Current disclosure will present a method to improve the efficiency and the effectiveness of Drop Detection (DD) functionality and related servicing. This improvement is based on a predictive approach using as reference the printmode nozzle usage strategy. It is very common, in large format printers (middle and low volume) for the printheads (PHs) to have a fixed position in the carriage. Thus, depending on the printmode selected, the printer uses just a small part of the available nozzles of the printhead(s). It is also usual that before printing a plot, the printer performs a drop detection to record which nozzles are not firing and based on that program an error hiding strategy or a cleaning servicing. There are some printmodes that only use a 10% of the available nozzles but normally the machine performs a detection to the entire pen and takes decision based on that information. This means that even if we need just the 10% of the nozzles, we are taking into account if a not used nozzle is firing and even triggering an additional cleaning servicing in case that the number of nozzles is higher than the threshold, even if those nozzles will not be used never. In addition, there is not information used about these nozzles out are located so, even if they are less than the threshold they could be clustered in a used zone, compromising the final IQ of the plot. For fixing this we propose a different solution where we detect the entire performance of the pen, but we just use the information about the nozzles used in the next plot printmode to trigger (or not) a recovery routine, being more specific, increasing IQ, saving time and ink from recoveries. This approach leads to many advantages, first of all, the improvement in IQ performance due to the specific recovery of the area of the PHs used, avoiding unnecessary recoveries over the rest of the nozzles and at the same time giving the opportunity of removing clusters of nozzles out that will compromise the final results.
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INC, HP, "SELECTIVE PRINTHEADS SERVICING BASED ON PRINTMODE AND DROP DETECTION ANALYSIS", Technical Disclosure Commons, (December 13, 2022)