Controlling the output of the production line has always been a complicated operation. We have developed technology that allows you to do this in an automated manner using Artificial Intelligence.
Controlling the output of the production line has always been a complicated operation. We have developed technology that allows you to do this in an automated manner using Artificial Intelligence.
Dedicating resources to quality control has a cost that affects the final product.
Depending on who is doing the testing and their state of alertness, there could be very different results.
Despite the many data collected, it is often almost impossible to use them to prevent or improve the line.
ADR-Flow is software that, once trained, uses artificial intelligence to autonomously recognize defects.
It quickly detects products that do not meet production standards and reports them in real time.
Show the results of your measurements on a dashboard and create customized data analyses.
The final result is a clear improvement in line quality, with fewer resources used.
Surface inspection of spark plugs, injectors, larger components or final assemblies.
Verification of correct wiring and correct assembly of motorcycles.
Checking the correct weldings of the components of a frame
Verification of the assembly accuracy of multiple components.
Each system has its own peculiarities, its own strong points and its own weak points, but at the end of the analysis you have to choose based on the data.
The data speaks clearly and says that an automatic defect recognition system, led by an artificial intelligence that uses neural networks, is absolutely the best solution (as well as the cheapest).
The functioning of an artificial intelligence is very interesting. It uses the most advanced technologies in the field of neural networks and machine learning.
As a first step, we need to define which defects the neural network will have to recognize and position the cameras in such a way that they can shoot at exactly the right moment.
The neural network will initially need to be trained. In practice it is very simple: you need to show ADR-Flow a certain number of images of the component and tell it if there is a defect within each image or if the photographed component is fine.
This operation is carried out by an expert operator together with the ADR-Flow team.
Once ADR-FLow has learned to detect defects, the neural network will be implanted directly inside the cameras installed on site. In this way there is no communication latency and defect recognition is immediate.
The neural network, as it works, improves its own ability to find errors, because it constantly learns from the new images it processes.
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The system uses machine learning algorithms to analyze images and detect defects. Training is performed on a dataset that contains images of defects and images of objects that show none, resulting in immediate and precise recognition of defective objects.
If a defect can be identified visually ADR-Flow, appropriately trained, is able to detect it.
Currently the system only works on images.
If you think ADR FLOW can be integrated on your line or if you need additional information send a request to our team.
Once you send your request you will receive an email to respond to in order to get in touch with us.