Featured Case Study

Western Australia Mining Giant

How AI-powered scheduling optimization delivered $1.8M savings per shutdown across 27 deployments - with independently verified results.

27
Shutdowns Optimized
$1.8M
Savings / Shutdown
52
Weekly Cycles
$8M
License Savings
20s
Break-in Resolution

The Challenge

A major mining operation in Western Australia faced a critical problem: their planned shutdown required 700 workers, but their remote site could only accommodate 350-400 people.

The original plan required chartering expensive flights to rotate workers in 12-hour shifts - a logistical nightmare that would add millions in costs and introduce significant operational risk.

Key Constraints

  • Remote location with limited accommodation (350-400 capacity)
  • Complex multi-phase shutdown with thousands of work orders
  • Strict safety compliance requirements
  • Tight timeline with no room for delays
  • Multiple trade types requiring precise coordination

The Solution

OptiSchedule AI's AI-powered optimization engine analyzed the entire shutdown workload - thousands of operations across multiple work centers - and discovered that the workforce requirement could be dramatically reduced through intelligent scheduling.

How It Worked

  • Data Integration: Connected directly to SAP to extract all work orders, operations, constraints, and historical patterns from 15-20 previous shutdowns
  • AI Analysis: Multi-agent AI architecture explored trillions of schedule combinations using constraint programming and tree pruning algorithms
  • Optimization: Generated optimal schedules in 5 minutes that would have taken 4 weeks manually
  • Implementation: Schedules written directly back to SAP for execution with real-time adjustments as needed

"The game changed completely. We had capacity for 350-400 people. OptiSchedule AI showed us we didn't need 700 - we needed 320. No more charter planes. Just changed the whole dynamics."

- Operations Director, Mining Site

The Results

The deployment delivered transformational results that have since been replicated across 27 shutdowns with 52 weekly optimization cycles.

700 → 320
Workforce Reduction
54%
Labor Savings
$0
Charter Flights Needed
≈$1.8M
Per Shutdown Savings
20 sec
Break-in Replanning
Zero
Accommodation Conflicts

Key Highlights

  • Eliminated charter flights via optimized workforce sizing
  • Break-in scenarios resolved in seconds vs days
  • 3rd Party Software replacement: ~$8M/yr license savings
  • Zero accommodation conflicts with allocation models
  • 700 → 320 workforce while sustaining full throughput
  • 100% on-time completion maintained

Financial Summary

≈$1.8M savings per shutdown across 27 deployments, with $50M+ annual savings (conservative estimate). Additional $8M/year saved by replacing third-party scheduling software licenses. ROI achieved in less than 60 days from deployment.

Broader Impact

Beyond the immediate shutdown, the platform now optimizes 52 weekly maintenance cycles annually, ensuring consistent labor optimization across all operations.

Operational Benefits

  • 20-50% staff reduction across all optimized jobs
  • 4 weeks → 5 minutes to generate full schedules
  • 20-second replanning for unexpected break-in work
  • Zero constraint violations with auto-enforced compliance
  • 60% reduction in scheduling workforce needed

Technology Advantage

  • Multi-agent AI architecture with master orchestration
  • Explores trillions+ of schedule combinations
  • Market-basket analysis with 89% accuracy
  • Cloud-native design for elastic scaling
  • Bidirectional SAP integration preserving existing investments
  • Continuous learning with each operation

Proven, not promised. All metrics based on live deployments; results independently verified. Patent-pending technology.

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