Computer Vision Based Quality Inspection in Injectable Ampoules/Vials

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Team Name	Nupeak Neurons
Track	Health Care & Life Sciences
Use Case	Computer Vision Based Quality Inspection in Injectable Ampoules/Vials Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects and then react to what they “see.” Our goal is to leverage Computer Vision in manufacturing process the Pharma Industry, to automate the visual inspection of Ampoules & Vials. In the context of Quality Inspection for Injectable Ampoules & Vials, real-time assessments are conducted leveraging cameras, image processing methods, and cutting-edge machine learning algorithms. The Image & Videos captured via Industrial Cameras, will inspect against known defects and non-defects via Convolutional Neural Networks (CNN). After the defects are learned by the model, the scoring logic is sent to a real-time inference engine software that is installed on the inspection machines. This enables real-time scoring of the image components as they are scanned. It also enhances operator efficiency by relieving operators of their manual visual inspection work.
Technology	Python, SAS VDMML, SAS Studio
Region	India, Asia Pacific
Team lead	Tushar Sonawane @tushar_sonawane
Team members	Dipen Shah @Dipenshah  Vishal Patil @vishalbpatil  Rujhan Jain @rujhanjain
Social media handles	NA
Is your team interested in participating in an interview?	Y
Optional: Expand on your technology expertise	NA