In multi-cavity molds, consistency depends on every cavity experiencing the same conditions. When one cavity fills faster than another, it sees higher shear and pressure, while slower cavities may lag behind and underpack.
A Cavity Balance Study checks whether flow is truly uniform across the mold. This is where variation either gets eliminated early or compounds into bigger issues later in the process.
This step verifies that flow and pressure are evenly distributed across all cavities at the injection speed defined during the rheology study.
When balance is achieved, each cavity follows the same fill pattern and produces parts with consistent weight and structure. If not, variation begins to stack through packing, cooling, and shrinkage.
The study evaluates how uniformly each cavity fills and identifies any imbalance caused by runner layout, gate geometry, or flow resistance.
Part weight variation and pressure consistency are measured to confirm whether each cavity is performing under the same conditions. A well-balanced mold typically stays within 5% variation in part weight, with closely aligned pressure behavior across cavities.
This study uses the injection speed selected from the rheology curve’s stable region. Keeping shear conditions consistent removes material behavior as a variable.
If imbalance appears here, it points directly to the tool itself rather than the machine or resin. That clarity makes root cause identification much more direct.
The process begins by setting the machine to the established baseline conditions, including the optimized injection velocity.
The mold is then filled to about 95–98% using short shots. These parts reveal how the flow front progresses through each cavity.
Each part is labeled by cavity and weighed using a high-precision scale. Multiple runs are repeated to confirm consistency, and the results are plotted to visualize variation across the mold.
When available, cavity pressure sensors or thermal imaging add another layer of confirmation by showing how each cavity behaves internally during fill.
Part weight is the primary indicator of balance. Consistent weights across cavities signal uniform fill, while variation highlights differences in flow resistance.
Fill time and injection pressure are also monitored to ensure they remain consistent. When cavity pressure data is available, overlays should align closely if the system is balanced.
Even small deviations can point to specific issues. For example, consistently lighter cavities often indicate higher restriction in the runner or gate leading to those locations.
When all cavities show similar weights and fill patterns, the process is ready to move forward.
If only a few cavities are lighter, the issue is usually localized, often tied to gate sizing or venting. A gradual pattern of imbalance across cavities suggests a runner design issue.
Random variation tends to trace back to material or temperature inconsistency rather than the mold itself.
Each finding directs a specific adjustment, and the study is repeated after corrections to confirm the improvement.
Short shots provide a clear visual map of how the mold fills.
Uniform flow fronts across cavities indicate balanced conditions. Cavities that fill early may show higher gloss or even burn marks, while late-filling cavities often appear dull or incomplete.
Photographs of these patterns create a record that ties visual behavior directly to measured data.
When pressure sensors are installed, they offer a precise view of what’s happening inside each cavity.
Pressure curves from all cavities should closely match. Differences in shape or timing reveal variations in resistance or flow path.
Aligned pressure profiles translate directly to balanced fill, packing, and final part quality.
The study produces a detailed report with part weight data, visual documentation of short shots, and pressure overlays when available. It also includes recommended adjustments if imbalance is found.
Once balance is confirmed, the process moves forward with confidence. Downstream variables like packing and cooling become far more predictable, which tightens control over dimensional outcomes.
Balance is established before optimization. When every cavity follows the same path, the rest of the process becomes easier to control and scale.
That consistency carries through validation and into production, where stable conditions lead to repeatable results across every cycle.