Surface defects, presence/absence of chamfer
Our client is the largest contract manufacturing pharmaceutical company of India. The organization deals in the manufacturing and export of formulations in a wide spectrum of dosage forms & therapeutic segments. With 5000+ employees, the company is currently supplying to almost all Indian and multinational pharmaceutical companies across the globe. In a span of few years, the organization has become the icon of Indian Pharmaceutical manufacturing industry and currently manufactures around 9% to 10% of the country’s total medicinal requirements.
Client Name: Harsh Cngineers
Problems Faced By Our Client:
- Online reading of QR code and characters on Blisters was soporific and most importantly less accurate.
- Another major issue was with the time consumption of the same task.
Technology Introduced By Qualitas Technologies:
Artificial Intelligence & Deep Neural Network which helps in optimal decision making and generating accurate results of Image processing. Compared to traditional OCR algorithms, AI-based OCR is far more accurate, resulting in 100% accuracy. Not only is it more accurate, but it’s very easy to maintain and update when new characters and letters are to be added to the recognizable character list.
- In the proposed system, Blister passes on the conveyor and the presence of the blister is sensed by the sensor and a trigger is generated for image acquisition.
- On image acquisition, the acquired image is processed and OCR operation is performed to read the characters printed on the tube.
- The read characters are displayed in the Qualitas System GUI.
- Result (OK/NOT OK), is sent to PLC by the DIO module present in the vision system controller.
The proposed solution worked for all the variants.