Three Ways To Enhance Pharmaceutical Packaging Lines

This white paper focuses on optical character recognition (OCR) and its extensive use in pharmaceutical packaging for compliance with date and lot tracking regulations. Machine vision OCR helps manufacturers adhere to these mandates in an effi cient and cost-effective manner, and can also improve line performance. Three common applications are described here: - Ensuring code presence and verifi cation of readability - Tracking products throughout the supply chain - Matching product labels to contents

OCR, or optical character recognition, is a vision system tool that is widely used in the pharmaceutical packaging industry. Like barcode technology, OCR is a data capture methodology. Its primary advantage is that it encodes information in a format that is both machine-readable and human-readable, while barcodes and 2D symbols are only machine-readable. OCR turns printed text characters from a digital image into a string of characters that can be decoded (read) by the system, and then moved through subsequent steps in the production process as defi ned by the control software. The simplest and most reliable method for optical character recognition relies on specifi c OCR fonts and templates that are designed for these applications. However, machine vision’s powerful functionality incorporates teachable OCR systems that can be trained to recognize characters in a user-defi ned font – a useful feature given the wide array of available printing technologies and the range of printed characters produced by them.

Lot codes, batch codes, and expiration dates have become necessary in the pharmaceutical industry, which has stringent labeling requirements to help ensure consumer safety and to prevent product diversion and counterfeiting. The capability of machine vision to read these text strings reliably, at high speeds, has become indispensible in today’s manufacturing environment. OCR and subsequent data retrieval help to ensure the smooth fl ow of information throughout the manufacturing and distribution process.