A weak seal, a skewed label, a missing or smudged date code — any one reaching the shelf can trigger a recall. Rule-based vision misjudged constantly under lighting and product variation, so the plant switched to AI-AOI for full inspection.
This food-packaging plant runs contract filling and packaging for multiple brands, with many SKUs and frequent changeovers. The three key quality items in packaging — seal integrity, label position and adhesion, and the presence and legibility of the production date code — previously relied on rule-based machine vision plus manual spot-checks. The rule-based approach was extremely sensitive to lighting fluctuation, packaging glare and slight product shift, producing frequent misjudgments. To cut nuisance stops, operators loosened the rules, which let real defects escape downstream, keeping complaints and returns high.
DaoAI replaced rule-based vision with an AI-AOI deep-learning solution, delivering three-in-one inline full inspection on the filling-and-packaging line. The model robustly recognizes seal wrinkles and weak seals, label lifting/bubbles/offset, and missing characters, ghosting or misplacement in the date code, with far greater tolerance to lighting and appearance variation than rule-based logic; rejects are ejected and logged in real time. Across many SKUs, APDT few-shot learning models new packaging formats quickly, so production starts right at changeover and commissioning time shrinks dramatically.
What AI-AOI Changes Versus Rule-Based
- Shifts from hard-coded thresholds to learned defect features, more robust to lighting, glare and shift
- Seal, label and code inspection merged into one station, no longer chaining multiple devices
- Few-shot adaptation for new SKUs cuts commissioning from days to hours
- Full-inspection logging makes every unit traceable, supporting brand-owner quality audits
Rule-based leans on hard-coded thresholds; AI-AOI learns the defect — the gap shows the moment the light shifts or the product moves.
After go-live, combined accuracy across the three checks exceeds 99.5%, delivering 100% inline inspection rather than sampling; end-customer complaints tied to seal/label/code issues fell about 61% year over year, return and recall risk dropped markedly, changeover commissioning time was cut substantially, and overall line OEE improved.