Can AI take medical device manufacturing to the next level?

Artificial intelligence could improve medical device manufacturing efficiency and reduce risk, but it’s still a work in progress.

[Image from Unsplash]

Artificial intelligence is driving the world and our habits. Some of the world’s most well-known companies are using AI: Apple in Siri, Tesla in self-driving cars, Amazon in Alexa and even Netflix.

Now companies like machine-learning and AI consulting company Wovenware are bringing AI to medical device manufacturing and other advanced industries to make the process more efficient while reducing risk.

Artificial intelligence is the capability of a machine to perform tasks that would normally be done by a human. Through machine learning, computers are taking in troves of data and learning mistakes while enhancing the jobs of engineers in the manufacturing process.

“Engineers have more time to do the important work,” said Carlos Meléndez, COO and co-founder of Wovenware (San Juan, Puerto Rico). “They don’t have to worry about things that they will not be able to fix.”

For example, a predictive algorithm can gather data about a medical device that was taken out of a production line because of a problem with the device. Using data and performance records, AI can determine the probability of that particular device being scrapped. If the algorithm shows a 99% chance that the device is going to be scrapped, it won’t be sent to the engineering department. Engineers then have more time to dedicate to more important processes, said Meléndez.

Get the full story on our sister site Medical Design & Outsourcing.

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