CASE SCeNARIOS

Fleet Optimization

Problem Statement: Autonomous Haul System (AHS) is not achieving expected performance metrics. 

Objective: Simulate AHS fleet with the purpose of identifying key performance levers, testing hypothesized performance improvement on the system, and quantify discrete performance impact to ranking of performance initiatives.

Approach: Modeled fleet behavior and performance from Fleet Management System (FMS) and Autonomous Control System (ACS) over actual haul routes, within the defined operating environment and interacting with the other production and auxiliary equipment fleet. 

  • Create high fidelity baseline simulation that emulates the haulage system, dynamic areas, number of haul trucks, other Autonomous Operating Zone (AOZ) equipment interaction, loading scenarios, haul truck events (downtime, standby, operating delays and non-productive time), actual speed profiles by road segment and calibrated to match production rates. 
  • Identified and simulated variable rates of high impact events, reduction of speed constraints, improved exchanges at shovels, performance in dynamic areas. 
  • Vary fleet size to test production impact. 

1. BASELINE

  • Emulate “as-is” operations
  • Validate accuracy & establish baseline for experiments
  • Road network
  • Truck behaviour and events
  • Speed analysis
  • Bunching analysis

2. Bunching

  • Bunching analysis
  • Escort/Bubble use case
  • Impact of bunching events on system performance
  • Reduce wait on escort & bubble events
  • Shovel event reduction

3. Fleet Analysis

  • Ease system constraints
  • Additional shovel scenarios
  • Additional truck sensitivity
  • Shovel event reduction

4. Sensitivity

  • Return all experiments for best combination
  • Sensitivity (0-100%) of event reduction

Identified key system impacts and strategies towards improved system performance with quantified benefits.

  • Generated optimized truck/shovel fleet allocation which showed significant operational performance improvements.
  • Modeled and provided a value prioritized talk list for AHS improvement based on customer initiatives.

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