Every Part Every Interval: Calculate a Realistic EPEI

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You want to make every part in a product family more often, in smaller batches. The production wheel looks tidy: A, then B, then C, and back to A. But the machine also has customer orders to finish, and each trip around the wheel brings another set of changeovers.

Every part every interval, or EPEI, helps you judge how frequently that family can repeat. The useful question is not just how short you would like the interval to be. It is whether the production time, setups and other work fit inside it.

Start with that capacity test. Then bring the recurring orders into the same schedule as the rest of production. SkyPlanner APS helps you do this without continually rebuilding separate machine queues to make your chosen rhythm fit.

What is every part every interval?

Every part every interval (EPEI) is the time between successive production runs of each part in a defined family at a defined process. An EPEI target of two working days means returning to each part in that family every two working days, producing the quantity needed for that replenishment rhythm.

You may also see “every product every interval” or EPEx, where x represents the chosen time interval. The important point is the repeat frequency, not which acronym a factory uses.

Define the boundary before giving the number. “Two days” is useful only when everyone knows which parts, which resource and which working calendar it describes. A family that repeats every two days at machining may still wait for a downstream process that runs weekly.

Also distinguish three things:

• The calculated lower bound: the shortest interval that passes a stated capacity calculation.
• The planning target: the rhythm you choose after considering practicality, demand and operating conditions.
• The achieved interval: how long actually passed between successive runs of each part.

A target on a production wheel is not evidence that the shop achieved it. Nor is EPEI the cycle time to make one piece, the takt time required by demand, or an order’s total production lead time.

How to calculate an EPEI capacity bound

For a simple family running sequentially on one resource, start with three inputs:

1. Available time per working day for this family. Deduct planned nonproduction time and the capacity committed to other work on the resource.

2. Daily run time required to meet demand. For each part, multiply average daily demand by processing time per piece, then add the results.

3. Setup time for one complete repeating sequence. Count every transition, including the change from the final part back to the first.

The difference between available time and daily run time is the capacity left for setups. The basic calculation is:

Minimum interval in working days = total setup time per repeating cycle ÷ daily capacity left for setups

In symbols, let A be available minutes per day, R be required run minutes per day and S be setup minutes per complete cycle:

T ≥ S ÷ (A − R)

The reasoning is straightforward. Over T working days, you need R × T minutes of processing and S minutes of setups. Those must fit into A × T available minutes. Rearranging that condition gives the interval above.

Use consistent units. If demand is pieces per day and processing time is seconds per piece, convert the resulting seconds to minutes before subtracting them from available minutes per day.

Leave deliberate room for variability

The basic lower bound consumes all the remaining capacity with changeovers. That is a fragile operating target if routine variation has nowhere to go.

You can reserve an explicit number of minutes per day for recovery or demand variation before calculating the interval. Subtract that reserve from A. Do not subtract the same allowance twice: breaks, known downtime, competing work and recovery time need clear, separate treatment.

If A − R is zero or negative, there is no positive setup budget. Lengthening the interval cannot solve a sustained run-time load that already uses all the available capacity. You need to change the load, the processing requirement or the capacity.

This is a capacity bound, not an economic optimum. It assumes a stable representative demand mix, one visit to each part per cycle and the stated sequence. Minimum batch quantities, fixed-time processes, material availability and other operations can require a longer interval.

EPEI calculation example: three parts on one machine

Imagine a machining cell with three recurring parts. After planned nonproduction time and other committed work, this family has 420 minutes per working day available.

Part	Demand per working day	Processing time per piece	Required run time per working day
A	100 pieces	2 minutes	200 minutes
B	60 pieces	1.5 minutes	90 minutes
C	40 pieces	1 minute	40 minutes
Total	200 pieces	—	330 minutes

The complete A–B–C–A sequence needs 90 minutes of changeovers. That total includes returning from C to A; otherwise the next cycle would begin with a setup that the calculation had forgotten.

Without a reserve, daily capacity left for setups is 420 − 330 = 90 minutes. The calculated minimum interval is therefore 90 ÷ 90 = one working day. Daily production would fit exactly, with no recovery room.

Now reserve 45 minutes per day. The setup budget becomes 420 − 45 − 330 = 45 minutes per day, giving:

EPEI capacity bound = 90 ÷ 45 = two working days

At that rhythm, one cycle produces 200 units of A, 120 of B and 80 of C. Processing takes 660 minutes; setups take another 90. The total is 750 minutes across two days with 840 minutes available, leaving the intended 90-minute reserve.

That makes two working days a credible candidate—not yet a proven timetable. Check that the sequence fits the actual shift windows, that the parts and tools are ready, and that subsequent operations can accept the work. Two working days can span more than two calendar days around a weekend.

What would make the interval shorter—or longer?

If the full cycle’s setups fall from 90 to 45 minutes while everything else stays the same, the reserve-aware bound becomes 45 ÷ 45 = one working day. Setup reduction has bought a more frequent return to every part, not merely a faster changeover.

The reverse is easy to overlook. If daily processing demand rises from 330 to 360 minutes, the same reserve leaves only 420 − 45 − 360 = 15 minutes per day for setups. With the original 90-minute setup cycle, the bound becomes six working days.

A modest increase in run load can sharply lengthen the interval when little setup capacity remains. Recheck EPEI when the mix or shared load changes, not only after a setup-improvement project.

Choose a rhythm that serves demand, not just the wheel

A shorter repeat interval lets you replenish a part sooner and cover a shorter gap between runs. That supports smaller replenishment lots and less inventory tied up between visits. But shortening the interval also repeats the setups more often.

For a stable demand rate, an initial quantity per visit is demand per working day multiplied by the chosen interval. In the example, part A needs 100 × 2 = 200 pieces per visit. That is the cycle’s demand quantity, not a complete safety-stock or replenishment policy. Existing stock, shortages, minimum lots and demand changes still matter.

Avoid three common traps when choosing the rhythm.

Do not confuse stock coverage with production capability. Stock divided by daily demand tells you how long that stock could cover consumption. It does not tell you whether the resource can process and change over the whole family often enough to replenish it.

Do not make every slow mover on every circuit. A repeatable group of regular runners can justify a short interval while intermittent items run less frequently against genuine need. Name that boundary explicitly. If an item runs only every third circuit, it does not share the runners’ one-circuit EPEI.

Do not optimize setups in isolation. Where the direction of a change matters, use the actual transitions in the selected sequence. A setup matrix can help identify a more efficient order. Yet making one very long campaign to save changes can leave another part waiting too long for its next run.

Production leveling is the broader task of distributing volume and mix. EPEI gives you a specific question within it: how often can we return to these parts? Answer that question without forcing the entire product range into a rigid pattern.

Put the recurring work into the real production schedule

The capacity calculation is deliberately simple. Your factory’s schedule is not. Other orders use the same machines, operators work particular shifts, and a missing material can interrupt the next planned run.

This is where SkyPlanner APS becomes valuable. Rather than maintain an isolated wheel and manually fit everything else around it, schedule the selected replenishment orders together with the rest of your order book. You get a clearer view of whether the recurring work and customer commitments can coexist—and less daily work reconciling their machine queues.

Model the time that the family really needs

SkyPlanner supports processing times per piece, output rates and fixed durations at process-step level, together with setting times and eligible workstations. Use the appropriate method for each operation rather than treating every batch as a simple pieces-times-cycle-time calculation.

Bring the selected quantities, routes and due dates into the schedule with the relevant shifts and resource capacity. Arcturus, SkyPlanner’s scheduling engine, calculates placement using configured priorities and operation dependencies. With material-aware scheduling enabled, material availability also affects the calculation. The Gantt timeline makes the resulting work sequence visible.

You retain the planning decision: which family should repeat, what target makes sense and how exceptions should be prioritized. If an order should not be made early, its start eligibility date can prevent scheduling before that date. It is an earliest-start restriction, not a guarantee of the next return.

Save setup time without losing sight of the next required run

SkyPlanner can group jobs by shared properties such as tooling, material or color. Workstation similarity rules take the chosen property and setup time for differing jobs into account, with the grouping’s importance controlled through Dynamic Priorities.

That helps recover time otherwise lost to avoidable changes. But setup savings and a short repeat interval are not always the same goal. Keeping similar jobs together for too long may delay the next run of another part. Set the grouping weight alongside delivery priorities, then review the resulting sequence against your chosen interval.

At KJH-Comp, weekly ERP loading and spreadsheets once left day-level machine assignment to supervisors. With SkyPlanner, finite scheduling and machine assignment became automatic. In bending, the company describes grouping jobs with the same tooling and material thickness, shortening setups and reducing idle time.

For a recurring family, those same gains matter: fewer avoidable setups and less time rebuilding the daily plan. The next step is checking your chosen return interval against the whole workload.

Check the return interval as production changes

Once you adopt a target, record successive run times consistently for each part at the agreed process. Use the same event—such as run start—and the same working calendar. Review the gaps, especially missed returns; an average alone can hide a part that repeatedly waits too long.

When a return slips, identify why before changing the target. Was the original setup budget too optimistic? Did another order take the capacity? Was the material unavailable, or did a downstream restriction prevent the planned flow?

Update the relevant capacity, material or priority information and recalculate the schedule in SkyPlanner. Then review the next replenishment runs and affected customer work together. The point is to correct the underlying conflict, not keep yesterday’s wheel looking intact while queues diverge from it.

Test one recurring family with SkyPlanner

A useful EPEI connects three decisions: the interval your capacity can support, the replenishment rhythm your demand needs and the schedule that must deliver both alongside other orders.

SkyPlanner gives you the scheduling foundation for that third decision. It integrates with any ERP or MES through its open REST API, so you can keep your existing business system and give recurring production a place in the same finite schedule as the rest of the shop.

Book a SkyPlanner demo with one product family, its processing and changeover times, the shift calendar and other orders sharing the resource. Use that discussion to see how your proposed rhythm would fit the real workload. If you prefer to explore the environment first, try SkyPlanner with demo data or the Assistant’s AI-assisted Getting Started flow.