pit is proposed for mine design optimization. The problem is formulated as maximization of the net present value (NPV) of the mining project under the constraints of access, landfill waste handling, mining and processing capacities. A case study using a data set was carried out to see the performance of the proposed approach. The findings showed that this approach could be used in waste management incorporating a landfilling option into mine planning. As a result, material handling costs decrease, and environmental compliance increases due to less external waste quantity.

As a type of general layout problems, dig‐limits optimization focuses on generating the ore‐waste boundaries of a bench sector in an open‐pit mining operation. Typically, blast holes are de...

Histograms are widely used in geosciences for data analysis and visualization. In cases where a distribution is not fitted to data, histograms are often used to address various sampling- and interpolation-related aspects. However, the results of these applications are substantially affected by the histogram’s number of bins as determined by several binning methods. This paper proposes a new binning approach and compares it with various standard approaches to demonstrate the relative performance of the new approach. Cut-off grade optimization for polymetallic deposits, Monte-Carlo modeling, and derivation of conditional distribution, all of which use histograms, are used as case studies. The proposed technique is based on calculating the squared error for each bin in a histogram, and combining the error values to evaluate the total error for each histogram. The new technique then selects the bin number which minimizes the total error. The results showed that the new binning approach is well suited for binning small datasets and can be used in geoscience applications if needed.