Deep learning is the foundation of modern defect removal in french fries production. S-Blade detects defects and cuts them out, and it gets smarter as it processes more product. PIP Innovations is the only supplier applying deep learning to defect removal in this way.
Adapting learning system
Traditional optical sorters rely on fixed rules: anything outside a defined range is rejected as a whole. Deep learning works differently. It learns from large amounts of real production data and builds a model of what defects look like in context. This matters for french fry production, where defects vary with season, supplier and storage. A learning system adapts; a rule-based system does not.
Detection, classification, action
S-Blade's vision system runs continuously during production. Each fry is analysed for shape, surface and colour. The system classifies what it sees and S-Blade cuts the defect out at the precise location, at industrial speed, with a throughput up to 20 metric tons per hour.
Always improving
Deep learning lets PIP keep improving how S-Blade performs. When a customer flags a defect that is being missed or cut incorrectly, PIP looks into it and improves the model. Improvements will be shared across the installed base, during scheduled updates. Over time the system gets richer, broader and smarter, so when a plant runs a new french fry type, it is very likely that S-Blade is capable of processing it.
