Lifting Proactive Monitoring

Anticipate component needs before they become race-day risks

Ferrari applies predictive maintenance to component lifing, connecting each vehicle’s component status with upcoming events, technical interventions and race logistics. Engineers know earlier what each car will need next, giving workshops and trackside operations more time to prepare and reducing avoidable risk before the car reaches the track.

Situation

Win the race before it starts.

In motorsport, reliability and performance are built long before a car reaches the grid. Across multiple championships and events, Ferrari must continuously assess how long critical components can remain in service, when to replace them, and what each vehicle will require before its next race.

Every predictive maintenance decision involves a trade-off. Replace a component too early and usable life is lost. Replace it too late and technical risk increases when the consequences matter most.

Predicting remaining useful life is therefore only the beginning. The real value comes from turning that prediction into a timely decision about replacement, testing, workshop preparation and race logistics.

Key challenges

Turn component life into an operational plan.

Component lifing relied heavily on manual processes. Information about remaining life existed, but converting it into the next operational decision was slow and labour- intensive.

Engineers still had to determine which components required attention, whether replacement could wait, what technical work should be scheduled and which parts had to travel to the next event. Each choice had to balance component life, replacement cost, technical risk and upcoming race requirements.

Those decisions also crossed engineering, workshop, logistics and trackside operations. Without one continuously updated view from component status through to action, preparation required repeated coordination and left less time to anticipate what each vehicle would need next.

Solution & Benefits

Move from monitoring component life to preparing the next decision.

Natzka creates a continuously updated decision environment around the digital twin of each vehicle, connecting component lifecycle, remaining useful life, fleet status, planning and reporting. Component condition is no longer viewed in isolation: it becomes the starting point for replacement, testing, workshop and logistics decisions.

Decision Support

Make the trade-off visible before acting

Remaining component life is evaluated alongside replacement cost, technical risk and upcoming race requirements. Engineers get a clearer view of what needs attention now, what can safely wait and where an intervention matters most for race readiness.

Human in the Loop

Turn predictions into coordinated preparation

AI agents flag components approaching critical lifing thresholds and prepare recommended actions, from replacement to testing or repair. Engineers validate those recommendations against vehicle condition and race context, then translate them into workshop, testing and trackside plans.

Preparation starts earlier with less manual coordination, while engineering judgement remains central wherever technical context or risk requires it.

Decision Automation

Execute repeatable lifing decisions within defined boundaries

Where decisions follow established rules and parameters, the system generates replacement recommendations, identifies testing and repair requirements and determines trackside inventory needs from expected usage and remaining component life. Routine decisions move forward without waiting for repeated manual analysis, while exceptions and higher-risk trade-offs remain under engineering control.

The result

Ferrari anticipates technical requirements earlier and turns them into coordinated workshop, testing and logistics actions before they become urgent, reducing race logistics preparation time and post-race reporting time by 80% and delivering first value within 30 days.