  This report examines machine learning algorithms for detecting short forming
and weaving in plastic parts produced by injection moulding. Transfer learning
was implemented by using pretrained models and finetuning them on our dataset
of 494 samples of 150 by 150 pixels images. The models tested were Xception,
InceptionV3 and Resnet-50. Xception showed the highest overall accuracy
(86.66%), followed by InceptionV3 (82.47%) and Resnet-50 (80.41%). Short
forming was the easiest fault to identify, with the highest F1 score for each
model.
