Pharma 5.0

How AI vision inspection is transforming medical device quality assurance (part II)

Published: 24-Sep-2025

In the second half of this article, Rockwell’s Senior Product Manager, Carl Lewis, examines adoption and implementation practices, scaling for quality and future applications

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As demand rises and production volumes grow, maintaining consistent quality inspection becomes increasingly challenging with traditional methods (see Part I).

AI vision systems make it possible to scale consistent quality inspection seamlessly across multiple lines and facilities, ensuring uniform standards. For medical device makers, adoption is driving measurable benefits.

Catching more defects: AI vision systems detect subjective quality issues that may otherwise go unnoticed, thereby improving overall product quality.

Driving continuous improvement: Detailed analytics uncover root causes of recurring issues. For example, a diabetes care manufacturer used AI inspection to track intermittent packaging defects to a specific machine component that was wearing unevenly. Correcting the issue’s root cause eliminated the problem.

Optimising human resources: Experienced quality professionals are amongst the most experienced in a medical device plant. By automating repetitive inspection tasks, AI vision systems make it possible to free these people up to focus on higher-value work, such as process optimisation and resolving issues.  

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