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.
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| 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 |
Pitch Video:
Jury Video :
