Applying Ai To Process Manufacturing

By Author: Syntelli Solutions
Total Articles: 29
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Predictive Maintenance
One of the biggest concerns for any manufacturer is downtime, faulty machinery or unexpected issues. Reactive maintenance or solving the failure after it occurs costs a lot of money.

That’s why predictive maintenance is a smart and productive implementation of AI in manufacturing.

By using machine learning, the AI’s algorithm can leverage and analyze any current and previous data about the machine, and provide useful insights about unplanned failures.

This way, Artificial Intelligence anticipates the possible downtime and creates an opportunity for an engineer to come up with a better and smarter decision in the manufacturing process.

If you want to read more on this topic check out our blog post – Big Data Analytics for Manufacturing – Getting Started with Predictive Maintenance.

Quality Control
With the rise of technology, manufacturers feel the pressure to provide a product or machine with a skyrocketing quality. Applying AI in manufacturing is one way to maintain steady quality, especially in the production phase.

An effective way to do ...
... this is by using computer vision. Even though the production process can be managed by a team of qualified and experienced engineers, some product flaws are too small to be noticed by the human eye. If you set up cameras to your AI machine, the machine can catch even the smallest flaws or defects that may occur, take a picture, and send it to an expert to evaluate it.

Nowadays, this entire process can be automated without an expert’s evaluation, and the system can notice the flaw, and alert the engineer to fix it immediately.

Digital Twins
Another productive use of AI in manufacturing is by building an accurate virtual representation of a product or a machine. This process includes using a combination of data, different AI tools, and CAD to develop a virtual representation of a real-world data.

In simpler words, you are creating a digital twin of the physical characteristics of a real object.

All the data AI collects is connected to a cloud-based service which is afterward analyzed and processed. Developing digital twins is extremely important to design engineers.

AI enables them to monitor and analyze the performance of the object, the change in quality with the smallest design changes, and all this before the product is developed.

Not only that a lot of time and resources are saved by applying AI in manufacturing, but also the overall positive user experience increases since the number of critical mistakes are cut down entirely.

With Syntelli and our solution in AI and machine learning, your company can experience all these benefits too. Contact us to learn more.