Abstract: A system for aligning print-heads in a printing-press, which includes a print-head array which includes a plurality of print-head-rows. Each print-head-row includes a plurality of print-heads and prints print a color associated with therewith. Each print-head includes an array-of-nozzles, which includes a plurality of nozzle-lines. The system includes an imager and a processor. The imager includes at least one imaging-sensor. The imager is configured to acquire an image of a printed first-alignment-pattern and further configured to acquire an image of a printed second-alignment-pattern. The processor is configured to receive the image of the first-alignment-pattern and the image of the second-alignment-pattern and to determine alignment of reference print-heads in at least a reference-row of print-heads from the image of the first-alignment-pattern.

Abstract: A method and system for implementation of quality control includes a machine vision system for capturing images of instances of a product, and a computer system including computer memory containing machine-readable instructions executable by a processor. The processor evaluates the quality control images for a plurality of potential quality defects in the product and generates a defect alert associated with a captured image in which at least one potential quality defect is identified. Information about each defect alert is stored in a database log file in the computer memory. A neural network machine learning algorithm processes the database log file by, in a learning phase, receiving human-initiated input accepting or rejecting each defect alert and storing the human-initiated input in the log file, and, in an automated phase, automatically accepting or rejecting at least some defect alerts without performing the step of receiving human initiated input.