What Is Capacity Requirements Planning (CRP)?

Capacity requirements planning, abbreviated CRP, is the planning step that checks whether the orders a material plan generates can physically be run given the capacity available at each work center. It compares required capacity against available capacity, period by period, the way a host checks whether the evening's reservations actually fit the tables on hand. Classic CRP flags the overloads; a finite-capacity engine like EDGEBIC goes a step further and resolves them while building the schedule.

This entry is part of the EDGEBIC by User Solutions glossary series; for the broader vocabulary of planning, see the manufacturing glossary.

How Capacity Requirements Planning Works

CRP is one phase in the classic material and capacity planning loop. Material requirements planning comes first and decides what to make and when, based on demand, on-hand stock, and lead times. That step assumes capacity is unlimited, which keeps the math simple but produces a plan that may not be runnable. CRP is the follow-up that tests the plan against the real world.

To do that, CRP translates each planned order into the hours it will consume at each work center in each time period. It sums those hours into required capacity and lines them up against available capacity, the working hours each work center can actually offer. Where required exceeds available, the period is overloaded, and CRP raises the flag.

The important limitation is that traditional CRP is a report, not a fix. It tells you a work center is at 130 percent next Tuesday, but it does not decide what to move. Resolving the overload is the planner's job: reschedule work into a lighter period, offload to an alternate machine, add a shift, or renegotiate a due date. CRP illuminates the problem and stops there.

A Concrete Example

Imagine a material plan puts three jobs through the same milling center next week, and each needs 20 hours of milling. Required capacity for the week is 60 hours. The mill offers two 8-hour shifts across five days at a planned utilization that yields 48 available hours for the week.

CRP lines those up: 60 required against 48 available, a load of 125 percent. It reports the overload. Under classic CRP, that is the end of the analysis. A planner then decides to push one job into the following week, or run Saturday overtime, or route one job to a second mill. Nothing about CRP itself resolves the 12-hour gap; it only makes the gap visible.

A finite scheduler handles the same situation differently. Instead of loading all 60 hours into a 48-hour week and reporting the overflow, it places jobs only up to the 48 available hours and pushes the remaining work into the next open window automatically. The plan it produces never shows 125 percent because it never books hours that do not exist.

How EDGEBIC Uses It

EDGEBIC is a finite-capacity scheduling engine, which is the capability that sits beyond CRP in the planning hierarchy. Where capacity requirements planning checks feasibility and reports overloads for a human to resolve, EDGEBIC builds a schedule that respects available capacity from the start. Each operation is placed on a work center and shift only if room exists under that day's available capacity; when a day is full, the operation moves to the next open window rather than overloading the machine.

You still get the visibility CRP provides. EDGEBIC's dashboards and load views compare available capacity against the demand pressing on each work center, so you can see where the shop is tight and where it has slack. The difference is that the schedule underneath those views is already capacity-feasible, so the load bars describe a runnable plan rather than an optimistic one waiting to be fixed. To understand the available-capacity side of the comparison, see what available capacity is, and for the finite versus infinite distinction at the heart of CRP, read finite versus infinite capacity scheduling.

Related Reading

CRP depends on knowing each work center's available capacity, and its whole purpose is to avoid the overloads described in production bottleneck identification. For the generic entry on the same topic, see the capacity requirements planning glossary.