Multi-Camera Measurement Meets 0.2 mm on a Tray in 96 s
A battery tray is a classic large workpiece. Holes, surfaces and assembly features are distributed across it, and the inspection point count runs into the thousands. This cell uses several industrial cameras as a multi-camera 3D measurement system, capturing simultaneously, computing in parallel and measuring jointly. It completes thousands of points for dimensions and missing or wrong assembly within a 96 second cycle, with dual 100 percent coverage, 0.2 mm measurement accuracy and SPC process optimization, subject to site acceptance results.
Thousands of points, 0.2 mm and two full checks at once
The more points, the longer measurement and judgment take, and the harder accuracy is to hold. Keeping both quantity and precision inside one takt cannot be solved by stacking algorithms; the task has to be split at the acquisition end, so each camera is responsible for its own region.
Neither dimension checks nor assembly checks permit sampling. A single escape can cause a battery pack installation problem. Dual 100 percent sounds like an attitude, but in engineering it is a compute and takt bill: both judgments must run on the same data batch, and neither may slow the cycle.
Parallel computing is where the speed comes from
Several cameras shoot at once, each assigned a responsibility zone based on tray structure, computing dimensions and assembly state for its own points independently, then combining under a common coordinate system for joint measurement. Total time per unit approaches one zone rather than the sum of thousands of points. However many points there are, a sensible split means the cycle is set by the slowest zone.
Missing parts are a model comparison, not a dimension
For every assembly feature, a reference model records what should be fitted and where. 3D measurement captures the actual state, and comparison with the model exposes missing parts, wrong parts and wrong positions as recognizable differences. It shares the point cloud with dimensional judgment but uses a different criterion: one asks whether a geometric value is within tolerance, the other whether the required object is present.
SPC turns measurement into process data
Measurement data is aggregated by point and by time, producing control charts and trend warnings. Dimensional drift is gradual, and waiting until it becomes an out-of-tolerance result is already late. SPC identifies process fluctuation at the trend stage and gives parameter adjustment a quantitative basis.
How 96 seconds aligns with the line
The measuring fixture works with the line's transport positioning so the tray arrives in the same attitude every time, reducing repeat positioning error. The acquisition window aligns with the conveyor cycle: passing trays are released, anomalous ones intercepted, and inspection does not become a separate station that slows the line.
Long-term accuracy needs an owner
0.2 mm does not hold forever because it was calibrated once. The system runs periodic verification with a reference piece to prevent calibration drift from eroding accuracy. Among thousands of points, an anomaly at any single point can disturb the overall verdict, so zone parallelism and process monitoring have to be in place together.
The questions asked most often at selection
How are thousands of points measured in one pass?
Several cameras capture simultaneously and compute in parallel, each owning part of the points and measuring jointly. Judgment time approaches one zone, so all points fit within 96 seconds and both dimensions and assembly reach 100 percent.
Is 0.2 mm accurate enough?
It depends on the judgment. For mounting holes, surfaces and assembly state, 0.2 mm matches the tolerance system. Micron-level form tolerance is a CMM task.
What does SPC actually do here?
It turns measurement into process data: it reveals drift, warns early and guides parameter changes, moving from after-the-fact blocking to prevention. The more data accumulated, the more reliable the trend.
Does dual 100 percent slow the takt?
Both judgments share one point cloud and one calibration, differing only in algorithm branch. The load is compute and zoning, not repeat acquisition; final figures are subject to site acceptance results.