AI Use Case
Detect defects and quality issues during production using visual and other data
Detect defects and quality issues during production using visual and other data. This process will potentially be impacted by unexpected issues - e.g. a change in the quality of the lighting on a production line.
Operational Support - Issue triage,Operational Support - Issue / outlier ID,Revenue - Product optimisation
"Kewpie~Kewpie, a Japanese food manufacturing company, used deep machine vision that identified defective potato cubes on the production line with the same level as accuracy as humans",Netflix~Netflix increases quality control efficiency by using machine learning to predict which video assets are likely to fail,AngloGold Ashanti~Researchers investigate a cost-effective machine learning method for identifying gold from waste during ore sorting at an AngloGold Ashanti mine,University of Lincoln~Researchers from the University of Lincoln have built a learning computer system to early detect potentially harmful flaws in production and packaging of potatoes,Foxconn~Foxconn to identify and predict defects in manufacturing process with machine vision,Wikimedia~Wikimedia identifies and prioritises missing citations with an accuracy of up to 90% using a recurrent neural network
Machine Learning (ML),ML Task - Grouping - Anomaly Detection,Product - Data Capture - Camera,Product - Data Capture - Sensor IoT,ML Task - Prediction - Regression,ML Task - Prediction - Annotation,ML Task - Prediction - Binary Classification,ML Task - Prediction - Multi-class Classification