Conor Kennedy

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MERCK
Conor Kennedy works for Merck’s Global Engineering Solutions group on installing new AVI machinery for vaccine manufacturing. He joined Merck with the West Point vision inspection group and supported their suite of inspection systems at that site as well as the packaging vision inspection team. He was a founding member of the Merck Machine Learning for Automated Vision Inspection project. Conor graduated from the Pennsylvania State University with a BS in mechanical engineering; he conducted research with the Penn State Intelligent Vehicles and Systems Lab and Multiscale Thermal Fluids and Energy Lab. He is currently attending Drexel University, where he is studying for a master’s degree in electrical engineering.

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Figure 1: CNN model training process and validation results for a lyophilized vial AVI system.
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Vision Inspection Using Machine Learning/Artificial Intelligence

Pharmaceutical companies rely on automated vision inspection (AVI) systems to help ensure product safety. Although these systems overcome challenges associated with manual inspection, they can be hindered by limitations in their programming—if the system is programmed to consider every variation in inspection conditions, it is likely to falsely identify defects in safe products. This article...