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During the last few decades, the mining industry has increasingly turned to autonomous systems in its efforts to modernize and advance mining methods and techniques. Vehicle automation in such complex working environments can play a critical role in improving worker safety and mine productivity. Moreover, as the global demand for minerals continues to increase, such technologies will enable access to deeper and more difficult to mine orebodies. The research reported in this article seeks to demonstrate the feasibility of autonomous batch haulage vehicles in the underground coal mining production cycle. By introducing autonomous shuttle cars, the operator can be removed from dusty, noisy, and potentially dangerous conditions and be placed in a relatively safe location, while supervising the machine rather than operating it. This article presents an overview of the approach taken, a description of a lab-scale model and mock mine environment, and preliminary results for autonomous navigation of the prototype shuttle car.

Highlights • Granting of the Social License to Operate (SLO) is extremely important at the prefeasibility or bankable feasibility phase of a mining or a coal mining project. Feasibility studies typically focus on technical aspects of a mining project • Loss of the SLO can result in disruptions of the Value Chain business model. • A Mining Operational Risk Management Model (MORMM) was developed to incorporate risk probabilities and risk severities evaluated by experts. • Hazard categories, hazards and hazard indicators are identified and evaluated for a hypothetical coal mining project., The Social License to Operate (SLO) and the Value Chain business model are basic elements that need to be considered both at the planning and operation stages of mining operations and in particular in coal mining projects. If a coal mining enterprise loses its SLO, it may face risks in operations, which may lead to value chain risks. One of the causes of enterprise failure as related to coal mining operations is the inability to reliably assess/manage risk holistically and the inability to understand that lack of SLO is a critical risk. Although financial risks are typically assessed for mining projects, lack of SLO risk should also be taken into account starting as early as the bankable feasibility study. Furthermore, as it is difficult to establish a proactive decision-making policy for SLO risk in coal mining operations, the Operational Risk Management (ORM) methodology is probably a good tool to apply towards that goal. For this reason, a Mining Operational Risk Management Model (MORMM) was developed to incorporate risk probabilities and risk severities evaluated by experts. The final risk assessment is coded using Risk Assessment Codes (RACs). A hypothetical scenario was developed utilizing the MORMM model in order to illustrate how risks can be managed during the SLO granting process. This scenario describes a hypothetical coal mining project evaluated by virtual risk evaluators under specific hazard categories. Risk evaluation involves the assessment of risk probability and risk severity. Through this scenario this paper presents ways: (i) to establish a baseline ORM process that will be applicable to any coal mining operation environment, and (ii) to provide a theoretical example to demonstrate how the method can be applied to coal mining operations. The resulting RACs can provide critical information to decision makers regarding the rejection, acceptance or re-engineering of the mining business plan.

“Web ground control” (webGC) provides users with instantaneous access to mine design applications anywhere, at any time, through a web browser. Utilizing a web-based multiple-tier architecture, users are able to easily access ground control designs, perform on-demand calculations in the field, as well as facilitate project collaborations across multiple users, devices, and operating systems. Currently, the webGC platform contains five ground control related design applications previously developed and distributed by the US National Institute of Occupational Safety and Health (NIOSH), that is, analysis of roof bolt stability (ARBS), analysis of longwall pillar stability (ALPS), analysis of retreat mining stability (ARMPS), analysis of retreat mining stability–highwall mining (ARMPS-HWM), and analysis of horizontal stress in mining (AHSM). With respect to design decisions made by the webGC development team, the webGC platform will be able to further integrate future mine design applications providing the mining industry with one of a kind umbrella suite of ground control related software available at ones fingertips. The following paper provides a detailed overview on the current state of the webGC platform with discussions ranging from back-end database development and design to the front-end user-platform interface. Based on current progress in platform development as well as beta testing results, the webGC platform is scheduled for release in the fall of 2018. Keywords: Ground control, Stability, Web application, Cloud computing

The last few decades, the mining industry has turned to autonomous systems in its efforts to modernize and advance its methods and techniques. Automation in such complex working environments can play a critical role in improving worker safety and mine productivity. Moreover, as the global demand for minerals continues to increase, such technologies will enable access to deeper and more difficult orebodies. The research in this paper seeks to demonstrate the feasibility of autonomous machinery in the underground coal mining production cycle. By introducing autonomous shuttle cars, the operator can be removed from dusty, noisy, and potentially dangerous conditions and be placed in a relatively safe location while supervising the machine instead of operating it. This paper presents preliminary results for autonomous navigation of shuttle cars in the underground coal mining cycle. A lab scale prototype equipped with several exteroceptive and proprioceptive sensors has been developed and is being tested in a mock mine plan, simulating several navigation scenarios within a room and pillar section.

This paper presents a data management application driven by real-time events, which has been developed as a productivity and maintenance planning software application to be used in the surface lignite mines in Northern Greece. The mines operate using a continuous mining system comprised of multiple bucket wheel excavators, belt conveyors, spreaders and stackers. There is a control centre for each mine, comprising of aspect servers, OPC servers and a SCADA system which interfaces with PLCs at each equipment unit in the field. The overall data management infrastructure is installed on the main network system and draws data from the OPC servers at each mine. In order to collect the data, the application is developed using event driven functionality as well as data polls. Data can then be modified by the control tower personnel. The application generates reports on a daily basis for production monitoring, productivity, equipment performance and utilisation as well as various maintenance tasks. The system has been in operation at the surface lignite mines in northern Greece since 2011 and has been embraced by mine personnel for decision making and planning.

A cloud-based near real-time data management system for geotechnical monitoring that can efficiently record, transfer, store, manage, process, analyse and evaluate monitoring data and generate easy to view and use information is presented. The database structure and manual of the system functionalities for addressing issues during data upload and processing, record handling for multisensory devices, data visualisation using common reference dates, data error correction and parametric handling of import files are presented in detail. New features that are in development include a more robust warning system and a journaling system for visual observations. The system can reliably and quickly generate alarms and information about excessive movements with respect to mining and other operations that require monitoring.