While manufacturers across the globe embark on industry 4.0 journey, they do bear in mind that it is not going to be smooth sailing. The supply of defect-free, high-quality products is an important success factor for the long-term competitiveness of manufacturing companies. The increasing challenges of rising product variety and complexity add to high inspection volumes which turn inspection processes into manufacturing bottlenecks.

ICURO guarantees the delivery and transfer of zero-defect products and enable visual inspection with high accuracy akin to a trained eye. AI visual inspection is used in manufacturing for quality or defect assessment, in non-production environments, it can be used to determine whether the features indicative of a “target” are present and prevent potential negative impacts. Machine learning approach to 3D visual inspection involves image acquisition, preprocessing, feature extraction and classification. These help in complex cosmetic Inspection with segmentation and defect detection, part and feature location, counting, texture and material classification, assembly verification, deformed and variable feature location, challenging optical character recognition including distorted print.

ICURO team of manufacturing AI practitioners prepare the description of product and process quality, classification of quality, quality prediction, and parameter optimization. This results in significant reduction of scrap through early control interventions. Optimization of process parameter settings and product quality, stabilization of processes, Inspection plans dynamization, and formulation of model-based inspection processes. ICURO manufacturing AI platform provides a range of machine learning techniques to choose from and these include artificial neural networks, annotation-based computer vision, soft competitive learning fuzzy adaptive resonance theory, sparse restricted Boltzmann machine method, scale-invariant feature transform. The restricted Boltzmann machine is widely used in feature extraction, feature selection, and image classification for visual inspection.