How Many Cavities Should Your Mold Have?
Last updated: 2026-09-01 · Reading time: about 10 min
Cavity count is a production-arithmetic decision, not a status symbol: the right number of cavities is the smallest count that meets your annual volume at the machine’s real cycle time with realistic uptime and yield — because every cavity beyond that buys a lower piece price with a bigger tool, a longer build, and a machine that must run perfectly every shot. Size it from demand math at DFM, not from the largest budget the program can bear, and the piece price will take care of itself.
Key facts
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Runner system — The channel network that delivers melt from the machine nozzle to each cavity. Cold runner: solidifies between shots, produces runner waste. Hot runner: stays molten, eliminates runner waste but adds $15k–$40k to mold cost. See also related guide.
What does cavity count actually change?
Cavitation
The number of identical part impressions in one tool. Four cavities produce four parts per shot; the cavitation number sits at the center of the trade between tooling investment and piece price.
The levers move in opposite directions, and seeing both clearly is the whole decision. Add cavities and the piece price falls — the machine’s hourly cost spreads over more parts per shot, and material per shot barely changes per part. But the tool grows: more steel, more complex balancing, a longer build, a larger press, a higher service burden, and a costlier failure mode when something drifts.
A single-cavity tool forgives a lot and probes a market at modest cost; a sixteen-cavity tool is a factory commitment that must run on a stable process to be worth its steel. Neither end is the right answer. The right answer is the count that meets the demand — with room for real uptime and real yield — and stops there, because cavities beyond demand are steel that waits.
Programs that size cavitation from demand at DFM rarely regret the math; programs that size it from a piece-price target alone often meet the regret at the first capacity review.
How do you size the cavity count from demand?
The cavity count inherits every optimism error you make here.
The effective output per cavity is well below the theoretical one.
Where does the piece-price argument go wrong?
The quoted piece price is real, and it does fall as cavitation rises — the arithmetic behind that is sound.
The trap is reading the piece price as the whole story. A high-cavitation tool spreads its cost across parts only while it runs, and everything that threatens runtime scales with cavity count: balancing (the far cavity fills differently from the near one), maintenance (eight ejector systems instead of one), and sensitivity (a small process drift shows up as cavity-to-cavity variation the inspector must sort).
The comparison that decides well is total cost of ownership: tooling plus running cost plus service cost, divided by good parts actually shipped. On that arithmetic the extra cavities have to earn their steel — and they do, when the volume is real. When the volume is thin, the same arithmetic quietly favors the smaller tool that runs more often than it waits.
The worst outcome is not a wrong quote; it is a correct quote for a program that no longer exists. That sentence is why the demand math comes first and the quote comes second — in that order, every time, before the deposit and after it too.
| Dimension | Low cavitation | High cavitation |
|---|---|---|
| Piece price | Highest per part. | Lowest per part — while the tool runs. |
| Tooling investment | Lowest; fastest to build and revise. | Highest; longest build, costliest changes. |
| Balance and validation | Simple; one cavity to tune. | Demanding; every cavity must match, every shot. |
| Service and spare parts | Light. | Scales with count; downtime hits volume hardest. |
| Risk profile | Volume-limited, not steel-limited. | Steel-limited if demand thins or process drifts. |
What breaks first in high-cavity tools?
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When does each end of the spectrum actually win?
The two ends are not better or worse; they are answers to different programs. The single-cavity end wins when volume is modest, the market is still being tested, the part is large, or the program expects design changes — a small tool bends, a big tool resists. It is also the honest answer when the forecast has more hope than history behind it.
The high-cavitation end wins when volume is proven and stable, the part is small, the process has been validated, and the calendar needs parts faster than one cavity can freeze them — medical disposables, closures, small precision components at scale. Between those poles sits the silent majority of programs, and their answer usually lands in the middle band the demand math produces.
The pattern across every program we have sized is consistent: the cavity count that survives a year of production is the one chosen from the forecast that was true, not the one that was hoped. Where those two forecasts differ, the smaller tool is the apology that costs less.
“Cavity count is where programs meet their own forecasts face to face. We would rather size the tool to the demand we can defend than to the piece price we cannot fill.”
— Arthur, Tooling Engineer at aCatMould
Frequently asked questions
Can I start with fewer cavities and add later?
Sometimes — some tool architectures accept added cavities, and starting smaller matches a cautious demand case. But “addable” must be designed in from the start: plate space, runner layout and cooling capacity do not appear by themselves. Decide the path at DFM, not at the capacity crisis.
Does high cavitation always need a bigger machine?
Usually yes — more cavities need more projected area, more clamp force and more shot capacity. The machine step-up is part of the piece-price arithmetic; a cavitation plan that quietly requires a new press has not finished its math.
How does a family mold fit this picture?
A family tool trades the same balance in a different currency: different parts share one tool, so each part’s volume rides the shot of the whole family. It wins when the parts run together in stable ratios — the family-mold decision is the cavitation decision’s sibling.
Why did our eight-cavity tool never run at the quoted piece price?
Because the quote assumed the theoretical cycle. Uptime losses, balancing drift and sorting add back cost that the piece-price line cannot show. The honest number is cost per good part over the year — which is why the demand math runs before the quote, not after it.
Is there a typical cavity count for a given volume?
No universal table survives contact with a real cycle time. Volume alone cannot set cavitation — cycle time, part size and machine availability move the answer by factors. The five-step demand math in this article is the reusable method; the output is a range, and the neighbors around it get priced.
How much does cycle-time error move the cavity answer?
Far more than most programs expect: because output per cavity divides by cycle time, a twenty percent error in the cycle estimate is a twenty percent error in the cavity count. That is why the estimate comes from wall thickness and cooling geometry at DFM — and why the answer is a band, with the neighbors priced instead of a single number defended.
Should resin selection come before or after cavitation?
Before, at least in outline: the grade’s flow and cooling behavior shape the cycle-time estimate the cavity math runs on. A thin-flowing high-MFI grade and a stiff engineering resin can double the answer for the same part. Fix the resin family first, then size the cavities — and keep both decisions in the same DFM record.
Does cavitation affect the tolerances the tool can hold?
Indirectly, yes. More cavities mean more places where balance can drift, and cavity-to-cavity variation becomes a tolerance consumer of its own — the drawing may hold, but the process must be tighter to hold it eight or sixteen times per shot. Tight-tolerance parts therefore push the math toward lower counts or tighter process control, and the decision belongs in the same conversation as the tolerance stack.
Who owns the cavitation decision?
Whoever owns the forecast and the budget — usually shared between the customer’s program management and the tooling engineer. The tooling side brings cycle time and balance reality; the program side brings volume honesty. Decided together at DFM, the count holds for the life of the program.
Key takeaways
- Cavitation is demand math, not aspiration: annual volume, real cycle time, uptime and yield give a viable band — and the smallest count inside it usually wins.
- Piece price falls as cavities rise, but total cost of ownership is the deciding arithmetic — service, balance and downtime scale with count.
- High-cavitation tools earn their steel only on stable volume and a stable process; every added cavity multiplies balance and maintenance obligations.
- Expandability is a design decision made at DFM — plate space, runners and cooling do not retrofit themselves.
- Price the neighbors: one cavity below and above the band turns the cavitation debate into a comparison of records.
If your program is choosing a cavity count — or arguing about one — send us the 3D model, the annual volume and the machine constraints before the deposit. You will get the demand math on paper with its assumptions named, the neighbor comparisons priced, and the tooling plan that matches the forecast you can defend — and the neighbors priced beside it, so the debate ends at the table — from a named tooling engineer, before any steel is ordered.
Sources
ISO 20457:2018 — Plastics moulded parts: Tolerances and acceptance conditions, International Organization for Standardization
Plastics Industry Association — industry resources on plastics processing practice
LKM — mold base supplier, reference for multi-cavity tool architecture
HASCO — moldmaking components, reference for multi-cavity tool hardware
Sources: Plastics Technology · Plastics Technology Online · Prospector — Resin Datasheets · MatWeb — Material Property Database