
Pharmaceutical
In the pharmaceutical industry, industrial AI visual quality inspection advances, covering packaging label checks, medicine bottle/blister appearance defect detection, and production quality control. Its automation and high precision boost efficiency and reduce manual pressure. Yet pain points remain: complex environments hurt data quality; diverse specs hinder universal algorithms; tiny defects are hard to stably detect; annotation is costly, and integration compatibility needs improvement.
Aqrose AI Solution Overview
Aqrose provides AIDI algorithm-based visual inspection solutions for the pharmaceutical industry, covering key scenarios. For Blister Packaging Inspection, its segmentation algorithm addresses low-contrast and small-area defect issues, with a speed of 400pcs/min to improve yield. For Three-Phase Code Inspection, positioning and recognition algorithms accurately locate printing positions, featuring strong anti-interference and over 99% accuracy. For Appearance Inspection of Medicine Bottles, the "fast detection + segmentation" algorithm achieves a 90% first-pass rate, with a universal model adapting to product changes.

Full-process Inspection of Pharmaceutical Industry
Packaging Inspection
Critical Information Recognition
Container & Product Appearance
Success Cases
- Medicine bottles are core containers for pharmaceutical packaging, mostly made of plastic (such as PP, PE) or glass. They typically include structures like the bottle body, bottle mouth threads, and bottle cap, and must meet pharmaceutical standards for sealing and contamination prevention.The inspe
- Three-phase code is a general term for the production date, expiration date, and batch number marked on pharmaceutical packaging. It is usually presented on the surface of labels, aluminum foil, and other packaging via spraying, stamping, or laser engraving.Multiple challenges exist in inspection: C
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