SET - Data-driven Modeling for Moveable Asset Logistics

Developing simulation models for movable asset operations (haul trucks, loaders, shovels, etc.) in heavy industries such as mining, is complex and time-consuming. There are many dependencies on multiple systems and data sources, as well as interactions with overall operations. Fleet management systems monitor and record operational data on movable assets. However, the data is collected in real-time but only viewed in hindsight, resulting in reactive operations. The analysis of the collected data can provide valuable insights on utilisation, availability, idle time, etc. but lacks real-time responsiveness. Therefore, it falls short when it comes to scheduling, planning, target adherence and overall system performance. By integrating data-driven simulation technologies with fleet management systems, the simulation model will become a predictive analytics tool, incorporating historical and real-time data. The integrated solution can support performance optimisation, provide accurate planning and scheduling, track target adherence, support proactive asset management, and improve cost management. With the proprietary data-driven modelling approach, the simulation model uses fleet management data to automatically build the simulation model, inclusive of the haulage network. This approach enables a standardised methodology to be applied and reduces the time and costs associated with the construction of such models. Complex model logic is replaced with our proprietary approach, which is fully driven by operational data using the Simio® Simulation Software. This session showcases how such technology can bring the industry a step closer to benefitting from the Digital Twin.