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MineAlytics Mine Robotic Process Automation

Analytics Analyse

MineAlytics offers an cloud platform for mining data analytics, where you configure your process, establish the boundary conditions of your mine, upload your data and run extensive analytics on your data. In a matter of hours, you can have a full report of the health of your plant in your hands!

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Implementation Implement

Implementation of the most advanced control algorithms can be done through our secure cloud platform, where you select a MineAlytics Robot (algorithm) you want to implement, connect your control system to the selected MineAlytics Robot API and launch the Robot that will instantly start controlling your processes.

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Monitor/Fine Tune Monitor & Fine Tune

To maximise the benefits of an implemented RPA, you can real-time data analytics and KPI monitoring capabilities through the MineAlytics platform. By using the Plant Configuration tool you can specify measurement streams and assign a wide rang of analytics to these streams.

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Mining Process Robotic Process Automation

MineAlytics offers a range of mining specific, process optimisation and control algorithms (robots) that utilise the combination of machine learning, dynamic process modeling, stochastic and sequence model based reliability and alarm prediction and deep-learning assisted computer vision.

  • 1. Robot Selection

    The implementation has never been simpler. It is really an unobtrusive technology with a very quick implementation cycle. MineAlytics robots cover the areas of crushing optimisation and control, dry and wet screen dynamic capacity optimisation and surge protection controls, conveyor burden control, dynamic startup constraint control and AI based volume optimisation, surge bin optimal capacity control, screen house throughput optimisation, thickener optimal water utilisation control, model based stacking and reclaiming.

MineAlytics RPA for Mining
MineAlytics Robotic Process Automation
MineAlytics Robotic Process Automation for Mining - Data Analysis
  • 2. Interface Definition

    Once the analytical step is completed and the available RPA APIs identified, the interface between your systems and MineAlytics needs to be established. We can provide you with the necessary IoT gateways, media converters, data concentrators that can interact with your plant supervision layer (DCS/SCADA servers, plant historians, SQL databases, etc.), the control layer (PLC, DCS, PAC) or with the sensor layer (IEDs, instruments, actuators, VSDs, cameras etc.).

MineAlytics Robotic Process Automation for Mining
  • 3. Realising Value by MineAlytics RPA

    Once the RPAs are connected to the process they start observing and learning process bottlenecks, inefficiencies and underutilisation. This information will be readily available for plant operators and provides the basis for the RPAs to start and take control of the processes. Different RPAs have different responsibilities some have distinct functions, while others look for complex objectives and manipulate at multiple layers.

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MineAlytics Robotic Process Automation for Mining

MineAlytics RPAs

  • Haul Truck Optimisation and Scheduling Engine

    An integrated, global optimisation RPA allows maximum utilisation of haul trucks by monitoring plant health and selecting the optimal speed for Autonomous Haul Trucks. Better utilisation of trucks results in instant plant availability improvment, reduction in truck and plant equipment maintenance and increase in production.

  • Autonomous Rock Breaker - Crush & Burn ©

    Our cutting-edge, autonomous Rock Breaker RPA detects bridges in ROM bins or crusher bowls using AI assisted Computer Vision at incredible accuracy. It models the environment in 3D and provides a state-of-the-art inverse kinematics control algorithm to guide the rock breaker in position autonomously and start the cleaning process with maximum precision.

    MineAlytics Crush&Burn Autonomous Rock Breaking
  • Data-driven Feeder Control

    Advanced Feeder Discharge Models incorporate ROM bin level, ore characteristic and PSD to provide an accurate representation of the discharege flow. All MineAlytics models are based on real, process data so they can adapt to the specific operating conditions.

  • Plant Health Heat-Mapping

    One of our most popular RPAs monitors plant equipment and calculates Overall Equipment Efficiency. The insight is turned into a heat map overlay real-time that visualises plant health. Our heatmapping RPA goes even a step forward by creating predictive models and visualising plant health in the future.

    MineAlytics Plant Health Heat Mapping
  • Conveyor Surge Detection and Recovery Control

    MineAlytics RPAs are able to predict surges based on a number of process variables. Once a surge is predicted a recovery control algoirthm takes control of the conveyors and smoothes the surge out so it does not cause any issues downstream.

  • Surge Bin Capacity Optimiser

    The Surge Bin Optimiser RPA learns if a bottleneck is on the feed or the discharge side of bin. The information is then used to balance the operation and prevent plant stoppages. The optimisation scheme is data driven and learns over time so changes to plant infrastructure does not affect its performance.

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