INTELLIGENT IDENTIFICATION AND REVIVING OF MISSING JETS BASED ON CUSTOMER USAGE
A system includes a processor that executes computer executable components stored in a memory. The system includes a first component to receive data generated by at least one sensor. The system further includes a second component to generate an array that determines between activating one of a purge routine and a diagnostic routine on a printhead based on the array. The array is a function of the data. The system further includes a control component operable to selectively activate the purge routine on the printhead based on the determination.
1 . A system operative on a printhead, comprising:
an ink-jet recording device including the printhead that ejects ink droplets from a plurality of nozzles;
a first sensor to detect data relating to the nozzles on the printhead; and
a processor to execute computer executable components stored in a memory, comprising:
a machine learning component to employ artificial intelligence (AI) to learn the data generated by the sensor for determining between selectively activating one of a purge routine and not activating the purge routine.
2 . The system of claim 1 , wherein the data identifies nonoperational nozzles on the printhead.
3 . The system of claim 2 , wherein the machine learning component employs the data to map an array of the non-operational nozzles relative to the printhead.
4 . The system of claim 3 , wherein the machine learning component uses the array to forecast a defect in a future print job.
5 . The system of claim 4 , wherein the processor is further operative to:
weigh the forecasted defect against a predetermined tolerance threshold; and
activate one of the purge and a diagnostic routine in response to the tolerance not being met.
6 . The system of claim 1 further comprising a second sensor to measure defects in an image rendered or to be rendered by the system.
7 . A system for use with an associated printhead, comprising:
a non-transitory storage device having stored thereon instructions for:
acquiring data from a drop sensor monitoring nozzles on the associated printhead; and
using the data, generating a map representing the nozzles on the associated printhead;
employing artificial intelligence to forecast a potential defect in images to be rendered by the printhead; and
selectively initiating a maintenance to be performed on an associated printhead based on the forecasted defect, the associated printhead being in communication with at least one hardware processor configured to execute the instructions.