Abstract:
Techniques are described for maintaining synchronization of inspection data when a web roll is converted into intermediate smaller rolls prior to cutting the web into individual parts. A system comprises a database that stores anomaly data acquired from a manufactured web. The anomaly data specifies positions anomalies within a manufactured web relative to a set of fiducial marks on the manufactured web. A conversion processing line comprises a fiducial mark reader to output position information for the set of fiducial marks on the manufactured web, a slitter that cuts the manufactured web into slit rolls, and a fiducial mark printer to print a set of fiducial marks on each slit roll. A position monitoring system maintains spatial synchronization of the anomaly data by computing an updated position for the anomalies relative to the set of fiducial marks printed on the slit rolls.
Abstract:
This disclosure describes techniques for automatically controlling the operation of a slitter (40) to convert a web (20) of material into smaller slit rolls (64, 66, 68). A slitter director (60) may automatically control the operation of a slitter (40) for defect removal, web splicing, and/or slit roll rejection based on continually registering previously-generated anomaly data (62) with physical locations of the web (20).
Abstract:
Techniques are described for maintaining synchronization of inspection data when a web roll is converted into intermediate smaller rolls prior to cutting the web into individual parts. A system comprises a database that stores anomaly data acquired from a manufactured web. The anomaly data specifies positions anomalies within a manufactured web relative to a set of fiducial marks on the manufactured web. A conversion processing line comprises a fiducial mark reader to output position information for the set of fiducial marks on the manufactured web, a slitter that cuts the manufactured web into slit rolls, and a fiducial mark printer to print a set of fiducial marks on each slit roll. A position monitoring system maintains spatial synchronization of the anomaly data by computing an updated position for the anomalies relative to the set of fiducial marks printed on the slit rolls.
Abstract:
An example method for selecting product images for training a machine-learning model includes obtaining product images to include in an image population; receiving an indication of an image selection strategy for determining if a product image is to be included in a set of images of interest; determining image transforms based on configuration data for the indicated image selection strategy, wherein the image transforms perform image manipulation operations to obtain transformed image data for each of the product images in the image population; selecting a subset of images from the image population for inclusion in the set of images of interest based on the indicated image selection strategy and the transformed image data; determining one or more descriptive labels and applying the one or more descriptive labels to the respective sets of images; and training an inspection model for a product inspection system based on the labeled images.