Performing Post-Production Defect Detection of Pet Preforms With Image Processing Technology

With the speed and cost advantage provided by the developing technology, image processing technology has started to become widespread especially in the production sector. In this study, the defects in pet preform production were examined and in this direction, it was aimed to eliminate the errors by using an image processing system. Preforms found to be faulty by image processing are distinguished with great precision. For this purpose, the design and manufacture of the mechanical test station was made. In this test device, preforms can be adjusted according to product dimensions, products that pass the test can be moved to the stock box. In this study, features including statistical, textural and morphological features of the patterns obtained after segmentation of the separated product image were determined. It has been proven that the preforms show classification success with 97% accuracy in terms of classification precision. Based on Tables 1 and 2, an enterprise producing 30 million units monthly experienced a loss of 8.5 million units due to adverse conditions. This resulted in significant inefficiencies in energy use, labor, raw materials, and machinery. To address these issues, an image processing test device was developed and implemented in 2021.