EV Battery Visual Inspection
Catch Assembly Errors Before Rework

Automate visual inspection for surface defects, missing/reversed components, connector seating and traceable part markings. 

Start with a station that still needs manual checks. Set checks by product recipe, highlight the affected area and link inspection records to product IDs.

Cells

Surface & ID Checks

Modules

Parts & Orientation

PACK

Connectors & Records

What Slows Battery Inspection Down

False alarms on conforming units, late‑discovered assembly faults and repeated configuration work create extra overhead on your production line.

/ 01

Reflections Trigger Extra Review

Glare, minor scratches and normal production marks are easily misclassified as defects. Acceptable surface variations trigger false alarms, requiring operators to re-inspect good units.

/ 02

Assembly Errors Are Found Too Late

Missing insulation, reversed components or improperly seated connectors may require full disassembly for repair. Critical checks must run while target components remain accessible.

/ 03

Each Variant Adds Setup Work

New cell formats and module layouts change where to inspect and what to reject. Updating regions, tuning rules and validating results consumes valuable engineering capacity.

/ 04

Manual Review Becomes a Bottleneck

Operators locate flagged regions, make defect‑acceptance judgements and log outcomes. Fatigue and inconsistent judgment can lead to missed defects.

Reduce False Calls. Simplify Setup. Expand Inspection.

Distinguish normal surface variation, adapt checks to new products and add inspection tasks to compatible equipment.

Problem: Reflections/surface variation trigger false alarms, adding extra manual review.

↓

AI Anomaly Detection

Use suitable lighting and samples from normal production to define acceptable variation. Validate target defects against agreed reject criteria.

<2%

False positive rate

Problem: New variants require fresh setup, while collecting and labeling defect samples delays deployment.

↓

Few-Shot Model Adaptation

Adapt pre-trained models to target checks with a small set of labeled examples. Reduce sample collection and annotation work when introducing new products.

5-20 

Training images

Problem:Adding inspection tasks can mean extra hardware, wiring and integration work at an existing station.

↓

Multi-Task Visual Inspection

Configure presence, orientation, position and marking checks in Apexera Vision. Combine checks in one workflow and reuse compatible devices to limit hardware changes.

4+

Configurable check types

Key Visual Inspection Tasks for Battery Production

Cover critical assembly and quality checks before the next process step.

Add Checks to the Equipment You Have

Choose the integration route after checking image quality, camera interfaces, trigger timing and line-control requirements.

Existing Production Lines

Apexera Box

Add inspection software to a compatible imaging station. Connect camera input and trigger signals, then return inspection results to the line controller.

✓ Assess existing cameras and lighting for reuse

✓ Connect inspection triggers and control signals

✓ Link results to MES / SPC as required

Equipment Builders

Apexera Card

Integrate image acquisition and AI inference into your own inspection equipment through a PCIe vision card, SDK and API.

✓ Combine acquisition and inference

✓ Integrate inspection with equipment controls

✓ Build with the SDK and API

From Sample Validation to Production Deployment

Which visual checks can be configured for an EV battery production line?

We support custom checks for cell surface quality, busbar/insulation presence, assembly orientation, harness, connector and sealant condition, plus readable ID marking. Feel free to check with us your needs.

Yes. If the existing cameras, lighting and field of view meet the inspection requirements, Apexera Box or Card can connect to the installed hardware without replacing the existing station equipment. Where imaging conditions are insufficient, we recommend suitable imaging changes.

Single-frame inspection takes 0.3–1.5 seconds, depending on the field of view and the number of features checked simultaneously. During solution planning, we assess the cameras and image-capture timing to configure the inspection around the production cycle.

A large collection of defective samples is not required to begin. Normally, 5-30 is applicable for model training. 

Yes, Inspection data and images are stored locally. Every result is tied to serial numbers, batches and station IDs for complete traceability.

Yes. Operators can manage and deploy new recipes through our production‑friendly interface, no dedicated AI team required.

Deployment can be phased. Define a checklist for each station and inspect only the specified parts or regions for appearance, assembly and markings.

For related products, recalling a validated inspection recipe typically allows changeover and tuning in 10–30 minutes. New structures or substantially different parts require recipe configuration and calibration; the required time is assessed separately.

Discuss your EV battery visual inspection requirements

Let’s discuss how our AI vision system fits your inspection stations, with minimal disruption to your existing production.

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