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How Artificial Intelligence Could Improve Medical Manufacturing Efficiency

Posted May 12, 2019

Artificial intelligence has applications for a diverse range of industries, such as the finance, education and transportation sectors. Some professionals employ the technology for workflow and business automation, while others are more familiar with its function as a virtual assistant — Siri or Alexa.

Image credit: Asemi via Wikipedia, CC BY-SA 3.0

With its impressive versatility, it’s only natural that artificial intelligence would see integration elsewhere. Beyond automation, and the convenience of virtual assistants, artificial intelligence has the potential to bring production to new heights of efficiency. Industry experts agree on this point.

An annual report from “The Manufacturer” found 92% of senior manufacturing executives believe “smart factory” digital technologies like AI will enable them to improve their productivity. The implications for manufacturing — and medical manufacturing in particular — are immense.

We’ll explore recent developments in the sector, providing a comprehensive picture of the value of artificial intelligence as we move into the next decade. In an increasingly digital world, it will serve an integral purpose for all areas of an organization. Medtronic is evidence of that fact.

Medtronic Case Study

Medtronic is actively developing AI applications throughout its manufacturing and supply-chain operations. Todd Morley, director of data science at the company, said their areas of focus include supply-chain optimization, yield optimization, predictive maintenance and supplier and production quality control.

Concerning the motivation for these changes, Morley explained it was a convergence of different factors. The decreasing cost of sensors, abundant computing resources and highly accurate AI methods — like deep learning and graphical modeling — all contributed to Medtronic’s decision to embrace new practices.

With AI integration in the manufacturing process, engineers can prioritize their more pressing responsibilities, with less stress over smaller tasks. As an example, a predictive algorithm can collect data on a medical device with defects. It can then determine whether a production line would scrap the device.

If the algorithm shows a 99% chance the production line would scrap the device, the AI won’t send it to the engineering department. It’s a small but effective measure which reduces inefficiencies and streamlines the production process — only one example of how medical manufacturing has evolved.

Industry Transformation

The promise of artificial intelligence for predictive maintenance is notable. When data scientists collect and analyze information about the status of manufacturing equipment, they can find trends and make correlations to adjust maintenance schedules —which, in turn, reduces the risk of downtime.

Since an hour of unplanned downtime costs an average of $260,000 across all businesses, technologies that assist with predictive maintenance are indispensable. In the future, medical manufacturers will likely adopt artificial intelligence to preempt problems and enhance all processes within their organization.

As for alternative functions of artificial intelligence, the possibilities are exciting. AI technology will provide more opportunities for mass customization on the shop floor. These systems could take custom orders to add or remove components from standard procedural trays, allowing for a greater degree of flexibility.

Ultimately, the coordination of co-working robots, intelligent automation, machine learning and the Internet of Things will transform medical manufacturing. More than that, it’ll improve the manufacturing industry as a whole, leading to incredible improvements in industrial production.

Moving Forward

Despite the potential of artificial intelligence for medical manufacturing, companies have still shown reluctance around these technologies. AI is still in the proof-of-concept phase for many manufacturing processes, and explainability also presents an issue. Professionals are less receptive to systems they don’t understand, especially as the medical industry can be slow to implement new technology unless they see its value and ability to save them time.

Even with these challenges, specific companies have shown a willingness to adapt their manufacturing with AI, and that represents a significant step forward. As we move into the next decade, it’s exciting to speculate how medical manufacturing will continue to change. AI will almost certainly have a substantial role to play.


Emily covers topics in manufacturing and environmental technology. You can follow her blog, Conservation Folks, or her Twitter to get the latest updates.

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