This paper introduces a method for designing and manufacturing a model capable of detecting product defects caused by missing items and automatically supplementing them with a feeder. The proposed model is composed of two primary components: a missing-product detection unit and an automatic feeder. The main processing system utilizes data from a video camera, employing color processing followed by edge detection and shape classification to identify the locations of missing items on the tray. Based on the identified missing locations, the feeder supplements the empty cells to complete the trays. The prototype was fabricated and tested with cylindrical products in size of Ø25 × 10 mm in height. The camera was positioned at a height of 30 cm above the conveyor belt, which run at a linear speed of 60 mm/s, while the feeder operated at a speed of 11 mm/s. Experimental results showed that the model could detect missing cells with an accuracy of 99.2%. Additionally, it accurately determined the coordinates of missing cells with 100% precision and successfully supplemented the missing items as required. This study is particularly suitable for tray applications where all cells contain identical products. Future work could integrate an object recognition model to detect types of products in cells.