01 / Establish
Retain the baseline
Record source history, starting state, applicable rules and model configuration. Make gaps in the input explicit.
MAFRM / 03
Roster intelligence & scenarios
Change the roster.
Ask a better question.
Before changing a duty pattern, examine what else changes with it. MAFRM supports transparent comparisons across a common baseline.
Explore the concept
Three early starts.
What should follow?
These hypothetical rosters differ on day four. The illustrative scenario shows how a shared-baseline comparison can reveal the questions created by one change.
One change. A different recovery opportunity.
Illustrative scenario · synthetic dataA / Early-to-late transition
Day 01 / Early
04:00–12:00Day 02 / Early
04:00–12:00Day 03 / Early
04:00–12:00Day 04 / Proposal
12:00–20:00
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.
Look beyond the edited duty
A change can travel
through the roster.
Moving one duty can alter the preceding rest window, estimated waking time and recovery available afterwards. A meaningful comparison needs to follow the downstream sequence.
The workflow retains the baseline, changes only the proposed inputs and recalculates with the same model and configuration. Differences can then be traced to the change and its assumptions.
The comparison provides structured evidence for review alongside operational context, applicable requirements and the wider fatigue-management process.
The comparison workflow
Keep the comparison honest.
02 / Change
Isolate the proposal
Keep an understandable change list. Compare named alternatives with an identical baseline and consistent assumptions.
03 / Review
Inspect the consequences
Review duty-level differences, downstream effects, rule findings and sensitivity to assumptions separately.
Roster design & shift transitions.
Potential applications include comparing consecutive early starts, transitions between early and late work, protected recovery windows and alternative duty commencement times.
The right question is not simply whether the fourth duty is shorter. It is what happens to the complete pattern of work, waking and opportunity for sleep.
Operational & agreement proposals.
Airlines, planners and pilot representative organisations can use consistent scenario assumptions when examining proposed roster rules or working arrangements.
MAFRM provides analytical support for that discussion while keeping operational requirements, consultation and industrial considerations in their proper place.
Patterns across a population.
A change may benefit some roster patterns while shifting exposure elsewhere. Population analysis can compare distributions and identify groups or transitions warranting closer review.
Aggregate analysis depends on appropriate privacy controls, reporting thresholds and protection of identifiable roster or health information.
Scenario capability
Start with one change.
Expand the comparison.
The current prototype supports exact single-duty edits on an isolated copy, named A/B/C scenarios and shared-baseline warnings, with records retained locally in the browser.
The roadmap extends this into added and resequenced duties, controlled sensitivity analysis and durable collaborative scenario records.
Explore the development roadmapHelp shape what comes next
A better question starts
with a conversation.
Developing a roster proposal, investigating an operational pattern or planning fatigue research? Let’s explore where MAFRM could contribute.