Abstract: Computer-implemented methods and systems for feeding workpieces to a manufacturing line are provided. An example method involves operating at least one processor to: receive, from at least one image device proximal to a bowl feeder, a sequence of images of workpieces within the bowl feeder; determine a flow velocity of the workpieces within the bowl feeder; generate bowl feeder control settings by applying the flow velocity to a predictive model; and automatically apply the bowl feeder control settings to the bowl feeder. Computer-implemented methods and systems for predicting anomalies in a manufacturing line are also provided. An example method involves operating at least one processor to: receive a sequence of images of workpieces in the manufacturing line; extract feature data from the sequence of images; apply the feature data to a predictive model to detect anomalies in the manufacturing line; and generate annotations to locate the anomalies within the images.

Abstract: Computer-implemented methods and systems for feeding workpieces to a manufacturing line are provided. An example method involves operating at least one processor to: receive, from at least one image device proximal to a bowl feeder, a sequence of images of workpieces within the bowl feeder; determine a flow velocity of the workpieces within the bowl feeder; generate bowl feeder control settings by applying the flow velocity to a predictive model; and automatically apply the bowl feeder control settings to the bowl feeder. Computer-implemented methods and systems for predicting anomalies in a manufacturing line are also provided. An example method involves operating at least one processor to: receive a sequence of images of workpieces in the manufacturing line; extract feature data from the sequence of images; apply the feature data to a predictive model to detect anomalies in the manufacturing line; and generate annotations to locate the anomalies within the images.