Feasibility Study on Image-based Faulty Nozzle Detection Method for Digital Textile Printing

Abstract

Digital textile printing (DTP) is a production method in which ink droplets are ejected from an inkjet head to print on a fabric. In recent years, the resolution of the DTP head has been increased, the nozzles have become smaller, fabric defects due to nozzle clogging have become easier to occur, and the production speed has also become faster, making it difficult for the human operator to confirm this in real time. In addition, real-time monitoring technology of defective nozzles is needed to break the existing time-based maintenance and implement condition-based maintenance.
In this study, we propose a method to identify defective nozzle position by acquiring an image of printed fabric in real time and verify method at prototype level and to examine feasibility. Based on the multi-pass type 1.8m-wide production equipment using a 1200 dpi head module, the
specifications and technical difficulties required for acquiring and analyzing the image are described in detail. It is hoped that these technologies will enable condition-based maintenance and further improve operational efficiency of manufacturing.