Finite vs Infinite Capacity Scheduling: Why MRP Schedules Break on the Floor

Key takeaways

• Infinite-capacity scheduling places work to meet due dates and assumes resources can always absorb it.
• Finite-capacity scheduling respects real capacity limits, so it never loads a resource past what it can run.
• Infinite is fast and simple but over-promises; finite is realistic but needs accurate capacity data.
• Mature plants plan with infinite logic and execute with finite logic.

The difference between infinite and finite scheduling is the difference between a plan on paper and a plan the floor can run. One assumes the plant can do whatever the dates require; the other checks whether it actually can.

Infinite-capacity scheduling

Infinite-capacity scheduling schedules each job to hit its due date without checking whether the resource has room. Classic MRP works this way: it will plan three jobs on the same press at the same time because it never looks at the machine.

It is fast, simple, and fine for rough planning over a long horizon. The trouble starts at execution, when those neat due dates collide with a bottleneck that can only do one job at a time.

Finite-capacity scheduling

Finite-capacity scheduling respects the real limits of each resource. It will not load a machine beyond its available time, so when capacity runs out, jobs move to the next open slot and the schedule shows the true completion date.

This produces a plan the floor can actually follow, with realistic promise dates and visible bottlenecks. The cost is that it needs accurate capacity, setup, and calendar data to be trustworthy.

A worked example

Three orders each need four hours on the same press and are all due end of day. Infinite scheduling shows all three finishing on time, because it stacks them in parallel on a machine that can only run one. Finite scheduling sequences them: order one finishes at noon, two at 4 p.m., three slips to tomorrow morning. The finite plan is less comfortable but it is the truth, and it lets you act before you over-promise.

Finite vs infinite at a glance

• Capacity: infinite ignores limits; finite enforces them.
• Dates: infinite gives due dates; finite gives achievable dates.
• Speed: infinite is fast; finite needs more data and compute.
• Use: infinite for rough planning; finite for executable schedules.

Where OEE fits

Finite scheduling is only as good as the capacity it assumes, and that capacity is what OEE measures. If a resource is rated for eight hours but real availability delivers six, a finite schedule built on the rated figure still over-promises. Feeding measured capacity into the model is what makes finite scheduling honest. Book a Fabrico demo to see live OEE sharpen capacity planning. This logic powers APS and shapes both forward and backward scheduling.

Common mistakes

• Promising from infinite plans. Due dates that ignore capacity become missed commitments at the bottleneck.
• Finite scheduling on bad data. Wrong capacity or setup times make the finite plan precisely wrong.
• Using one for everything. Infinite suits long-range planning; finite suits the executable schedule.

Frequently asked questions

Does MRP use finite or infinite capacity?

Classic MRP is infinite-capacity: it plans to due dates without checking resource limits. Finite scheduling is usually added by an APS layer that schedules the MRP output against real capacity.

When is infinite scheduling acceptable?

For rough, long-range planning where you only need approximate timing. For committing to customer dates and running the floor, finite scheduling is far safer.