Quality control in manufacturing firms often remains a manually intensive task. By smartly using AI and more precisely computer vision, we can automate our inspection processes,
increasing the reliability of the quality control and thus improving our SLAs.
Computer vision in AI has now reached a high maturity level to truly and accurately support quality control helping you to increase end-product quality, to improve production speed and to grow customer satisfaction.
Imagine being a manufacturing firm that uses computer vision to monitor the quality of products on a conveyor belt... Read more
Imagine being a manufacturing firm that uses computer vision to monitor the quality of products on a conveyer belt. For the purpose of this demo an example setup is built. You’ll need two things to get started: a camera that will be used as a monitoring device and a banana that will be used as a test object to perform the quality control on.
To analyze and predict the ripeness of the banana we used the open source programming language Python. To create our web page, Flask is leveraged as this allows us to easily pass along information from the web page to our python scripts and vice versa... Read more
First, we created a labelled dataset using around 20 images of every possible prediction. Next, for the analytics part a pre-defined, deep learning model structure from the Keras library is adopted which runs on top of TensorFlow... Read more