AI-Powered Quality Control
Your Path to Zero Defects
Quality control in manufacturing isn’t just about catching defects – it’s about keeping production smooth, customers happy, reducing scrap and lowering rework costs. Traditional QC methods work, but they can be slow, expensive and inconsistent. This is where AI-driven quality control shines: it’s fast, reliable, works 24/7 and doesn’t just make OK/NOK decisions but can categorize defects and support your cause analysis.
Traditional QC methods are struggling to keep up
❌ Human inspectors get tired and make inconsistent decisions across shifts and sites
❌ Sampling can miss defects in the batches you didn’t check.
❌ Machine vision systems are expensive and inflexible, requiring custom setups for every product change.
AI addresses all of these short-comings
✅ AI can inspect 100% of parts, 24/7, without breaks and consistently across lines and plants
✅ Learns over time to detect more and newer defect types
✅ Adapts quickly to new specs without code rewrites – just show it new examples
Quality inspection is a great use case to get started with AI. The Accella Quality Box(TM) can be implemented quickly with a fast ROI.
These are the steps needed to make AI-powered QC happen:
1️⃣ Image/Data Collection – cameras or sensors capture visual and process data of the product during production.
2️⃣ Model Training & Learning – the AI is trained to recognize defects and distinguish between acceptable variation and true anomalies.
3️⃣ Real-Time Inspection – every part is automatically checked during production; defects are flagged or automatically removed from the line.
4️⃣ Actionable Feedback – insights gained can be used for root cause analysis.
5️⃣ System Integration – AI connects with PLCs, MES/ERP systems and other legacy systems.
AI for detects defects with > 99.99% precision even in very high-throughput manufacturing, frees up personnel for more value-added tasks and overall reduces cost compared to manual inspection or traditional vision systems. Breakeven for the Accella Quality Box is generally achieved in months.
Use Cases
Automotive
Catch tiny defects on high-end rims/Class A surfaces.
Detect welding issues and flags false positives
CPG
Detect defects in high-speed battery manufacturing
Building Materials
Assign defect scores to wooden boards allowing binning for different uses.
Identify defective pavers in routine operation.
Detect palletizing mistakes to avoid mixed pallets
We’re here to help. Get in touch, and let’s discuss how AI can support quality control in your plant.
