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A new defect appears after your AVI system has been installed and validated. The instinct may be to retrain operators and retune the machine. But is that really the right first step?

False rejects can quickly become one of the biggest challenge in an Automated Visual Inspection project. Reducing them starts early: from selecting the right defect types to building variability into engineering runs and creating robust inspection recipes. Watch our AVI Q&A for practical insights.

Your test kit can't represent every possible production variation. So how do you build an AVI recipe that can cope with changes in product and container characteristics? Bram and Gunther explain why engineering runs are key to building robustness.

During our webinar on AVI implementation, we received more questions than we could answer during the live Q&A. So we sat down again to answer the 9 remaining questions, sharing practical insights from our AVI project experience.

Can Automated Visual Inspection distinguish a scratch from a crack? In our AVI Q&A, Bram and Gunther discuss the challenges of differentiating cosmetic defects and where leak testing fits into the picture.

An AVI machine can have hundreds, if not thousands, of parameters. The key is to identify which ones are critical to the quality outcome of your process.