Defect Detection Techniques for Airbag Production Sewing Stages
This work addresses quality control in airbag manufacturing, which is critical for safety, but it is incremental as it applies existing image processing methods to a specific domain.
The paper tackles the problem of detecting sewing defects in airbag production to ensure passenger safety, presenting a framework that automatically identifies and marks defects like skipped stitches and superimposed seams using image processing, with results indicating detection of specific defect types for lockstitch and chainstitch.
Airbags are subject to strict quality control in order to ensure passengers safety. The quality of fabric and sewing thread influence the final product and therefore, sewing defects must be early and accurately detected, in order to remove the item from production. Airbag seams assembly can take various forms, using linear and circle primitives, with threads of different colors and length densities, creating lockstitch or double threads chainstitch. The paper presents a framework for the automatic detection of defects occurring during the airbag sewing stage. Types of defects as skipped stitch, missed stitch or superimposed seam for lockstitch and two threads chainstitch are detected and marked. Using image processing methods, the proposed framework follows the seams path and determines if a color pattern of the considered stitches is valid.