Digital past, present, and future of mining industry

The process of introducing digital technologies in mining has an evolutionary character and began with the appearance of electronic computing machines at large enterprises, design and scientific organizations. At the initial stage, solving the tasks of mining technology with the use of computers was mainly of demonstration character. Development of works in this branch has led to differentiation of the general task into separate areas: mining-geological information systems (MGIS); geomechanical safety ensuring systems; dispatching systems; programs for solving individual tasks of mining technology. One of the most important directions of digital transformation is mining-geological information systems (MGIS), the development of which went, as a rule, from solving tasks of deposit reserves estimation to modeling of mining technology objects, tools for solving surveying tasks, design and planning of mining works. Evaluating the functionality of MGIS known in the Russian market, we can state that the achieved development level generally meets the requirements of a Digital Mine - the way of representation of objects and processes of mining technology as digital models describing the properties and behaviour of real objects in a single digital space of the enterprise. The next stage of digital transformation is a Digital Twin, which can be characterized as a Digital Mine that has on-line communication links between real equipment units and their digital models. Creation of the Digital twin implies real-time reproduction of the natural-engineering system functioning, reflecting its actual or forecasted state.

Modelling Large Heaped Fill Stockpiles Using FMS Data

The frequent best practice for managing large low-grade run-of-mine (ROM) stockpiles is to average the entire stockpile to only one grade. Modern ore control and mineral processing procedures need better precision. Low-precision models hinder the ability to create a digital mine-to-mill model and optimize the holistic mining process. Prior to processing, poorly characterized stockpiles are often drilled and sampled, despite there being no geological reason for relationships between samples to exist. Stockpile management is also influenced by reserve accounting and lacks a common operational workflow. This paper provides a review of base and precious metal run-of-mine (ROM) pre-crusher stockpiles in the mining industry, and demonstrates how to build a spatial model of a large long-term stockpile using fleet management system (FMS) data and geostatistical code in Python and R Studio. We demonstrate a framework for modelling a stockpile believed to be readily workable for most modern mines through use of established geostatistical modelling techniques applied to the type of data generated in a FMS. In the method presented, each bench of the stockpile is modeled as its own geological domain. Size of dump loads is assumed to contain the same volume of material and grade values that match those of the grade data tracked in the FMS. Despite the limitations of these inputs, existing interpolation techniques can lead to increased understanding of the grade distribution within stockpiles. Using the framework demonstrated in this paper, engineers and stockpile managers will be able to leverage operational data into valuable insight for empowered decision making and smoother operations.

How Will the 4th Industrial Revolution Influences the Extraction Industry?

Even the third industrial revolution has never been officially finished, from some time an expression Fourth Industrial revolutiongot viral. It has started in 2011 with a project of German government, called Industrie 4.0, which was initiated during the HanoverExpo in 2012. In 2013 an official report on that project was issued.The article explains the term of 4th industrial revolution and tries to foresee influence of that phenomena on extraction industry.The big challenge of digitalization and cybernetic systems implementation carries a large saving potential, estimated to astonishing321 Bio. USD till 2025 but also risks and challenges to overcome. Discussion in the paper includes the most important technologieswith their state of development and existing implementations including autonomous machines in both underground and open pitmining, technology of self-operating drilling rigs and driverless trucks in open pits.Briefly description of current situation and a picture of the mining industry after extended automatization is presented. It touchesalso the challenges of the new industry concept and highlights a road map for the full digital mine.

Development of Digital Subterranean Models for Real-Time Open Cut Horizon Control

A reliable coal seam sensing system is required to improve the productivity of selective mining in open-cut mining operations. A prototype system based upon commercial ground penetrating radar equipment, which measures coal thickness from the top of an exposed surface down to an underlying coal-interburden interface and generates digital subterranean models of the subsurface seam boundaries, was developed for this purpose. The models can be deployed to commercially available in-cab assistive guidance systems for bulldozers and other mining machinery in existing production processes, and can further contribute to the databases required for remote operation and control in a complete digital mine scenario. The system was evaluated at a production open cut coal mine in Queensland, Australia, with promising results. The benefits reported by operational personnel who evaluated the digital surface model in the mining environment provide strong motivation for ongoing technology development.

Cousins, Siblings and Twins: A Review of the Geological Model’s Place in the Digital Mine

Digital mining is a broad term describing the enhancement of the physical mining method through the use of digital models, simulations, analytics, controls and associated feedbacks. Mining optimisation will be improved through increased digitisation and real-time interactions via a “digital twin”, however digitisation of the rock mass component of this system remains problematic. While engineered systems can be digitally twinned, natural systems containing inherent uncertainties present challenges, especially where human-intensive procedures are required. This is further complicated, since the mining system is designed not only to interact with, but to substantially and continually alter its surrounding environment. Considering digital twin requirements and geological modelling capabilities, we assess the potential for a mine’s synchronised digital twin to encompass the complex, uncertain, geological domain within which it interacts. We find that current geological (and indeed hydro-geological) models and simulations would support digitisation that could be considered to provide, at best, a digitised ‘cousin’. Based on this assessment, the digital twin’s value for medium term forecasting of mining operations may be limited and we discuss technological advancements that can mitigate this.

Mining in the twenty-first century and its world of work: Considerations for universities offering mining qualifications

The intelligent digital mine of the future will look very different to what we have today; it will be managed differently, have different skill-sets, and will be staffed by professions that do not exist today. While mining in the 20th century was about ‘more’ (more production, for example), the 21st century is about ‘better’ (safer production, for example). This article investigates this fundamental shift from ‘more’ to ‘better’ by examining how the current international trends affect mining and its world of work. There are clear indications that the future of work requires a re-evaluation of skills-sets, qualifications and certification thereof. Although this shift creates a problem for current mine occupations with outdated skills-sets, there are many new opportunities for those who update their skills and knowledge so that they remain (or become) relevant in a cross-industry 21st century context. The approach followed in this article is an interpretation of how the fourth industrial revolution affects the world – and mining in particular – followed by a conceptual analysis of how it is shaping the future of work for mining. The fundamental learning content for a future-ready mining engineering graduate is then addressed. The findings of this article will benefit mining in general, but more particularly universities, skills providers and, most important, the youth who are preparing themselves for this world of work in mining.

A Mining Technology Collaboration Platform Theory and Its Product Development and Application to Support China’s Digital Mine Construction

At present, data exchange in China’s digital mine construction process is still based on paper media or electronic documents. The problems of “information islands,” “information versions,” “information faults” and “information preservation” are serious. There are many problems associated with across time and space and multidisciplinary collaborations, blocked business processes and unclear job responsibilities. These problems have seriously hindered the construction of China’s digital mine, thus restricting the safe, efficient production and sustainable development of China’s mining enterprises. Therefore, this paper proposes the concept, connotation, characteristics, architecture and technical requirements of the mining technology collaboration platform and uses it to guide the research and development and implementation of the mining technology collaboration platform of Fujian Makeng Mining Co., Ltd. The results show that the mining technology collaboration platform can solve the information and management problems existing in China’s digital mine construction and realize the centralized storage, interoperability and high sharing of all data, the integration of all involved business, business software and its participants, the clarification of responsibilities and its input and output data of each post and standardization and automation of business process. Therefore, it improves the ability to collaborate across time and space and multidisciplinary among participants, departments and professional posts, ensures high-speed flow of business processes and also improves the working efficiency and quality of mining enterprises and significantly reduces the time for business processing and business process flow and reduces production costs.