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Dynamic Scheduling for MRO Planning Control

Aviation

Dynamic Scheduling for MRO Planning Control

Dynamic Scheduling for MRO Planning Control

Success Story

An MRO doubled its maintenance lines but had outgrown its planning process. Bay utilization sat below the industry benchmark, mid-check disruptions absorbed days of planner time, and parts shortages surfaced at the bay rather than at planning. Scalefocus deployed a constraint-based dynamic scheduling layer above AMOS that validated bay availability, technician certifications, and parts readiness before any work package was committed.

The Client

An independent MRO provider scaling from three to six maintenance lines across two countries. Spreadsheet scheduling could not keep pace with the expansion, and the planning process had become a bottleneck, adding cost and constraining growth.

The Challenge

Every schedule change meant a full manual replanning cycle, and with three new lines added, the effort no longer fit the working day. Bay utilization sat at 73%, well below the industry benchmark, and mid-check disruptions pulled the team away from forward work to firefight instead. Parts shortages made it worse: they surfaced at the bay, turning a procurement problem into a slot problem at the worst possible moment.

The Solution

Scalefocus delivered constraint-based dynamic scheduling above AMOS. This enabled reading the maintenance system of record without changing it and automating the replanning that had been consuming planners’ days. The engine now forecasts hangar demand from the AMOS intake plan, then optimizes bay and skill allocation under hard capacity, regulatory, and soft cost constraints.

As a result, parts, tooling, and bay availability are validated before a task is scheduled, so no checks are planned against resources that will not be available. When a check slips, the engine generates ranked recovery plans for the planner to approve.

The solution was rolled out incrementally, starting with a single line, so planners could validate outputs before the full hangar went live.

The Results 

  • Bay utilization improved from 73% to 83%, achieved without adding hangar capacity
  • 60% reduction in mid-check disruption replanning effort, handled by the engine, not by hand
  • Parts-related delays dropped from 15% to 5%, dependency validation before scheduling removes parts-driven slips

The Technologies

Constraint solver
React
.NET microservices
Azure
read-only AMOS integration

Client Success Stories

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