Development and Evaluation of a Vision Inspection System for Plastic Bottle Measurement

Abstract:

To quickly adapt to the fast-changing conditions in the modern markets and the global economy, manufacturers are adopting digital manufacturing methods and tools, instead of traditional paper-based processes, to release higher quality products more quickly and at a lower cost. The pharmaceutical industry has a high production standard in the world. Delivering a defective product (or package) can lead to customer complaints and may even result in the entire product series being returned in severe cases. To reach out to the tiny space of products and achieve a high pharmaceutical product dimensional standard, manufacturers must introduce commercial vision inspection systems for the quality inspection process. However, conventional commercial inspection systems are often of a high cost, thus making them unaffordable for micro, small, and medium-sized enterprises (MSMEs), particularly in developing countries. This paper proposes a cost-effective vision inspection system that intelligently measures critical plastic bottle dimensions. The system comprises three 4K industrial cameras, two LED lights, a customized measurement platform, and a laptop, making it more affordable for MSMEs. Under the appropriate illumination setting, a plastic bottle is positioned on the stage and viewed by the laptop screen in real-time. The middle camera captures the bottle image, followed by a series of image processing operations to obtain the region of interest (ROI), such as the snap cap radius and height. Then, extract the target bottle edges with the Canny edge detector. Lastly, the system calculates the pixel-based distance and converts it to the measurement results for records or decision-making. The proposed method demonstrates reliable dimensional detection abilities, offering a potential solution to reduce human workload and improve inspection productivity in measuring pharmaceutical bottles.

• Periodical: Advances in Science and Technology (Volume 149)
• Pages: 41-50
• DOI: https://doi.org/10.4028/p-HPT9vc
• Online since: April 2024
• Authors: Jiwei Zhou*, Nathan W. Hartman
• Keywords: Inspection, Machine Vision, Vision Inspection System

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