This studio, I collaborated with fellow NuVu Students, Milin, and Sadie, to create a machine for processing plastic film in recycling facilities. Most recycling facilities are not able to automatically process plastic bags, and resort to using humans to filter this waste from the conveyor belt. Additionally, the plastic film is often missed, and, in turn adulterates the machinery. We began tackling this problem by focusing on the computer vision necessary for detecting plastic bags on a conveyor belt and decided on using the deep learning system, YOLOv8, for training our model. Creating a good computer vision algorithm, even with a system as good as YOLOv8, requires a large dataset of well labeled images, and a lot of compute. We used Roboflow to collect, label and organize a final data set including 9,100 labeled images(post augmentation) and Google Colab Pro which trained the model with 140 epochs(iterations). Originally, we intended for this project to assist the workers sorting plastic film, through a projector which would guide workers to where the plastic was being detected. We felt we could do better, so instead I designed(fusion 360) and we fabricated an arm to remove plastic bags on an also custom make conveyor belt. This arm is equipped with three degrees of motion(if counting the claw), featuring a robust and uniquely designed claw for grabbing plastic film, without getting damaged by other oncoming and not as forgiving materials. This arm is controlled by an Arduino controlled by a python program running on my laptop. This laptop runs our computer vision model using frames from a webcam mounted above the conveyor belt.