Automating The Connected Mine

Versatile industrial PCs operating within the distributed control system (DCS)

consolidate workloads to streamline operations, develop efficiencies and reduce

the hardware footprint at the rugged environment. Mining automation with

industrial PCs integrated at facilities, equipment and vehicles removes operators

from hazardous or mundane duties, instead developing a highly-skilled crew

through safe, rewarding tasks. With safety as a top concern, shifting mining

operations to more efficient automation helps keep mining operators out of harm's

way and in safe underground control rooms.

Computing At The Edge

Powerful computing has brought the ancient labor of mining into the Industry 4.0 fold. Through mining automation with industrial PCs, purpose-built computers support the DCS by aggregating and processing data close to the source and subordinate devices for safer, more efficient operations. Ruggedized hardware with reinforced features allows reliable integration in volatile, hazardous settings.

Connectivity For The Edge

Seamless connectivity supplies rapid, reliable communication to mining

automation through industrial PCs hosting a rich combination of physical and

wireless connection technologies. Reinforced physical I/O connections join

legacy and leading-edge equipment to data processing and control hardware, 

streamlining enterprise DCS integration. Wireless technologies enable smooth

data sharing between devices and workstations on the DCS. Strong

connectivity supports Remote Operating Systems (ROS) that keep mine

operators out of treacherous areas, ensuring a top-level overview for strict

safety standards.

Inference Analysis And Machine Learning

Inference analysis lends powerful parallel compute capabilities to complex data processing across numerous layers of mining operations. Inference analysis accelerates mining automation with industrial PCs processing vast data inputs to unearth fresh efficiencies, yield greater accuracy and deliver a higher ROI than standard computing allows. Localized inferencing and real-time computing depend on a significant amount of data collection for machine learning models. These algorithmic models can provide more automation, productivity and operational efficiency in extremely dangerous mining environments. Machine intelligence can help provide better insights and decision-making in highly reliable site prospecting, materials classification, resource management and systems autonomy processes at every mining stage.