Connected Operations &
Fleet Intelligence
A large logistics operator managed a mixed fleet across air and ground networks. Unexpected equipment failures and reactive maintenance were impacting reliability. We engineered a real-time intelligence platform to predict disruptions before they occurred.
The Context
The client operated a massive fleet of cargo aircraft and ground vehicles. Maintaining service levels meant ensuring every asset was ready to move. However, operational data was fragmented across IoT sensors, maintenance logs, and route systems.
Decisions were reactive. A single component failure could ground an aircraft, triggering a cascade of shipment delays, rerouting costs, and missed SLAs.
The Friction Point
Telemetry data was siloed. Failures were detected too late. Maintenance was schedule-based rather than condition-based. Operational downtime was not just a cost, it was a reliability crisis.
Reactive maintenance leading to costly unplanned downtime.
Siloed sensor data preventing holistic fleet health views.
Disruptions cascading into missed customer SLAs.
Engineering Predictive Operations
Real-Time Data Ingestion
We engineered a platform to ingest live sensor data, maintenance logs, and environmental telemetry into a unified data lake.
Predictive Failure Modeling
Machine learning models analyzed component degradation to predict failures days in advance, allowing for preemptive intervention.
Automated Workflow Sync
Maintenance orders were triggered automatically, synchronizing supply chain parts and mechanic availability with vehicle downtime windows.
Impact on Fleet Operations
Unplanned maintenance events.
For component failures.
Annual maintenance spend.
Post-deployment.
Airline Crew Recovery
Operational continuity starts with people. A major airline partnered with RSA Tech to solve one of aviation's most complex challenges: recovering crew schedules during disruptions.
Crew Recovery &
Operational Continuity
Solving the puzzle of crew alignment during weather disruptions with AI-driven optimization.
The Challenge
For a major global airline, weather disruptions and airport congestion frequently caused cascading delays, leaving crews "timed out" or out of position. Manual recovery planning took hours, leading to flight cancellations, regulatory risks, and significant financial loss.
Manual scheduling unable to keep up with disruptions.
Fragmented systems for crew tracking and weather.
Regulatory compliance risks during delays.
High cost of crew displacement and overtime.
The Solution: AI Optimization Engine
RSA Tech built an optimization engine that continuously evaluates crew availability, regulatory constraints, and aircraft positioning to generate recovery plans in minutes.
Automated recovery plans.
Real-time crew app updates.
Instant compliance validation.
Minimize overtime and hotels.