Application of Machine Learning to Resource Modelling of a Marble Quarry with DomainMCF

Machine learning is constantly gaining ground in the mining industry. Machine learning-based systems take advantage of the computing power of personal, embedded and cloud systems of today to rapidly build models of real processes, something that would have been impossible or extremely time-consuming a couple of decades ago. The widespread access to the internet and the availability of cheap and powerful cloud computing systems led to the development and acceptance of tools to automate resource modelling processes or optimise mine scheduling, using machine learning methodologies. The domain modelling system discussed in this paper, called DomainMCF, has been developed by Maptek, using artificial neural network technology. In the application presented in this paper, DomainMCF is used to model the spatial distribution of marble quality categorical parameters, and the results are combined to produce a final marble quality classification using drillhole and quarry face samples from an operational marble quarry in NE Greece. DomainMCF was made available for this study as a cloud processing service through an early access program for individuals or companies interested in testing its capabilities and suitability in various modelling scenarios and geological settings. The resulting marble product classifications are compared with those produced by the already established classification system that is based on a more conventional estimation method. The produced results show that DomainMCF can be effectively applied to the modelling of marble quality spatial distribution and similar domaining problems.

IMPORTANCE OF THIN SEAMS RECONCILIATION IN A NEW COAL MINING PROSPECT AREA

Coal thin seams in the coal mining industry are often considered by company as waste material or it is not gives a significance revenue. Actual condition it is true but this seams actually can be mined potentially and giving some additional profit if we do the plan and managed it correctly. In this paper will discuss and explaining about how much the importance related to optimalization of coal thin recovery in coal mining industry in the technical and economical perspectives. Starting on the iso-thickness polygon in the pit shell design that have been agreed (sign off) to coal reserves reconciliation that had mined completely. The Geologist must undertakes monthly monitoring about the sum of coal thin seams and it is variance between actual versus model. If they find loses indication, they must to do investigation immediately. The writer take a study case from one of area’s PT Arutmin Indonesia consession. The located of research area is situated in “Pit 4 Spessartine” with the coal thin seams succession from interval delta lower 2 – echo 1 lower. The Stratigraphy of research area is a part of Warukin Formation – Asem Asem Sub Basin. If we look in the engineering, mine scheduling, operational sequence and also marketing linkage perspectives, actually these thin seams gives a much economical profit but on the other hand it can gives a loss material such as coal contamination and increasing of ash content. In this paper the writer also reviewing the geological perspective so it can be known about the general parameters which controlled about coal sedimentary deposited among of them. We will disclose the paleo-peats distribution, paleo-base of their wet land or marsh and the last one is knowing about the water currents within the coal depositional environment.

Automatic closed-loop scheduling in underground mining using discrete event simulation

SYNOPSIS Today's mining operations require fast reporting and rapid rescheduling based on updated information. An automatic mine scheduling system could not only quickly reschedule but also propose alternative solutions. To avoid the financial and physical risks associated with testing such a system directly in operation, it could be first evaluated via discrete event simulation models. This would offer a safe environment to evaluate different operating rules and algorithms. In this study, this is achieved by integrating automatic scheduling software with a discrete event simulation model. Keywords: discrete event simulation; production planning; scheduling system; underground mining.