Finite scheduling demo
Routing-level capacity truth
The plant is not late because of “bad execution.”
It is late because the schedule was impossible before production even started.
This demo uses your uploaded WO & Operations dataset to expose the true bottleneck machine, calculate the hidden factory cost created by OEE loss, and show how one overloaded resource causes a queue explosion that ERP-style planning does not see.
Total routing load
485.8 hrs
From operation-level planned minutes
Actual hours at current OEE
694.0 hrs
This is the real plant time consumed
Hidden factory cost
$20,820
208.2 lost hrs at $100/hr
Required 48-hr resources
14.5x
Equivalent machine windows required
Scenario controls
Headline for the demo:
ERP sees order-level hours. Finite scheduling sees routing load against actual machine capacity. In this dataset, the Haas VF-2 is the first point where the plan breaks.
ERP sees order-level hours. Finite scheduling sees routing load against actual machine capacity. In this dataset, the Haas VF-2 is the first point where the plan breaks.
| Bottleneck machine | Haas VF-2 |
|---|---|
| Planned load | 65.0 hrs |
| Actual load at OEE | 92.9 hrs |
| 48-hour overload | 44.9 hrs late |
| Orders touching spillover zone | 21 |
Assumes a single 48-hour resource window per machine to illustrate the impossible schedule condition.
Machine load vs available 48-hour window
Any machine above 48 hours is overloaded even at 100% efficiency. Move the OEE slider and watch the real load expand.
Why the queue explodes
One constrained machine turns the whole routing network into a traffic jam. Upstream resources complete work and push it forward, but the bottleneck cannot absorb the flow.
Release all WOs
→
Upstream ops finish
→
Haas VF-2
overloaded
overloaded
→
WIP queue grows
→
Downstream starved / orders late
Executive takeaway: dashboards tell you what happened. Finite scheduling tells you what cannot happen on time given the machine reality.
Bottleneck queue spillover sequence
These are operations queued on the bottleneck machine. Once cumulative time crosses 48 hours, the order is mathematically late even before execution losses are added.
Talk track for your demo
“ERP thinks the plant can start everything now. But routing-level capacity says otherwise. The moment we load the work against the machines, Haas VF-2 becomes the governing constraint. That queue grows, downstream machines wait, and on-time delivery collapses. This is why finite scheduling beats ERP planning.”
| Point | Message |
|---|---|
| 1 | Order-level hours hide machine-specific overload. |
| 2 | Setup + routing + OEE convert a “possible” plan into an impossible one. |
| 3 | The bottleneck governs lead time, queue size, and late delivery risk. |
| 4 | Finite scheduling prevents chaos by sequencing work against real capacity. |
Finite scheduling demo
Routing-level capacity truth
The plant is not late because of “bad execution.”
It is late because the schedule was impossible before production even started.
This demo uses your uploaded WO & Operations dataset to expose the true bottleneck machine, calculate the hidden factory cost created by OEE loss, and show how one overloaded resource causes a queue explosion that ERP-style planning does not see.
Total routing load
485.8 hrs
From operation-level planned minutes
Actual hours at current OEE
694.0 hrs
This is the real plant time consumed
Hidden factory cost
$20,820
208.2 lost hrs at $100/hr
Required 48-hr resources
14.5x
Equivalent machine windows required
Scenario controls
Headline for the demo:
ERP sees order-level hours. Finite scheduling sees routing load against actual machine capacity. In this dataset, the Haas VF-2 is the first point where the plan breaks.
ERP sees order-level hours. Finite scheduling sees routing load against actual machine capacity. In this dataset, the Haas VF-2 is the first point where the plan breaks.
| Bottleneck machine | Haas VF-2 |
|---|---|
| Planned load | 65.0 hrs |
| Actual load at OEE | 92.9 hrs |
| 48-hour overload | 44.9 hrs late |
| Orders touching spillover zone | 21 |
Assumes a single 48-hour resource window per machine to illustrate the impossible schedule condition.
Machine load vs available 48-hour window
Any machine above 48 hours is overloaded even at 100% efficiency. Move the OEE slider and watch the real load expand.
Why the queue explodes
One constrained machine turns the whole routing network into a traffic jam. Upstream resources complete work and push it forward, but the bottleneck cannot absorb the flow.
Release all WOs
→
Upstream ops finish
→
Haas VF-2
overloaded
overloaded
→
WIP queue grows
→
Downstream starved / orders late
Executive takeaway: dashboards tell you what happened. Finite scheduling tells you what cannot happen on time given the machine reality.
Bottleneck queue spillover sequence
These are operations queued on the bottleneck machine. Once cumulative time crosses 48 hours, the order is mathematically late even before execution losses are added.
Talk track for your demo
“ERP thinks the plant can start everything now. But routing-level capacity says otherwise. The moment we load the work against the machines, Haas VF-2 becomes the governing constraint. That queue grows, downstream machines wait, and on-time delivery collapses. This is why finite scheduling beats ERP planning.”
| Point | Message |
|---|---|
| 1 | Order-level hours hide machine-specific overload. |
| 2 | Setup + routing + OEE convert a “possible” plan into an impossible one. |
| 3 | The bottleneck governs lead time, queue size, and late delivery risk. |
| 4 | Finite scheduling prevents chaos by sequencing work against real capacity. |