For the Production Planner
Schedule against the shop you have, not the one on the whiteboard.
Planning falls apart when the schedule lives in a spreadsheet and the floor lives in reality. Cortrova schedules finite - against machines, tooling, labor, and material - promises dates through ATP/CTP, and replans the moment a machine goes down or a rush order lands. A governed scheduling agent recommends the recovery move; you decide whether to take it.
The challenge
- !The schedule assumes infinite capacity, so it's fiction by Tuesday and the real sequence lives in the supervisor's head
- !Sales promises dates without asking whether the capacity or the material exists, and planning inherits the miss
- !A machine goes down or a rush order lands, and rebuilding the schedule by hand takes the rest of the day - while the floor runs on the stale one
- !There's no feedback loop: planned versus actual never gets measured, so the same optimistic run times get planned every week
How Cortrova answers
- ✓The finite-capacity scheduler sequences every job against machine, tooling, labor, and material constraints, so the plan you release is one the floor can physically run
- ✓ATP/CTP promising checks live inventory and finite capacity at order entry, so the dates sales commits are dates you can actually schedule to
- ✓When a machine goes down, material runs short, or a rush order lands, the schedule replans in real time and flags the affected orders ranked by impact on ship dates - so you work the exceptions that matter first
- ✓Schedule-versus-actual feedback flows from live floor progress, so planned run times converge on real ones instead of repeating the same optimistic estimate
- ✓The scheduling agent is a governed assistant: it recommends sequences and recovery moves through the platform's AI governance pipeline, and nothing changes until a planner accepts it - with unlimited users, everyone who touches the plan works in the system, not around it
A planner's day
From rebuilding the schedule to deciding on it.
When the schedule replans itself against real constraints, the planner's job stops being spreadsheet reconstruction and becomes what it should have been: judgment calls on the exceptions the system surfaces.
Morning: exceptions, not archaeology
Instead of walking the floor to find out what the schedule missed overnight, you open a schedule that already reflects last shift's actuals, with the orders at risk flagged and ranked by ship-date impact.
When the machine goes down
Downtime feeds the scheduler directly. The sequence re-forms around the constraint, reschedule messages land on the affected work and purchase orders, and you review the moves instead of deriving them.
When the rush order lands
CTP shows what the requested date does to the rest of the board before you commit. You see which orders give ground and by how much, and quote the rush with the trade-off in front of you.
End of week: the loop closes
Schedule-versus-actual comparison shows where planned times ran long or short, so next week's plan starts from evidence - and the estimates stop drifting from the shop.
How it works
Adopting For the Production Planner.
Discovery captures the real constraints
Implementation starts by documenting your machines, work centers, tooling, labor skills, and routing logic - the constraint model the scheduler will sequence against.
Migration brings routings and open orders
Routings, run times, open work orders, and inventory move into one data model, so the first schedule generated is built from your actual backlog, not a fresh start.
Calibration against your floor
During configuration and AI calibration, scheduling behavior is tuned to how your shop actually runs, and planners validate sequences before anything drives the floor.
Go live still holding the wheel
At a validated go-live - typically 4-8 weeks for most manufacturers - the scheduling agent recommends and planners decide. The authority over the schedule stays where it belongs.
FAQ
Questions, answered.
Does the scheduling agent change my schedule on its own?
No. The scheduling agent recommends - a sequence, a recovery move after a breakdown, a way to slot a rush order - and a planner accepts or rejects it. Every recommendation runs through the platform's AI governance pipeline and lands in the audit log, so there is no silent replan and no mystery about why the board changed overnight.
What happens to the schedule when a machine goes down?
Downtime feeds the finite-capacity scheduler in real time. The schedule re-sequences around the lost capacity and raises reschedule messages on the affected work and purchase orders, ranked by impact on ship dates. You review the proposed moves and act on the orders that actually threaten a delivery, instead of rebuilding the whole board by hand.
How does Cortrova stop sales from promising dates we can't hit?
Order promising runs Available-to-Promise and Capable-to-Promise checks at entry. ATP confirms the inventory exists and isn't already allocated; CTP reaches into finite-capacity scheduling to confirm the shop can build the order by the requested date. The date sales commits is one the schedule can hold, so planning stops inheriting promises made by feel.
Can the schedule reflect what actually happened on the floor?
Yes - that's the point of running scheduling and shop-floor execution on one data model. Operation completions, downtime, and material movements feed straight back into the schedule, and schedule-versus-actual comparison shows where planned times diverge from real ones. Over time the plan converges on the shop instead of drifting away from it.
Get started
See Cortrova through the production planner's screen.
We'll tailor a demo to your role, your KPIs, and your operation.