An Agent-Based System Framework for Dynamic Mine Scheduling

Decisions in the current and future mining environment are increasingly tied to reducing operating costs. Improving performance, productivity and profitability is crucial. Production, ancillary, plant and shipping equipment need to be monitored and controlled by online systems delivering production statistics and real-time information. Traditional systems currently in use today, operate in an iterative mode constantly switching between scheduling and execution. Techniques from Artificial Intelligence have already been used in Intelligent Manufacturing for more than twenty years. However, the recent developments in multi-agent systems in the new domain of Distributed Artificial Intelligence have brought new and interesting possibilities. This paper presents an agentbased system framework for mine planning and scheduling problems with focus on real time fleet management, plant and equipment performance monitoring, downtime and delay reporting, stockpile management, personnel and equipment tracking and product distribution and transportation.