The automation trend is being accelerated by daily advances in Artificial Intelligence and Deep Learning. In the manufacturing industry, the automation of tasks by machines has become one of the biggest technological revolutions in this field.
Object Detection is the component of Computer Vision that deals with locating a specific objective from images, which makes up a key part of manufacturing for automation.
Let´s start by understanding Computer Vision. It literally allows computers to ´see´ as humans do through the acquisition, processing, and analysis of digital images and videos. Many basic forms of this technology already exist that are able to use open and pre-source training to detect generic objects like trees. But Object Detection requires a trained algorithm to identify specific details within an image, such as facial expressions.
There is a plethora of uses for Object Detection, from quality management to sorting and packaging. We will break these use cases down for each function to see how this technology can be applied to newer manufacturing practices.
The quality control process remains a task that depends on human visual understanding and quick adaptation. The AI can automatically distinguish faulty products at speed and allow time for corrective action to be taken, which is useful in dynamic environments where things are always changing, and precious time can be saved and dedicated to other tasks.
Tracking items in real time can prove to be an incredibly complex task for an organisation, and capital and time can be wasted if this is not carried out properly. The automation of this task by AI diminishes the risk of human error, allowing inventory to be counted accurately and efficiently.
Manual sorting is a lengthy and costly process which is often accompanied by human error. Using AI powered Object Tracking, specific parameters can be selected and the corresponding statistics of the number of objects displayed. Not only does it make the assembly line more flexible, but it also reduces the number of abnormalities during categorisation.
In the manufacturing industry, almost all assembly lines are fully automated. Whilst the use of robotics in this field is extremely useful, the use of AI technology to correctly locate and differentiate products to correlate with their movement will open doors to more efficient labour and higher output. AI powered objective detection allows for this possibility to become a reality.
Custom Object Detection
Custom object detection allows for niche manufacturing set-ups to be catered to. Objects take a variety of forms and usually algorithms need thousands of training examples to learn to differentiate the products. With this technology programmers are able to use less than 50 of these examples to train the algorithm to perform with accuracy and efficiency.
Overall, with the advances in Visual Object Detection, we are able to create machines that are capable of identify objects from videos and images more accurately and more detailed than ever. The benefit to the manufacturing industry is huge, with automated tasks becoming more streamlined, and human error becoming more obsolete. By furthering the understanding ad therefore ability to react to faulty products, machines will be able to navigate through the environment for themselves, rather than requiring a constant scripted input.