Roster intelligence
Inspect duties, transitions and rest windows. Compare alternative proposals against a common baseline.
Inspect the patternA connected view of aviation fatigue risk. Bringing roster intelligence, transparent modelling and real-world observations into one explainable platform.
A duty tells you when someone works.
The pattern tells you what came before.
Early starts, changing duty times, sleep opportunity and recovery can interact across days and roster cycles. Evaluating each duty in isolation can leave important questions unanswered.
MAFRM follows that continuity: inspect the roster, examine cumulative modelled exposure and make the assumptions visible.
Understand the modelling approachExplore a hypothetical transition after three early duties. Switch the fourth day to see the question a scenario comparison could help investigate.
The fourth duty starts at 12:00 and ends at 20:00. The review question is how this transition interacts with prior early starts and waking time.
Illustrative scenario using synthetic data. It demonstrates the comparison workflow rather than a live MAFRM result. Sleep, commute and starting-state assumptions are not included in this example.
Connect what was scheduled, what the model indicates and what independent observations show—without confusing one for another.
Inspect duties, transitions and rest windows. Compare alternative proposals against a common baseline.
Inspect the patternCarry model state across time. Make starting assumptions, configuration and interpretation explicit.
Explore the modelKeep sleep, physiological observations, fatigue reports and functional testing in a separate evidence layer.
Follow the evidenceUnderstand recurring roster patterns and the questions they raise.
↗02Bring transparent analysis into a broader fatigue management process.
↗03Assess proposed working patterns with consistent assumptions.
↗04Help test the relationship between predictions and observations.
↗MAFRM brings together roster review, continuous modelling and scenario comparison. Its roadmap extends this foundation into connected roster history, real-world observations and independent performance evaluation.
The aim is simple: make the reasoning behind each result visible, keep evidence types distinct and improve the quality of fatigue-risk conversations.
Developing a roster proposal, investigating an operational pattern or planning fatigue research? Let’s explore where MAFRM could contribute.